fusionbibs.bib

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@COMMENT{{The file containts ABBREVIATED versions for abbreviations commonly
         used in publishers and journal names. It has to be included in
         your \bibliography... list first. File has to be used in
         conjoint with abb-full.bib which containts full versions
         of the same names, so it must be of the same length as this one}}
@COMMENT{{******** Publishers ********}}
@COMMENT{{**** Wouldn't it be nice if the publisher's address ****
     **** could get put into entries automatically?      ****}}
@COMMENT{{******** Misc ********}}
@COMMENT{{******** Journals ********}}
@COMMENT{{******** Prefixes ********}}
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@COMMENT{{The bibliography was collected to contain papers relevant for the
 methods of multimodal brain imaging.  References herein were
 originally used in HHP05.  I hope you find the bibliography
 useful and I would greatly appreciate any comments/suggestions

 -- Yaroslav Halchenko
    yoh(a)onerussian.com

}}
@COMMENT{{**** Entries ****}}
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@PREAMBLE{{\newcommand{\noopsort}[1]{} }}
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@ARTICLE{AB02,
  author = {Arthurs, O. J. and Boniface, S.},
  title = {How well do we understand the neural origins of the
                   f{MRI} {BOLD} signal?},
  journal = {Trends Neurosci},
  volume = {25},
  number = {1},
  pages = {27-31},
  abstract = {The successful use of functional magnetic resonance
                   imaging (fMRI) as a way of visualizing cortical
                   function depends largely on the important relationships
                   between the signal observed and the underlying neuronal
                   activity that it is believed to represent. Currently, a
                   relatively direct correlation seems to be favoured
                   between fMRI signals and population synaptic activity
                   (including inhibitory and excitatory activity), with a
                   secondary and potentially more variable correlation
                   with cellular action potentials.},
  authoraddress = {Wolfson Brain Imaging Centre, University of Cambridge,
                   Box 65, Addenbrooke's Hospital, Hills Road, CB2 2QQ,
                   Cambridge, UK.},
  keywords = {Action Potentials/physiology ; Animals ; Cerebral
                   Cortex/*physiology ; Cerebrovascular
                   Circulation/*physiology ; Excitatory Postsynaptic
                   Potentials/physiology ; Human ; *Magnetic Resonance
                   Imaging ; Neural Inhibition/physiology ;
                   Neurons/*physiology ; Support, Non-U.S. Gov't ;
                   Synaptic Transmission/*physiology},
  language = {eng},
  medline-aid = {S0166223600019950 [pii]},
  medline-da = {20020121},
  medline-dcom = {20020227},
  medline-edat = {2002/01/22 10:00},
  medline-ein = {Trends Neurosci 2002 Mar;25(3):169},
  medline-fau = {Arthurs, Owen J ; Boniface, Simon},
  medline-is = {0166-2236},
  medline-jid = {7808616},
  medline-lr = {20040116},
  medline-mhda = {2002/02/28 10:01},
  medline-own = {NLM},
  medline-pl = {England},
  medline-pmid = {11801335},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {36},
  medline-sb = {IM},
  medline-so = {Trends Neurosci 2002 Jan;25(1):27-31.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11801335},
  year = 2002
}
@ARTICLE{AB03,
  author = {Arthurs, O. J. and Boniface, S. J.},
  title = {What aspect of the f{MRI} {BOLD} signal best reflects
                   the underlying electrophysiology in human somatosensory
                   cortex?},
  journal = {Clin Neurophysiol},
  volume = {114},
  number = {7},
  pages = {1203-1209},
  abstract = {The interpretation of task-induced functional imaging
                   of the brain is critically dependent on understanding
                   the relationship between observed haemodynamic
                   responses and the underlying neural changes. However,
                   the precise nature of this neurovascular coupling
                   relationship remains unknown. In particular, it is
                   unclear which measure of functional magnetic resonance
                   imaging blood oxygen level dependent (fMRI BOLD)
                   activity is the best correlate of neural activity. We
                   measured the somatosensory evoked potential (SEP)
                   amplitude at the scalp, and fMRI BOLD signal to
                   increases in intensity of contralateral median nerve
                   electrical stimulation in healthy non-anaesthetised
                   subjects. We compared correlation analyses between SEP
                   amplitude and both peak voxel fMRI BOLD percentage
                   signal change and mean voxel fMRI BOLD percentage
                   signal change across a somatosensory cluster, and we
                   also performed a voxel-by-voxel correlation between
                   fMRI BOLD activity and SEP amplitude. We found that
                   fMRI BOLD changes in primary somatosensory cortex
                   correlate significantly with SEP amplitudes, suggesting
                   a linear neurovascular coupling relationship under the
                   conditions investigated. We also found that mean
                   changes across a cluster correlate less well with SEP
                   amplitude than peak voxel levels. This suggests that
                   the area of haemodynamic activity correlating with SEP
                   amplitude is smaller than the entire cluster observed.},
  authoraddress = {Wolfson Brain Imaging Centre, University of Cambridge,
                   Box 65, Addenbrooke's Hospital, Hills Road, Cambridge,
                   CB2 2QQ, UK.},
  keywords = {Adult ; Brain Mapping ; Comparative Study ; Electric
                   Stimulation ; Electrophysiology/*methods ; Evoked
                   Potentials, Somatosensory/*physiology ; Female ;
                   Hemodynamic Processes/physiology ; Human ; *Magnetic
                   Resonance Imaging ; Male ; Nerve Net/physiology ;
                   Oxygen/metabolism ; Somatosensory Cortex/*physiology ;
                   Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1388245703000804 [pii]},
  medline-da = {20030704},
  medline-dcom = {20030820},
  medline-edat = {2003/07/05 05:00},
  medline-fau = {Arthurs, O J ; Boniface, S J},
  medline-is = {1388-2457},
  medline-jid = {100883319},
  medline-lr = {20031114},
  medline-mhda = {2003/08/21 05:00},
  medline-own = {NLM},
  medline-pl = {Netherlands},
  medline-pmid = {12842716},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Clin Neurophysiol 2003 Jul;114(7):1203-9.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12842716},
  year = 2003
}
@ARTICLE{ABH+04,
  author = {Adjamian, P. and Barnes, G. R. and Hillebrand, A. and
                   Holliday, I. E. and Singh, K. D. and Furlong, P. L. and
                   Harrington, E. and Barclay, C. W. and Route, P. J.},
  title = {Co-registration of magnetoencephalography with
                   magnetic resonance imaging using bite-bar-based
                   fiducials and surface-matching},
  journal = {Clin Neurophysiol},
  volume = {115},
  number = {3},
  pages = {691-698},
  abstract = {OBJECTIVE: To introduce a new technique for
                   co-registration of Magnetoencephalography (MEG) with
                   magnetic resonance imaging (MRI). We compare the
                   accuracy of a new bite-bar with fixed fiducials to a
                   previous technique whereby fiducial coils were attached
                   proximal to landmarks on the skull. METHODS: A bite-bar
                   with fixed fiducial coils is used to determine the
                   position of the head in the MEG co-ordinate system.
                   Co-registration is performed by a surface-matching
                   technique. The advantage of fixing the coils is that
                   the co-ordinate system is not based upon arbitrary and
                   operator dependent fiducial points that are attached to
                   landmarks (e.g. nasion and the preauricular points),
                   but rather on those that are permanently fixed in
                   relation to the skull. RESULTS: As a consequence of
                   minimizing coil movement during digitization, errors in
                   localization of the coils are significantly reduced, as
                   shown by a randomization test. Displacement of the
                   bite-bar caused by removal and repositioning between
                   MEG recordings is minimal ( approximately 0.5 mm), and
                   dipole localization accuracy of a somatosensory mapping
                   paradigm shows a repeatability of approximately 5 mm.
                   The overall accuracy of the new procedure is greatly
                   improved compared to the previous technique.
                   CONCLUSIONS: The test-retest reliability and accuracy
                   of target localization with the new design is superior
                   to techniques that incorporate anatomical-based
                   fiducial points or coils placed on the circumference of
                   the head.},
  authoraddress = {The Wellcome Trust Laboratory for MEG Studies,
                   Neurosciences Research Institute, Aston University,
                   Birmingham B4 7ET, UK. adjamiap@aston.ac.uk},
  keywords = {Brain/anatomy & histology ; Comparative Study ; Data
                   Collection ; Equipment Design ; Head ; Human ; *Image
                   Processing, Computer-Assisted ; *Magnetic Resonance
                   Imaging ; *Magnetoencephalography ; Monte Carlo Method
                   ; Posture ; Reproducibility of Results ; Stereotaxic
                   Techniques/*instrumentation/standards},
  language = {eng},
  medline-aid = {10.1016/j.clinph.2003.10.023 [doi] ; S1388245703003791
                   [pii]},
  medline-da = {20040323},
  medline-dcom = {20040407},
  medline-edat = {2004/03/24 05:00},
  medline-fau = {Adjamian, P ; Barnes, G R ; Hillebrand, A ; Holliday,
                   I E ; Singh, K D ; Furlong, P L ; Harrington, E ;
                   Barclay, C W ; Route, P J G},
  medline-is = {1388-2457},
  medline-jid = {100883319},
  medline-mhda = {2004/04/08 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Oct/20 [accepted]},
  medline-pl = {Netherlands},
  medline-pmid = {15036065},
  medline-pst = {ppublish},
  medline-pt = {Evaluation Studies ; Journal Article},
  medline-sb = {IM},
  medline-so = {Clin Neurophysiol 2004 Mar;115(3):691-8.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15036065},
  year = 2004
}
@ARTICLE{ADS+06,
  author = {Anemuller, Jorn and Duann, Jeng-Ren and Sejnowski,
                   Terrence, J. and Makeig, Scott},
  title = {Spatio-temporal dynamics in f{MRI} recordings revealed
                   with complex independent component analysis},
  journal = {Neurocomputing},
  volume = {69},
  pages = {1502-1512},
  abstract = { Independent component analysis (ICA) of functional
                   magnetic resonance imaging (fMRI) data is commonly
                   carried out under the assumption that each source may
                   be represented as a spatially fixed pattern of
                   activation, which leads to the instantaneous mixing
                   model. To allow modeling patterns of spatio-temporal
                   dynamics, in particular, the flow of oxygenated blood,
                   we have developed a convolutive ICA approach: spatial
                   complex ICA applied to frequency-domain fMRI data. In
                   several frequency-bands, we identify components
                   pertaining to activity in primary visual cortex (V1)
                   and blood supply vessels. One such component, obtained
                   in the 0.10 Hz band, is analyzed in detail and found to
                   likely reflect flow of oxygenated blood in V1.},
  medline-jo = {Neurocomputing},
  medline-kw = {Complex independent component analysis (complex ICA) ;
                   Convolution model ; Spatio-temporal dynamics ;
                   Functional magnetic resonance imaging (fMRI) ;
                   Hemodynamic response ; Primary visual cortex (VI) ;
                   Biomedical signal analysis ; Statistical signal
                   processing},
  medline-t1 = {Spatio-temporal dynamics in fMRI recordings revealed
                   with complex independent component analysis},
  medline-ty = {JOUR},
  url = {http://www.sciencedirect.com/science/article/B6V10-4JXRX2J-1/2/540dffc57cf39b4dd4cfd6a8c14107ac},
  medline-vl = {In Press, Corrected Proof},
  year = 2006
}
@ARTICLE{AI02,
  author = {Attwell, D. and Iadecola, C.},
  title = {The neural basis of functional brain imaging signals},
  journal = {Trends Neurosci},
  volume = {25},
  number = {12},
  pages = {621-625},
  abstract = {The haemodynamic responses to neural activity that
                   underlie the blood-oxygen-level-dependent (BOLD) signal
                   used in functional magnetic resonance imaging (fMRI) of
                   the brain are often assumed to be driven by energy use,
                   particularly in presynaptic terminals or glia. However,
                   recent work has suggested that most brain energy is
                   used to power postsynaptic currents and action
                   potentials rather than presynaptic or glial activity
                   and, furthermore, that haemodynamic responses are
                   driven by neurotransmitter-related signalling and not
                   directly by the local energy needs of the brain. A firm
                   understanding of the BOLD response will require
                   investigation to be focussed on the neural signalling
                   mechanisms controlling blood flow rather than on the
                   locus of energy use.},
  authoraddress = {Dept of Physiology, University College London, Gower
                   Street, UK. d.attwell@ucl.ac.uk},
  keywords = {Action Potentials/physiology ; Astrocytes/physiology ;
                   Brain/*blood supply/physiology ; Brain Mapping ;
                   Cerebrovascular Circulation/*physiology ; Energy
                   Metabolism/*physiology ; Human ; Magnetic Resonance
                   Imaging ; Neural Inhibition/physiology ; Presynaptic
                   Terminals/physiology ; Support, Non-U.S. Gov't ;
                   Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {S0166223602022646 [pii]},
  medline-da = {20021126},
  medline-dcom = {20030113},
  medline-edat = {2002/11/26 04:00},
  medline-fau = {Attwell, David ; Iadecola, Costantino},
  medline-is = {0166-2236},
  medline-jid = {7808616},
  medline-mhda = {2003/01/14 04:00},
  medline-own = {NLM},
  medline-pl = {England},
  medline-pmid = {12446129},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {66},
  medline-sb = {IM},
  medline-so = {Trends Neurosci 2002 Dec;25(12):621-5.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12446129},
  year = 2002
}
@ARTICLE{AJM+04,
  author = {Arthurs, O. J. and Johansen-Berg, H. and Matthews, P.
                   M. and Boniface, S. J.},
  title = {Attention differentially modulates the coupling of
                   f{MRI} {BOLD} and evoked potential signal amplitudes in
                   the human somatosensory cortex},
  journal = {Exp Brain Res},
  volume = {157},
  number = {3},
  pages = {269-274},
  abstract = {Blood oxygenation dependent contrast (BOLD) fMRI is
                   used increasingly to probe "connectivity" based on
                   temporal correlations between signals from different
                   brain regions. This approach assumes that there is
                   constant local coupling of neuronal activity to the
                   associated BOLD response. Here we test the alternative
                   hypothesis that there is not a fixed relationship
                   between these by determining whether attention
                   modulates apparent neurovascular coupling. Electrical
                   stimulation of the median nerve was applied with and
                   without a concurrent distractor task (serial
                   subtraction). Increasing stimulation intensity
                   increased discomfort ratings ( p<0.001) and was
                   associated with a significant increase in both
                   somatosensory evoked potential (SEP) N20-P25 amplitude
                   and BOLD fMRI response in the contralateral primary
                   (SI) and bilaterally in the secondary somatosensory
                   cortices. Attention to stimulation was reduced during
                   distractor task performance and resulted in an overall
                   trend for reduction in discomfort ( p=0.056), which was
                   significant at the highest stimulation level ( p<0.05).
                   A volume of interest analysis confined to SI confirmed
                   a reduction in BOLD response with distraction (
                   p<0.001). However, distraction did not measurably
                   affect SEP magnitude. The quantitative relationship
                   between the BOLD fMRI response and the local field
                   potential measured by the early SEP response therefore
                   varies with attentional context. This may be a
                   consequence of differences in either local spatial or
                   temporal signal summation for the two methods. Either
                   interpretation suggests caution in assuming a simple,
                   fixed relationship between local BOLD changes and
                   related electrophysiological activity.},
  authoraddress = {Wolfson Brain Imaging Centre, University of Cambridge,
                   Addenbrooke's Hospital, Hills Road, Box 65, Cambridge,
                   CB2 2QQ, UK.},
  language = {eng},
  medline-aid = {10.1007/s00221-003-1827-4 [doi]},
  medline-da = {20040714},
  medline-dep = {20040619},
  medline-edat = {2004/06/29 05:00},
  medline-fau = {Arthurs, O J ; Johansen-Berg, H ; Matthews, P M ;
                   Boniface, S J},
  medline-is = {0014-4819},
  medline-jid = {0043312},
  medline-mhda = {2004/06/29 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Apr/08 [received] ; 2003/Dec/02 [accepted] ;
                   2004/Jun/19 [aheadofprint]},
  medline-pl = {Germany},
  medline-pmid = {15221172},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Exp Brain Res 2004 Aug;157(3):269-74. Epub 2004 Jun
                   19.},
  medline-stat = {in-process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15221172},
  year = 2004
}
@ARTICLE{AJT00,
  author = {Allen, P. J. and Josephs, O. and Turner, R.},
  title = {A method for removing imaging artifact from continuous
                   {EEG} recorded during functional {MRI}},
  journal = {NeuroImage},
  volume = {12},
  number = {2},
  pages = {230-239},
  abstract = {Combined EEG/fMRI recording has been used to localize
                   the generators of EEG events and to identify subject
                   state in cognitive studies and is of increasing
                   interest. However, the large EEG artifacts induced
                   during fMRI have precluded simultaneous EEG and fMRI
                   recording, restricting study design. Removing this
                   artifact is difficult, as it normally exceeds EEG
                   significantly and contains components in the EEG
                   frequency range. We have developed a recording system
                   and an artifact reduction method that reduce this
                   artifact effectively. The recording system has large
                   dynamic range to capture both low-amplitude EEG and
                   large imaging artifact without distortion (resolution 2
                   microV, range 33.3 mV), 5-kHz sampling, and low-pass
                   filtering prior to the main gain stage. Imaging
                   artifact is reduced by subtracting an averaged artifact
                   waveform, followed by adaptive noise cancellation to
                   reduce any residual artifact. This method was validated
                   in recordings from five subjects using periodic and
                   continuous fMRI sequences. Spectral analysis revealed
                   differences of only 10 to 18\% between EEG recorded in
                   the scanner without fMRI and the corrected EEG.
                   Ninety-nine percent of spike waves (median 74 microV)
                   added to the recordings were identified in the
                   corrected EEG compared to 12\% in the uncorrected EEG.
                   The median noise after artifact reduction was 8 microV.
                   All these measures indicate that most of the artifact
                   was removed, with minimal EEG distortion. Using this
                   recording system and artifact reduction method, we have
                   demonstrated that simultaneous EEG/fMRI studies are for
                   the first time possible, extending the scope of
                   EEG/fMRI studies considerably.},
  authoraddress = {Department of Clinical Neurophysiology, National
                   Hospital for Neurology and Neurosurgery, University
                   College London Hospitals, Queen Square, London, WC1N
                   3BG, United Kingdom.},
  keywords = {Adult ; Algorithms ; *Artifacts ;
                   Electroencephalography/*methods/statistics & numerical
                   data ; Female ; Human ; Image Processing,
                   Computer-Assisted/*methods/statistics & numerical data
                   ; Magnetic Resonance Imaging/*methods/statistics &
                   numerical data ; Male ; Reproducibility of Results ;
                   Signal Processing, Computer-Assisted},
  language = {eng},
  medline-aid = {10.1006/nimg.2000.0599 [doi] ; S1053811900905998 [pii]},
  medline-ci = {Copyright 2000 Academic Press.},
  medline-da = {20001011},
  medline-dcom = {20001011},
  medline-edat = {2000/07/29 11:00},
  medline-fau = {Allen, P J ; Josephs, O ; Turner, R},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20001218},
  medline-mhda = {2000/10/14 11:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10913328},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2000 Aug;12(2):230-9.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10913328},
  year = 2000
}
@ARTICLE{AMT+03,
  author = {Anami, K. and Mori, T. and Tanaka, F. and Kawagoe, Y.
                   and Okamoto, J. and Yarita, M. and Ohnishi, T. and
                   Yumoto, M. and Matsuda, H. and Saitoh, O.},
  title = {Stepping stone sampling for retrieving artifact-free
                   electroencephalogram during functional magnetic
                   resonance imaging},
  journal = {NeuroImage},
  volume = {19},
  number = {2.1},
  pages = {281-295},
  abstract = {Ballistocardiogram and imaging artifacts cause major
                   interference with simultaneous electroencephalogram
                   (EEG) and functional magnetic resonance imaging (fMRI)
                   recording. In particular, the large amplitude of the
                   imaging artifact precludes easy retrieval of EEG
                   signals during fMRI scanning. Recording with 20,000-Hz
                   digitization rate combined with 3000-Hz low-pass filter
                   revealed the real waveform of the imaging artifact, in
                   which it was elucidated that each artifact peak
                   precisely corresponded to each gradient component and
                   actually had differential waveforms of the original
                   gradient pulses. Based on this finding, to retrieve EEG
                   signal during fMRI acquisition, a blip-type echo planar
                   sequence was modified so that EEG sampling might be
                   performed at every 1000 micros (digitization rate 1000
                   Hz) exclusively in the period in which the artifact
                   resided around the baseline level. This method, called
                   "stepping stone sampling," substantially attenuated the
                   amplitude of the imaging artifact. The remnant of the
                   artifact was subtracted from the averaged artifact
                   waveform. In human studies, alpha activity was
                   successfully retrieved by inspection, and its
                   attenuation/augmentation was observed during eyes
                   open/closed periods. Fast Fourier transform analysis
                   further revealed that even from DC up to 120 Hz,
                   retrieved EEG data during scanning had very similar
                   power distributions to the data retrieved during no
                   scanning, implying the availability of the
                   high-frequency band of the retrieved EEG signals,
                   including even the gamma band.},
  authoraddress = {Department of Psychiatry, National Center Hospital for
                   Mental, Nervous, and Muscular Disorders, National
                   Center of Neurology and Psychiatry, Tokyo 187-8551,
                   Japan. anami@ncnpmusashi.gr.jp},
  keywords = {Adult ; Alpha Rhythm ; *Artifacts ;
                   Ballistocardiography/methods ; Brain Mapping/methods ;
                   Cerebral Cortex/*physiology ; Echo-Planar
                   Imaging/methods ; Electroencephalography/*methods ;
                   Female ; Fourier Analysis ; Human ; Image
                   Interpretation, Computer-Assisted/*methods ; Magnetic
                   Resonance Imaging/*methods ; Male ; Phantoms, Imaging ;
                   Reference Values ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S105381190300048X [pii]},
  medline-da = {20030619},
  medline-dcom = {20030826},
  medline-edat = {2003/06/20 05:00},
  medline-fau = {Anami, Kimitaka ; Mori, Takeyuki ; Tanaka, Fumiko ;
                   Kawagoe, Yusuke ; Okamoto, Jun ; Yarita, Masaru ;
                   Ohnishi, Takashi ; Yumoto, Masato ; Matsuda, Hiroshi ;
                   Saitoh, Osamu},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2003/08/27 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12814579},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2003 Jun;19(2 Pt 1):281-95.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12814579},
  year = 2003
}
@ARTICLE{APS+04,
  author = {Angelone, L. M. and Potthast, A. and Segonne, F. and
                   Iwaki, S. and Belliveau, J. W. and Bonmassar, G.},
  title = {Metallic electrodes and leads in simultaneous
                   {EEG}-{MRI}: specific absorption rate ({SAR})
                   simulation studies},
  journal = {Bioelectromagnetics},
  volume = {25},
  number = {4},
  pages = {285-295},
  abstract = {The purpose of this study was to investigate the
                   changes in specific absorption rate (SAR) in human-head
                   tissues while using nonmagnetic metallic
                   electroencephalography (EEG) electrodes and leads
                   during magnetic resonance imaging (MRI). A realistic,
                   high resolution (1 mm(3)) head model from individual
                   MRI data was adopted to describe accurately thin
                   tissues, such as bone marrow and skin. The RF power
                   dissipated in the human head was evaluated using the
                   FDTD algorithm. Both surface and bird cage coils were
                   used. The following numbers of EEG electrodes/leads
                   were considered: 16, 31, 62, and 124. Simulations were
                   performed at 128 and 300 MHz. The difference in SAR
                   between the electrodes/leads and no-electrodes
                   conditions was greater with the bird cage coil than
                   with the surface coil. The peak 1 g averaged SAR values
                   were highest at 124 electrodes, increasing to as much
                   as two orders of magnitude (x172.3) at 300 MHz compared
                   to the original value. At 300 MHz, there was a fourfold
                   (x3.6) increase of SAR averaged over the bone marrow,
                   and a sevenfold (x7.4) increase in the skin. At 128
                   MHz, there was a fivefold (x5.6) increase of whole head
                   SAR. Head models were obtained from two different
                   subjects, with an inter-subject whole head SAR
                   variability of 3\%. .},
  authoraddress = {MGH/MIT/HMS Athinoula A. Martinos Center for
                   Functional Imaging, Charlestown, Massachusetts 02129,
                   USA. angelone@nmr.mgh.harvard.edu},
  keywords = {Adult ; *Electrodes ;
                   Electroencephalography/*instrumentation ; Human ;
                   Magnetic Resonance Imaging/*instrumentation ; Male ;
                   Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1002/bem.10198 [doi]},
  medline-ci = {Copyright 2004 Wiley-Liss, Inc.},
  medline-da = {20040428},
  medline-dcom = {20040903},
  medline-edat = {2004/04/29 05:00},
  medline-fau = {Angelone, Leonardo M ; Potthast, Andreas ; Segonne,
                   Florent ; Iwaki, Sunao ; Belliveau, John W ; Bonmassar,
                   Giorgio},
  medline-is = {0197-8462},
  medline-jid = {8008281},
  medline-mhda = {2004/09/04 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {15114638},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Bioelectromagnetics 2004 May;25(4):285-95.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15114638},
  year = 2004
}
@ARTICLE{AS04,
  author = {Ahlfors, S. P. and Simpson, G. V.},
  title = {Geometrical interpretation of f{MRI}-guided
                   {MEG}/{EEG} inverse estimates},
  journal = {NeuroImage},
  volume = {22},
  number = {1},
  pages = {323-332},
  abstract = {Magneto- and electroencephalography (MEG/EEG) and
                   functional magnetic resonance imaging (fMRI) provide
                   complementary information about the functional
                   organization of the human brain. An important advantage
                   of MEG/EEG is the millisecond time resolution in
                   detecting electrical activity in the cerebral cortex.
                   The interpretation of MEG/EEG signals, however, is
                   limited by the difficulty of determining the spatial
                   distribution of the neural activity. Functional MRI can
                   help in the MEG/EEG source analysis by suggesting
                   likely locations of activity. We present a geometric
                   interpretation of fMRI-guided inverse solutions in
                   which the MEG/EEG source estimate minimizes a distance
                   to a subspace defined by the fMRI data. In this
                   subspace regularization (SSR) approach, the fMRI bias
                   does not assume preferred amplitudes for MEG/EEG
                   sources, only locations. Characteristic dependence of
                   the source estimates on the regularization parameters
                   is illustrated with simulations. When the fMRI
                   locations match the true MEG/EEG source locations, they
                   serve to bias the underdetermined MEG/EEG inverse
                   solution toward the fMRI loci. Importantly, when the
                   fMRI loci do not match the true MEG/EEG loci, the
                   solution is insensitive to those fMRI loci.},
  authoraddress = {MGH/MIT/HMS Athinoula A. Martinos Center for
                   Biomedical Imaging, Massachusetts General Hospital,
                   Harvard Medical School, 149 13th Street, Mailcode
                   149-2301, Charlestown, MA 02129, USA.
                   seppo@nmr.mgh.harvard.edu},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.12.044 [doi] ;
                   S1053811904000199 [pii]},
  medline-da = {20040427},
  medline-edat = {2004/04/28 05:00},
  medline-fau = {Ahlfors, Seppo P ; Simpson, Gregory V},
  medline-gr = {DA 09972/DA/NIDA ; MH/DA 52176/MH/NIMH ; NS
                   27900/NS/NINDS ; P41 RR 14075/RR/NCRR},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/04/28 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Aug/28 [received] ; 2003/Dec/18 [revised] ;
                   2003/Dec/23 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15110022},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 May;22(1):323-32.},
  medline-stat = {in-process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15110022},
  year = 2004
}
@ARTICLE{ASD+99,
  author = {Ahlfors, S. P. and Simpson, G. V. and Dale, A. M. and
                   Belliveau, J. W. and Liu, A. K. and Korvenoja, A. and
                   Virtanen, J. and Huotilainen, M. and Tootell, R. B. and
                   Aronen, H. J. and Ilmoniemi, R. J.},
  title = {Spatiotemporal activity of a cortical network for
                   processing visual motion revealed by {MEG} and f{MRI}.},
  journal = {J Neurophysiol},
  volume = {82},
  number = {5},
  pages = {2545-2555},
  abstract = {A sudden change in the direction of motion is a
                   particularly salient and relevant feature of visual
                   information. Extensive research has identified cortical
                   areas responsive to visual motion and characterized
                   their sensitivity to different features of motion, such
                   as directional specificity. However, relatively little
                   is known about responses to sudden changes in
                   direction. Electrophysiological data from animals and
                   functional imaging data from humans suggest a number of
                   brain areas responsive to motion, presumably working as
                   a network. Temporal patterns of activity allow the same
                   network to process information in different ways. The
                   present study in humans sought to determine which
                   motion-sensitive areas are involved in processing
                   changes in the direction of motion and to characterize
                   the temporal patterns of processing within this network
                   of brain regions. To accomplish this, we used both
                   magnetoencephalography (MEG) and functional magnetic
                   resonance imaging (fMRI). The fMRI data were used as
                   supplementary information in the localization of MEG
                   sources. The change in the direction of visual motion
                   was found to activate a number of areas, each
                   displaying a different temporal behavior. The fMRI
                   revealed motion-related activity in areas MT+ (the
                   human homologue of monkey middle temporal area and
                   possibly also other motion sensitive areas next to MT),
                   a region near the posterior end of the superior
                   temporal sulcus (pSTS), V3A, and V1/V2. The MEG data
                   suggested additional frontal sources. An equivalent
                   dipole model for the generators of MEG signals
                   indicated activity in MT+, starting at 130 ms and
                   peaking at 170 ms after the reversal of the direction
                   of motion, and then again at approximately 260 ms.
                   Frontal activity began 0-20 ms later than in MT+, and
                   peaked approximately 180 ms. Both pSTS and FEF+ showed
                   long-duration activity continuing over the latency
                   range of 200-400 ms. MEG responses in the region of V3A
                   and V1/V2 were relatively small, and peaked at longer
                   latencies than the initial peak in MT+. These data
                   revealed characteristic patterns of activity in this
                   cortical network for processing sudden changes in the
                   direction of visual motion.},
  authoraddress = {Dynamic Brain Imaging Laboratory, Departments of
                   Neurology and Neuroscience, Albert Einstein College of
                   Medicine, Bronx, New York 10461, USA.},
  keywords = {Adult ; *Brain Mapping ; Cerebral Cortex/*physiology ;
                   *Evoked Potentials, Visual ; Human ; Magnetic Resonance
                   Imaging/*methods ; Magnetoencephalography/*methods ;
                   Male ; Middle Aged ; Motion Perception/*physiology ;
                   Nerve Net/physiology ; Support, Non-U.S. Gov't ;
                   Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-da = {19991217},
  medline-dcom = {19991217},
  medline-edat = {1999/11/24},
  medline-fau = {Ahlfors, S P ; Simpson, G V ; Dale, A M ; Belliveau, J
                   W ; Liu, A K ; Korvenoja, A ; Virtanen, J ;
                   Huotilainen, M ; Tootell, R B ; Aronen, H J ;
                   Ilmoniemi, R J},
  medline-gr = {MH-DA52176/MH/NIMH ; NS27900/NS/NINDS ;
                   NS37462/NS/NINDS},
  medline-is = {0022-3077},
  medline-jid = {0375404},
  medline-lr = {20031114},
  medline-mhda = {1999/11/24 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10561425},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM ; S},
  medline-so = {J Neurophysiol 1999 Nov;82(5):2545-55.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10561425},
  year = 1999
}
@ARTICLE{AZD98,
  author = {Aguirre, G. K. and Zarahn, E. and D'esposito, M.},
  title = {The variability of human, {BOLD} hemodynamic
                   responses.},
  journal = {NeuroImage},
  volume = {8},
  number = {4},
  pages = {360-369},
  abstract = {Cerebral hemodynamic responses to brief periods of
                   neural activity are delayed and dispersed in time. The
                   specific shape of these responses is of some importance
                   to the design and analysis of blood oxygenation
                   level-dependent (BOLD), functional magnetic resonance
                   imaging (fMRI) experiments. Using fMRI scanning, we
                   examine here the characteristics and variability of
                   hemodynamic responses from the central sulcus in human
                   subjects during an event-related, simple reaction time
                   task. Specifically, we determine the contribution of
                   subject, day, and scanning session (within a day) to
                   variability in the shape of evoked hemodynamic
                   response. We find that while there is significant and
                   substantial variability in the shape of responses
                   collected across subjects, responses collected during
                   multiple scans within a single subject are less
                   variable. The results are discussed in terms of the
                   impact of response variability upon sensitivity and
                   specificity of analyses of event-related fMRI designs.},
  authoraddress = {Department of Neurology, Hospital of the University of
                   Pennsylvania, Philadelphia, Pennsylvania, 19104-4283,
                   USA.},
  keywords = {Adult ; Brain/anatomy & histology ; Cerebrovascular
                   Circulation/*physiology ; Female ; Hemodynamic
                   Processes/*physiology ; Human ; Image Processing,
                   Computer-Assisted/*methods ; Magnetic Resonance Imaging
                   ; Male ; Models, Neurological ; Oxygen/*blood ;
                   Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {S105381199890369X [pii]},
  medline-ci = {Copyright 1998 Academic Press.},
  medline-da = {19990112},
  medline-dcom = {19990112},
  medline-edat = {1998/11/13},
  medline-fau = {Aguirre, G K ; Zarahn, E ; D'esposito, M},
  medline-gr = {AG13483/AG/NIA ; NS01762/NS/NINDS},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {1998/11/13 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9811554},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {NeuroImage 1998 Nov;8(4):360-9.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9811554},
  year = 1998
}
@ARTICLE{BAB+04,
  author = {Bagshaw, A. P. and Aghakhani, Y. and Benar, C. G. and
                   Kobayashi, E. and Hawco, C. and Dubeau, F. and Pike, G.
                   B. and Gotman, J.},
  title = {E{EG}-f{MRI} of focal epileptic spikes: analysis with
                   multiple haemodynamic functions and comparison with
                   gadolinium-enhanced {MR} angiograms},
  journal = {Hum Brain Mapp},
  volume = {22},
  number = {3},
  pages = {179-192},
  abstract = {Combined EEG-fMRI has recently been used to explore
                   the BOLD responses to interictal epileptiform
                   discharges. This study examines whether
                   misspecification of the form of the haemodynamic
                   response function (HRF) results in significant fMRI
                   responses being missed in the statistical analysis.
                   EEG-fMRI data from 31 patients with focal epilepsy were
                   analysed with four HRFs peaking from 3 to 9 sec after
                   each interictal event, in addition to a standard HRF
                   that peaked after 5.4 sec. In four patients, fMRI
                   responses were correlated with gadolinium-enhanced MR
                   angiograms and with EEG data from intracranial
                   electrodes. In an attempt to understand the absence of
                   BOLD responses in a significant group of patients, the
                   degree of signal loss occurring as a result of magnetic
                   field inhomogeneities was compared with the detected
                   fMRI responses in ten patients with temporal lobe
                   spikes. Using multiple HRFs resulted in an increased
                   percentage of data sets with significant fMRI
                   activations, from 45\% when using the standard HRF
                   alone, to 62.5\%. The standard HRF was good at
                   detecting positive BOLD responses, but less appropriate
                   for negative BOLD responses, the majority of which were
                   more accurately modelled by an HRF that peaked later
                   than the standard. Co-registration of statistical maps
                   with gadolinium-enhanced MRIs suggested that the
                   detected fMRI responses were not in general related to
                   large veins. Signal loss in the temporal lobes seemed
                   to be an important factor in 7 of 12 patients who did
                   not show fMRI activations with any of the HRFs.},
  authoraddress = {Montreal Neurological Institute, McGill University,
                   Montreal, Quebec, Canada. bagshaw@mcgill.ca},
  language = {eng},
  medline-aid = {10.1002/hbm.20024 [doi]},
  medline-ci = {Copyright 2004 Wiley-Liss, Inc.},
  medline-da = {20040614},
  medline-edat = {2004/06/15 05:00},
  medline-fau = {Bagshaw, Andrew P ; Aghakhani, Yahya ; Benar,
                   Christian-G ; Kobayashi, Eliane ; Hawco, Colin ;
                   Dubeau, Francois ; Pike, G Bruce ; Gotman, Jean},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-mhda = {2004/06/15 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {15195285},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 2004 Jul;22(3):179-92.},
  medline-stat = {in-process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15195285},
  year = 2004
}
@ARTICLE{BAM+99,
  author = {Brooks, D. H. and Ahmad, G. F. and MacLeod, R. S. and
                   Maratos, G. M.},
  title = {Inverse electrocardiography by simultaneous imposition
                   of multiple constraints},
  journal = {IEEE Trans Biomed Eng},
  volume = {46},
  number = {1},
  pages = {3-18},
  abstract = {We describe two new methods for the inverse problem of
                   electrocardiography. Both employ regularization with
                   multiple constraints, rather than the standard
                   single-constraint regularization. In one method,
                   multiple constraints on the spatial behavior of the
                   solution are used simultaneously. In the other, spatial
                   constraints are used simultaneously with constraints on
                   the temporal behavior of the solution. The specific
                   cases of two spatial constraints and one spatial and
                   one temporal constraint are considered in detail. A new
                   method, the L-Surface, is presented to guide the choice
                   of the required pairs of regularization parameters. In
                   the case when both spatial and temporal regularization
                   are used simultaneously, there is an increased
                   computational burden, and two methods are presented to
                   compute solutions efficiently. The methods are verified
                   by simulations using both dipole sources and measured
                   canine epicardial data.},
  authoraddress = {Electrical and Computer Engineering Department,
                   Northeastern University, Boston, MA 02115, USA.
                   brooks@cdsp.neu.edu},
  keywords = {Animals ; Dogs ; Electrocardiography/*methods ;
                   Mathematics ; *Models, Cardiovascular ; *Signal
                   Processing, Computer-Assisted ; Support, U.S. Gov't,
                   Non-P.H.S.},
  language = {eng},
  medline-da = {19990311},
  medline-dcom = {19990311},
  medline-edat = {1999/01/27},
  medline-fau = {Brooks, D H ; Ahmad, G F ; MacLeod, R S ; Maratos, G M},
  medline-is = {0018-9294},
  medline-jid = {0012737},
  medline-lr = {20031114},
  medline-mhda = {1999/01/27 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9919821},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng 1999 Jan;46(1):3-18.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9919821},
  year = 1999
}
@ARTICLE{BB02,
  author = {Bodurka, J. and Bandettini, P. A.},
  title = {Toward direct mapping of neuronal activity: {MRI}
                   detection of ultraweak, transient magnetic field
                   changes},
  journal = {Magn Reson Med},
  volume = {47},
  number = {6},
  pages = {1052-1058},
  abstract = {A novel method based on selective detection of rapidly
                   changing DeltaB(0) magnetic fields and suppression of
                   slowly changing DeltaB(0) fields is presented. The
                   ultimate goal of this work is to present a method that
                   may allow detection of transient and subtle changes in
                   B(0) in cortical tissue associated with electrical
                   currents produced by neuronal activity. The method
                   involves the detection of NMR phase changes that occur
                   during a single-shot spin-echo (SE) echo-planar
                   sequence (EPI) echo time. SE EPI effectively rephases
                   all changes in B(0) that occur on a time scale longer
                   than the echo time (TE) and amplifies all DeltaB(0)
                   changes that occur during TE/2. The method was tested
                   on a phantom that contains wires in which current can
                   be modulated. The sensitivity and flexibility of the
                   technique was demonstrated by modulation of the
                   temporal position and duration of the stimuli-evoked
                   transient magnetic field relative to the 180 RF pulse
                   in the imaging sequence-requiring precise stimulus
                   timing. Currently, with this method magnetic field
                   changes as small as 2 x 10(-10) T (200 pT) and lasting
                   for 40 msec can be detected. Implications for direct
                   mapping of brain neuronal activity with MRI are
                   discussed.},
  authoraddress = {3 Tesla Functional Neuroimaging Facility, National
                   Institute of Mental Health, NIH, Bethesda, Maryland
                   20892-1148, USA. jbodurka@codon.nih.gov},
  keywords = {Brain Mapping/*instrumentation/methods ;
                   Electromagnetic Fields ; Human ; Image Processing,
                   Computer-Assisted ; Magnetic Resonance Imaging/*methods
                   ; Neurons/*physiology ; *Phantoms, Imaging},
  language = {eng},
  medline-aid = {10.1002/mrm.10159 [doi]},
  medline-ci = {Published 2002 Wiley-Liss, Inc.},
  medline-da = {20020711},
  medline-dcom = {20021007},
  medline-edat = {2002/07/12 10:00},
  medline-fau = {Bodurka, Jerzy ; Bandettini, Peter A},
  medline-is = {0740-3194},
  medline-jid = {8505245},
  medline-mhda = {2002/10/09 04:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12111950},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Magn Reson Med 2002 Jun;47(6):1052-8.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12111950},
  year = 2002
}
@ARTICLE{BBC+02,
  author = {Babiloni, F. and Babiloni, C. and Carducci, F. and Del
                   Gratta, C. and Romani, G. L. and Rossini, P. M. and
                   Cincotti, F.},
  title = {Cortical source estimate of combined high resolution
                   {EEG} and f{MRI} data related to voluntary movements},
  journal = {Methods Inf Med},
  volume = {41},
  number = {5},
  pages = {443-450},
  abstract = {OBJECTIVES: In this paper, we employed advanced
                   methods for the modeling of human cortical activity
                   related to voluntary right one-digit movements from
                   combined high-resolution electroencepholography (EEG)
                   and functional magnetic resonance imaging (fMRI).
                   METHODS: Multimodal integration between EEG and fMRI
                   data was performed by using realistic head models, a
                   large number of scalp electrodes (128) and the
                   estimation of current density strengths by linear
                   inverse estimation. RESULTS: Increasing of spatial
                   details of the estimated cortical density distributions
                   has been detected by using the proposed integration
                   method with respect to the estimation using EEG data
                   alone. CONCLUSION: The proposed method of multimodal
                   EEG-fMRI data is useful to increase spatial resolution
                   of movement-related potentials and can also be applied
                   to other kinds of event-related potentials.},
  authoraddress = {Dipartimento di Fisiologia Umana e Farmacologia,
                   Universita di Roma La Sapienza, Roma, Italy.
                   Fabio.Babiloni@uniroma1.it},
  keywords = {Brain Mapping/methods ; Cerebral Cortex/*physiology ;
                   Cortical Synchronization ; Electrodes ;
                   Electroencephalography/*methods ; Human ;
                   Magnetoencephalography/*methods ; Motor
                   Activity/*physiology ; Nerve Net ; Signal Processing,
                   Computer-Assisted ; *Systems Integration},
  language = {eng},
  medline-da = {20021227},
  medline-dcom = {20030225},
  medline-edat = {2002/12/28 04:00},
  medline-fau = {Babiloni, F ; Babiloni, C ; Carducci, F ; Del Gratta,
                   C ; Romani, G L ; Rossini, P M ; Cincotti, F},
  medline-is = {0026-1270},
  medline-jid = {0210453},
  medline-mhda = {2003/02/26 04:00},
  medline-own = {NLM},
  medline-pl = {Germany},
  medline-pmid = {12501818},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Methods Inf Med 2002;41(5):443-50.},
  medline-stat = {completed},
  year = 2002
}
@ARTICLE{BBC+03c,
  author = {Babiloni, F. and Babiloni, C. and Carducci, F. and
                   Romani, G. L. and Rossini, P. M. and Angelone, L. M.
                   and Cincotti, F.},
  title = {Multimodal integration of high-resolution {EEG} and
                   functional magnetic resonance imaging data: a
                   simulation study},
  journal = {NeuroImage},
  volume = {19},
  number = {1},
  pages = {1-15},
  abstract = {Previous simulation studies have stressed the
                   importance of the use of fMRI priors in the estimation
                   of cortical current density. However, no systematic
                   variations of signal-to-noise ratio (SNR) and number of
                   electrodes were explicitly taken into account in the
                   estimation process. In this simulation study we
                   considered the utility of including information as
                   estimated from fMRI. This was done by using as the
                   dependent variable both the correlation coefficient and
                   the relative error between the imposed and the
                   estimated waveforms at the level of cortical region of
                   interests (ROI). A realistic head and cortical surface
                   model was used. Factors used in the simulations were
                   the different values of SNR of the scalp-generated
                   data, the different inverse operators used to estimated
                   the cortical source activity, the strengths of the fMRI
                   priors in the fMRI-based inverse operators, and the
                   number of scalp electrodes used in the analysis.
                   Analysis of variance results suggested that all the
                   considered factors significantly afflict the
                   correlation and the relative error between the
                   estimated and the simulated cortical activity. For the
                   ROIs analyzed with simulated fMRI hot spots, it was
                   observed that the best estimation of cortical source
                   currents was performed with the inverse operators that
                   used fMRI information. When the ROIs analyzed do not
                   present fMRI hot spots, both standard (i.e., minimum
                   norm) and fMRI-based inverse operators returned
                   statistically equivalent correlation and relative error
                   values.},
  authoraddress = {Dipartimento di Fisiologia Umana e Farmacologia,
                   Universita di Rome La Sapienza, Italy.
                   Fabio.Babiloni@uniromal.it},
  keywords = {Analysis of Variance ; Brain Mapping ; Cerebral
                   Cortex/*physiology ; *Computer Simulation ;
                   *Electroencephalography ; Electrophysiology ; Human ;
                   *Magnetic Resonance Imaging ; *Models, Neurological},
  language = {eng},
  medline-aid = {S1053811903000521 [pii]},
  medline-da = {20030603},
  medline-dcom = {20030721},
  medline-edat = {2003/06/05 05:00},
  medline-fau = {Babiloni, F ; Babiloni, C ; Carducci, F ; Romani, G L
                   ; Rossini, P M ; Angelone, L M ; Cincotti, F},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2003/07/23 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12781723},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2003 May;19(1):1-15.},
  medline-stat = {completed},
  year = 2003
}
@ARTICLE{BBC06,
  author = {Burke, M. and {Buhrle Ch}},
  title = {B{OLD} response during uncoupling of neuronal activity
                   and {CBF}.},
  journal = {Neuroimage},
  volume = {32},
  number = {1},
  pages = {1-8},
  abstract = {The widely used technique of functional magnetic
                   resonance imaging (fMRI) based on the blood oxygenation
                   level-dependent (BOLD) effect is a tool for the
                   investigation of changes in local brain activity upon
                   stimulation. The principle of measurement is based on
                   the assumption that there is a strong coupling between
                   changes in neural activity, metabolism, vascular
                   response and oxygen extraction in the area under
                   investigation. As fMRI is on the way to become a
                   routine tool in clinical examinations, we wanted to
                   investigate whether, generally and under a variety of
                   conditions, there is a strong link between the BOLD
                   signal and neural activity. For clinical and
                   experimental application of the method, it is crucial,
                   whether the absence of changes in BOLD signal intensity
                   upon stimulation can always be interpreted as an
                   absence of changes in brain activity. We approached
                   this question by inhibiting the nitric oxide mediated
                   'neurovascular coupling' via application of 7
                   nitroindazole. Before and after inhibition of this
                   neurovascular coupling, we acquired evoked potentials
                   and performed fMRI during somatosensory stimulation in
                   rats. Cerebral blood flow response as well as BOLD
                   signal intensity changes following electrical
                   stimulation were abolished within 10 min after
                   application of 7 nitroindazole, whereas
                   somatosensory-evoked potentials were only slightly
                   affected but still clearly detectable. Even 1 h after
                   injection of 7 nitroindazole, there was still remaining
                   electrical activity. Thus, we observed an uncoupling
                   between electrical, i.e., neural activity and the BOLD
                   signal. According to our results, the absence of BOLD
                   signal changes did not permit the conclusion that there
                   was no neural activity in the area under investigation.
                   Our findings are especially relevant for the clinical
                   application of fMRI in patients suffering from
                   cerebrovascular and other brain diseases.},
  authoraddress = {Faculty of Psychology, Section for Experimental and
                   Biological Psychology, Philipps-Universitat Marburg,
                   Gutenbergstrasse 18, D-35032 Marburg, Germany.
                   burkem@staff.uni-marburg.de},
  keywords = {Animals ; Blood Gas Analysis ; Cerebrovascular
                   Circulation/*physiology ; Evoked Potentials,
                   Somatosensory/physiology ; Heart Rate ; Magnetic
                   Resonance Imaging ; Male ; Neurons/*physiology ;
                   Oxygen/*blood ; Rats ; Rats, Sprague-Dawley ;
                   Somatosensory Cortex/blood supply/physiology},
  language = {eng},
  medline-aid = {S1053-8119(06)00217-5 [pii] ;
                   10.1016/j.neuroimage.2006.03.035 [doi]},
  medline-da = {20060724},
  medline-dcom = {20060915},
  medline-dep = {20060503},
  medline-edat = {2006/05/09 09:00},
  medline-fau = {Burke, M ; Buhrle, Ch},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2006/09/16 09:00},
  medline-own = {NLM},
  medline-phst = {2005/09/01 [received] ; 2006/02/27 [revised] ;
                   2006/03/16 [accepted] ; 2006/05/03 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16677832},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 Aug 1;32(1):1-8. Epub 2006 May 3.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16677832},
  year = 2006
}
@ARTICLE{BCB+05,
  author = {Babiloni, F. and Cincotti, F. and Babiloni, C. and
                   Carducci, F. and Mattia, D. and Astolfi, L. and
                   Basilisco, A. and Rossini, P.M. and Ding, L. and Ni, Y.
                   and Cheng, J. and Christine, K. and Sweeney, J. and He,
                   B.},
  title = {Estimation of the cortical functional connectivity
                   with the multimodal integration of high-resolution
                   {EEG} and f{MRI} data by directed transfer function.},
  journal = {Neuroimage},
  volume = {24},
  number = {1},
  pages = {118-131},
  abstract = {Nowadays, several types of brain imaging device are
                   available to provide images of the functional activity
                   of the cerebral cortex based on hemodynamic, metabolic,
                   or electromagnetic measurements. However, static images
                   of brain regions activated during particular tasks do
                   not convey the information of how these regions
                   communicate with each other. In this study, advanced
                   methods for the estimation of cortical connectivity
                   from combined high-resolution electroencephalography
                   (EEG) and functional magnetic resonance imaging (fMRI)
                   data are presented. These methods include a subject's
                   multicompartment head model (scalp, skull, dura mater,
                   cortex) constructed from individual magnetic resonance
                   images, multidipole source model, and regularized
                   linear inverse source estimates of cortical current
                   density. Determination of the priors in the resolution
                   of the linear inverse problem was performed with the
                   use of information from the hemodynamic responses of
                   the cortical areas as revealed by block-designed
                   (strength of activated voxels) fMRI. We estimate
                   functional cortical connectivity by computing the
                   directed transfer function (DTF) on the estimated
                   cortical current density waveforms in regions of
                   interest (ROIs) on the modeled cortical mantle. The
                   proposed method was able to unveil the direction of the
                   information flow between the cortical regions of
                   interest, as it is directional in nature. Furthermore,
                   this method allows to detect changes in the time course
                   of information flow between cortical regions in
                   different frequency bands. The reliability of these
                   techniques was further demonstrated by elaboration of
                   high-resolution EEG and fMRI signals collected during
                   visually triggered finger movements in four healthy
                   subjects. Connectivity patterns estimated for this task
                   reveal an involvement of right parietal and bilateral
                   premotor and prefrontal cortical areas. This cortical
                   region involvement resembles that revealed in previous
                   studies where visually triggered finger movements were
                   analyzed with the use of separate EEG or fMRI
                   measurements.},
  authoraddress = {Department of Human Physiology and Pharmacology,
                   University "La Sapienza", Rome, Italy; IRCCS Fondazione
                   Santa Lucia, Rome, Italy.},
  language = {eng},
  medline-aid = {S1053-8119(04)00564-6 [pii] ;
                   10.1016/j.neuroimage.2004.09.036 [doi]},
  medline-da = {20041213},
  medline-edat = {2004/12/14 09:00},
  medline-fau = {Babiloni, F ; Cincotti, F ; Babiloni, C ; Carducci, F
                   ; Mattia, D ; Astolfi, L ; Basilisco, A ; Rossini, P M
                   ; Ding, L ; Ni, Y ; Cheng, J ; Christine, K ; Sweeney,
                   J ; He, B},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/12/14 09:00},
  medline-own = {NLM},
  medline-phst = {2004/03/02 [received] ; 2004/05/17 [revised] ;
                   2004/09/23 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15588603},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuroimage 2005 Jan 1;24(1):118-31.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15588603},
  year = 2005
}
@ARTICLE{BDM+05,
  author = {Brazdil, M. and Dobsik, M. and Mikl, M. and Hlustik,
                   P. and Daniel, P. and Pazourkova, M. and Krupa, P. and
                   Rektor, I.},
  title = {Combined event-related f{MRI} and intracerebral {ERP}
                   study of an auditory oddball task.},
  journal = {Neuroimage},
  volume = {26},
  number = {1},
  pages = {285-93},
  abstract = {Event-related fMRI (efMRI) has been repeatedly used to
                   seek the neural sources of endogenous event-related
                   potentials (ERP). However, significant discrepancies
                   exist between the efMRI data and the results of
                   previously published intracranial ERP studies of
                   oddball task. To evaluate the capacity of efMRI to
                   define the sources of the P3 component of ERP within
                   the human brain, both efMRI and intracerebral ERP
                   recordings were performed in eight patients with
                   intractable epilepsy (five males and three females)
                   during their preoperative invasive video-EEG
                   monitoring. An identical auditory oddball task with
                   frequent and target stimuli was completed in two
                   sessions. A total of 606 intracerebral sites were
                   electrophysiologically investigated by means of depth
                   electrodes. In accordance with the finding of multiple
                   intracerebral generators of P3 potential, the target
                   stimuli evoked MRI signal increase in multiple brain
                   regions. However, regions with evident hemodynamic and
                   electrophysiological responses overlapped only
                   partially. P3 generators were always found within
                   hemodynamic-active sites, if these sites were
                   investigated by means of depth electrodes. On the other
                   hand, unequivocal local sources of P3 potential were
                   apparently also located outside the regions with a
                   significant hemodynamic response (typically in
                   mesiotemporal regions). Both methods should thus be
                   viewed as mutually complementary in investigations of
                   the spatial distribution of cortical and subcortical
                   activation during oddball task.},
  authoraddress = {First Department of Neurology, St. Anne's University
                   Hospital, Brno, Czech Republic. mbrazd@med.muni.cz},
  keywords = {Adult ; Auditory Cortex/physiology ; Auditory
                   Perception/*physiology ; Brain/*physiology ;
                   Cerebrovascular Circulation/physiology ; Electrodes,
                   Implanted ; Electroencephalography ; Electrophysiology
                   ; Epilepsy/physiopathology ; Evoked Potentials,
                   Auditory/physiology ; Female ; Humans ; Magnetic
                   Resonance Imaging ; Male ; Oxygen/blood ; Research
                   Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1053-8119(05)00053-4 [pii] ;
                   10.1016/j.neuroimage.2005.01.051 [doi]},
  medline-da = {20050502},
  medline-dcom = {20050712},
  medline-edat = {2005/05/03 09:00},
  medline-fau = {Brazdil, Milan ; Dobsik, Martin ; Mikl, Michal ;
                   Hlustik, Petr ; Daniel, Pavel ; Pazourkova, Marta ;
                   Krupa, Petr ; Rektor, Ivan},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2005/07/13 09:00},
  medline-own = {NLM},
  medline-phst = {2004/11/19 [received] ; 2005/01/04 [revised] ;
                   2005/01/14 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15862229},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage 2005 May 15;26(1):285-93.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15862229},
  year = 2005,
  yoh-notes = {XXXREADXXX}
}
@ARTICLE{BEG+96,
  author = {Boynton, G. M. and Engel, S. A. and Glover, G. H. and
                   Heeger, D. J.},
  title = {Linear systems analysis of functional magnetic
                   resonance imaging in human {V}1},
  journal = {J Neurosci},
  volume = {16},
  number = {13},
  pages = {4207-4221},
  abstract = {The linear transform model of functional magnetic
                   resonance imaging (fMRI) hypothesizes that fMRI
                   responses are proportional to local average neural
                   activity averaged over a period of time. This work
                   reports results from three empirical tests that support
                   this hypothesis. First, fMRI responses in human primary
                   visual cortex (V1) depend separably on stimulus timing
                   and stimulus contrast. Second, responses to
                   long-duration stimuli can be predicted from responses
                   to shorter duration stimuli. Third, the noise in the
                   fMRI data is independent of stimulus contrast and
                   temporal period. Although these tests can not prove the
                   correctness of the linear transform model, they might
                   have been used to reject the model. Because the linear
                   transform model is consistent with our data, we
                   proceeded to estimate the temporal fMRI
                   impulse-response function and the underlying
                   (presumably neural) contrast-response function of human
                   V1.},
  authoraddress = {Department of Psychology, Stanford University,
                   California 94305, USA.},
  keywords = {Artifacts ; Human ; *Magnetic Resonance Imaging ;
                   Models, Neurological ; Noise ; Photic Stimulation ;
                   Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S. ;
                   Time Factors ; Visual Cortex/*physiology},
  language = {eng},
  medline-da = {19961213},
  medline-dcom = {19961213},
  medline-edat = {1996/07/01},
  medline-fau = {Boynton, G M ; Engel, S A ; Glover, G H ; Heeger, D J},
  medline-gr = {IEQA455/PHS ; MH50228/MH/NIMH ; P41 RR09784/RR/NCRR},
  medline-is = {0270-6474},
  medline-jid = {8102140},
  medline-lr = {20001218},
  medline-mhda = {1996/07/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {8753882},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {J Neurosci 1996 Jul 1;16(13):4207-21.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=8753882},
  year = 1996
}
@ARTICLE{BESL-MCKAY92A,
  author = {Besl, P. J. and McKay, N. D.},
  title = {A Method for Registration of {3-D} Shapes},
  journal = {IEEE Trans. Pattern Anal. Machine Intell.},
  year = 1992,
  volume = 14,
  number = 2,
  keywords = {ICP},
  month = FEB
}
@ARTICLE{BET+97,
  author = {Beisteiner, R. and Erdler, M. and Teichtmeister, C.
                   and Diemling, M. and Moser, E. and Edward, V. and
                   Deecke, L.},
  title = {Magnetoencephalography may help to improve functional
                   {MRI} brain mapping},
  journal = {Eur J Neurosci},
  volume = {9},
  number = {5},
  pages = {1072-1077},
  abstract = {The validity of functional magnetic resonance imaging
                   (FMRI) brain maps with respect to the sites of neuronal
                   activation is still unknown. One source of localization
                   error may be pixels with large signal amplitudes, since
                   such pixels may be expected to overlie large vessels,
                   running remote from the centre of neuronal activation.
                   In this study, magnetoencephalography was used to
                   determine the centre of neuronal activation in a simple
                   finger tapping task. The localization accuracy of
                   conventional FMRI depending on FMRI signal enhancement
                   was investigated relative to the magnetoencephalography
                   reference. The results show a deterioration of FMRI
                   localization with increasing signal amplitude related
                   to increased contributions from large vessels. We
                   conclude that FMRI data analysis should exclude large
                   signal amplitudes and that magnetoencephalography may
                   help to improve FMRI brain mapping results in a
                   multimethod approach.},
  authoraddress = {Department of Neurology, University of Vienna,
                   Austria.},
  keywords = {Adult ; Brain/*physiology ; *Brain Mapping ; Human ;
                   Magnetic Resonance Imaging/*methods ;
                   *Magnetoencephalography ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-da = {19970721},
  medline-dcom = {19970721},
  medline-edat = {1997/05/01},
  medline-fau = {Beisteiner, R ; Erdler, M ; Teichtmeister, C ;
                   Diemling, M ; Moser, E ; Edward, V ; Deecke, L},
  medline-is = {0953-816X},
  medline-jid = {8918110},
  medline-lr = {20001218},
  medline-mhda = {1997/05/01 00:01},
  medline-own = {NLM},
  medline-pl = {ENGLAND},
  medline-pmid = {9182959},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Eur J Neurosci 1997 May;9(5):1072-7.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9182959},
  year = 1997
}
@ARTICLE{BF97,
  author = {Buxton, R. B. and Frank, L. R.},
  title = {A model for the coupling between cerebral blood flow
                   and oxygen metabolism during neural stimulation},
  journal = {J Cereb Blood Flow Metab},
  volume = {17},
  number = {1},
  pages = {64-72},
  abstract = {A general mathematical model for the delivery of O2 to
                   the brain is presented, based on the assumptions that
                   all of the brain capillaries are perfused at rest and
                   that all of the oxygen extracted from the capillaries
                   is metabolized. The model predicts that
                   disproportionately large changes in blood flow are
                   required in order to support small changes in the O2
                   metabolic rate. Interpreted in terms of this model,
                   previous positron emission tomography (PET) studies of
                   the human brain during neural stimulation demonstrating
                   that cerebral blood flow (CBF) increases much more than
                   the oxygen metabolic rate are consistent with tight
                   coupling of flow and oxidative metabolism. The model
                   provides a basis for the quantitative interpretation of
                   functional magnetic resonance imaging (fMRI) studies in
                   terms of changes in local CBF.},
  authoraddress = {Department of Radiology, University of California at
                   San Diego 92103-8756, USA.},
  keywords = {Brain/physiology ; *Cerebrovascular Circulation ;
                   Human ; *Models, Neurological ; *Oxygen Consumption ;
                   *Regional Blood Flow ; Tomography, Emission-Computed},
  language = {eng},
  medline-da = {19970121},
  medline-dcom = {19970121},
  medline-edat = {1997/01/01},
  medline-fau = {Buxton, R B ; Frank, L R},
  medline-is = {0271-678X},
  medline-jid = {8112566},
  medline-lr = {20001218},
  medline-mhda = {1997/01/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {8978388},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {53},
  medline-sb = {IM},
  medline-so = {J Cereb Blood Flow Metab 1997 Jan;17(1):64-72.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=8978388},
  year = 1997
}
@ARTICLE{BGH+05,
  author = {Brookes, M. J. and Gibson, A. M. and Hall, S. D. and
                   Furlong, P. L. and Barnes, G. R. and Hillebrand, A. and
                   Singh, K. D. and Holliday, I. E. and Francis, S. T. and
                   Morris, P. G.},
  title = {G{LM}-beamformer method demonstrates stationary field,
                   alpha {ERD} and gamma {ERS} co-localisation with f{MRI}
                   {BOLD} response in visual cortex.},
  journal = {Neuroimage},
  volume = {26},
  number = {1},
  pages = {302-8},
  abstract = {Recently, we introduced a new 'GLM-beamformer'
                   technique for MEG analysis that enables accurate
                   localisation of both phase-locked and non-phase-locked
                   neuromagnetic effects, and their representation as
                   statistical parametric maps (SPMs). This provides a
                   useful framework for comparison of the full range of
                   MEG responses with fMRI BOLD results. This paper
                   reports a 'proof of principle' study using a simple
                   visual paradigm (static checkerboard). The five
                   subjects each underwent both MEG and fMRI paradigms. We
                   demonstrate, for the first time, the presence of a
                   sustained (DC) field in the visual cortex, and its
                   co-localisation with the visual BOLD response. The
                   GLM-beamformer analysis method is also used to
                   investigate the main non-phase-locked oscillatory
                   effects: an event-related desynchronisation (ERD) in
                   the alpha band (8-13 Hz) and an event-related
                   synchronisation (ERS) in the gamma band (55-70 Hz). We
                   show, using SPMs and virtual electrode traces, the
                   spatio-temporal covariance of these effects with the
                   visual BOLD response. Comparisons between MEG and fMRI
                   data sets generally focus on the relationship between
                   the BOLD response and the transient evoked response.
                   Here, we show that the stationary field and changes in
                   oscillatory power are also important contributors to
                   the BOLD response, and should be included in future
                   studies on the relationship between neuronal activation
                   and the haemodynamic response.},
  authoraddress = {Sir Peter Mansfield Magnetic Resonance Centre, School
                   of Physics and Astronomy, University of Nottingham,
                   University Park, UK.},
  keywords = {Adult ; *Alpha Rhythm ; Brain Mapping ;
                   Cerebrovascular Circulation ; Cortical Synchronization
                   ; Female ; Humans ; Linear Models ; Magnetic Resonance
                   Imaging/*methods ; Magnetoencephalography ; Male ;
                   Oxygen/*blood ; Research Support, Non-U.S. Gov't ;
                   Visual Cortex/*physiology},
  language = {eng},
  medline-aid = {S1053-8119(05)00037-6 [pii] ;
                   10.1016/j.neuroimage.2005.01.050 [doi]},
  medline-da = {20050502},
  medline-dcom = {20050712},
  medline-edat = {2005/05/03 09:00},
  medline-fau = {Brookes, Matthew J ; Gibson, Andrew M ; Hall, Stephen
                   D ; Furlong, Paul L ; Barnes, Gareth R ; Hillebrand,
                   Arjan ; Singh, Krish D ; Holliday, Ian E ; Francis, Sue
                   T ; Morris, Peter G},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2005/07/13 09:00},
  medline-own = {NLM},
  medline-phst = {2004/07/23 [received] ; 2004/12/22 [revised] ;
                   2005/01/12 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15862231},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2005 May 15;26(1):302-8.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15862231},
  year = 2005
}
@ARTICLE{BKD+05,
  author = {Bagshaw, A.P. and Kobayashi, E. and Dubeau, F. and
                   Pike, G.B. and Gotman, J.},
  title = {Correspondence between {EEG}-f{MRI} and {EEG} dipole
                   localisation of interictal discharges in focal
                   epilepsy.},
  journal = {Neuroimage},
  abstract = {EEG-fMRI and EEG dipole source localisation are two
                   non-invasive imaging methods that can be applied to the
                   study of the haemodynamic and electrical consequences
                   of epileptic discharges. Using them in combination has
                   the potential to allow imaging with the spatial
                   resolution of fMRI and the temporal resolution of EEG.
                   However, although considerable data are available
                   concerning their concordance in studies involving
                   event-related potentials (ERPs), less is known about
                   how well they agree in epilepsy. To this end, 17
                   patients were selected from a database of 57 who had
                   undergone an EEG-fMRI scanning session followed by a
                   separate EEG session outside of the scanner.
                   Spatiotemporal dipole modelling was compared with the
                   peak and closest EEG-fMRI activations and
                   deactivations. On average, the dipoles were 58.5 mm
                   from the voxel with the highest positive t value and
                   32.5 mm from the nearest activated voxel. For
                   deactivations, the corresponding values were 60.8 and
                   34.0 mm. These values are considerably higher than is
                   generally observed with ERPs, probably as a result of
                   the relatively widespread field, which can lead to
                   artificially deep dipoles, and the occurrence of
                   EEG-fMRI responses remote from the presumed focus of
                   the epileptic activity. The results suggest that EEG
                   and MEG inverse solutions for equivalent current dipole
                   approaches should not be strongly constrained by
                   EEG-fMRI results in epilepsy, and that the use of
                   distributed source modelling will be a more appropriate
                   way of combining EEG-fMRI results with source
                   localisation techniques.},
  authoraddress = {Montreal Neurological Institute, McGill University,
                   Room 786, 3801 University Street, Montreal, QC, Canada
                   H3A 2B4.},
  language = {ENG},
  medline-aid = {S1053-8119(05)00732-9 [pii] ;
                   10.1016/j.neuroimage.2005.09.033 [doi]},
  medline-da = {20051104},
  medline-dep = {20051031},
  medline-edat = {2005/11/05 09:00},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2005/11/05 09:00},
  medline-own = {NLM},
  medline-phst = {2005/03/24 [received] ; 2005/09/07 [revised] ;
                   2005/09/20 [accepted]},
  medline-pmid = {16269248},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage 2005 Oct 31;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16269248},
  year = 2005
}
@ARTICLE{BKM+91,
  author = {Belliveau, J.W. and Kennedy, Jr, D.N. and McKinstry,
                   R.C. and Buchbinder, B.R. and Weisskoff, R.M. and
                   Cohen, M.S. and Vevea, J.M. and Brady, T.J. and Rosen,
                   B.R.},
  title = {Functional mapping of the human visual cortex by
                   magnetic resonance imaging.},
  journal = {Science},
  volume = {254},
  number = {5032},
  pages = {716-719},
  abstract = {Knowledge of regional cerebral hemodynamics has
                   widespread application for both physiological research
                   and clinical assessment because of the well-established
                   interrelation between physiological function, energy
                   metabolism, and localized blood supply. A magnetic
                   resonance technique was developed for quantitative
                   imaging of cerebral hemodynamics, allowing for
                   measurement of regional cerebral blood volume during
                   resting and activated cognitive states. This technique
                   was used to generate the first functional magnetic
                   resonance maps of human task activation, by using a
                   visual stimulus paradigm. During photic stimulation,
                   localized increases in blood volume (32 +/- 10 percent,
                   n = 7 subjects) were detected in the primary visual
                   cortex. Center-of-mass coordinates and linear extents
                   of brain activation within the plane of the calcarine
                   fissure are reported.},
  authoraddress = {Massachusetts General Hospital-NMR Center, Charlestown
                   02129.},
  keywords = {Blood Volume ; *Brain Mapping ; Humans ; Magnetic
                   Resonance Imaging/methods ; Magnetic Resonance
                   Spectroscopy/methods ; Regional Blood Flow ; Research
                   Support, Non-U.S. Gov't ; Research Support, U.S. Gov't,
                   P.H.S. ; Visual Cortex/anatomy & histology/blood
                   supply/*physiology},
  language = {eng},
  medline-da = {19911213},
  medline-dcom = {19911213},
  medline-edat = {1991/11/11 19:15},
  medline-fau = {Belliveau, J W ; Kennedy, D N Jr ; McKinstry, R C ;
                   Buchbinder, B R ; Weisskoff, R M ; Cohen, M S ; Vevea,
                   J M ; Brady, T J ; Rosen, B R},
  medline-gr = {P01-CA48729/CA/NCI ; R01-CA40303/CA/NCI ;
                   R01-HL39810/HL/NHLBI},
  medline-is = {0036-8075},
  medline-jid = {0404511},
  medline-lr = {20041117},
  medline-mhda = {2001/03/28 10:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {1948051},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Science 1991 Nov 1;254(5032):716-9.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=1948051},
  year = 1991
}
@ARTICLE{BL05,
  author = {Behzadi, Y. and Liu, T.T.},
  title = {An arteriolar compliance model of the cerebral blood
                   flow response to neural stimulus.},
  journal = {Neuroimage},
  volume = {25},
  number = {4},
  pages = {1100-11},
  abstract = {Although functional magnetic resonance imaging (fMRI)
                   is a widely used and powerful tool for studying brain
                   function, the quantitative interpretation of fMRI
                   measurements for basic neuroscience and clinical
                   studies can be complicated by inter-subject and
                   inter-session variability arising from modulation of
                   the baseline vascular state by disease, aging, diet,
                   and pharmacological agents. In particular, recent
                   studies have shown that the temporal dynamics of the
                   cerebral blood flow (CBF) and the blood oxygenation
                   level dependent (BOLD) responses to stimulus are
                   modulated by changes in baseline CBF induced by various
                   vasoactive agents and by decreases in vascular
                   compliance associated with aging. These effects are not
                   readily explained using current models of the CBF and
                   BOLD responses. We present here a second-order
                   nonlinear feedback model of the evoked CBF response in
                   which neural activity modulates the compliance of
                   arteriolar smooth muscle. Within this model framework,
                   the baseline vascular state affects the dynamic
                   response by changing the relative contributions of an
                   active smooth muscle component and a passive connective
                   tissue component to the overall vessel compliance.
                   Baseline dependencies of the BOLD signal are studied by
                   coupling the arteriolar compliance model with a
                   previously described balloon model of the venous
                   compartment. Numerical simulations show that the
                   proposed model describes to first order the observed
                   dependence of CBF and BOLD responses on the baseline
                   vascular state.},
  authoraddress = {Center for Functional Magnetic Resonance Imaging and
                   Department of Radiology, 9500 Gilman Drive, MC 0677, La
                   Jolla, CA 92093-0677, USA.},
  keywords = {Aging/physiology ; Algorithms ; Arterioles/anatomy &
                   histology/physiology ; Brain Chemistry/physiology ;
                   Carbon Dioxide/physiology ; Cerebrovascular
                   Circulation/*physiology ; Compliance ; Elasticity ;
                   Hemoglobins/metabolism ; Humans ; Magnetic Resonance
                   Imaging ; Models, Neurological ; Models, Statistical ;
                   Muscle Contraction/physiology ; Muscle, Smooth,
                   Vascular/anatomy & histology/*physiology ; Nonlinear
                   Dynamics ; Oxygen/blood ; Research Support, Non-U.S.
                   Gov't ; Viscosity},
  language = {eng},
  medline-aid = {S1053-8119(04)00764-5 [pii] ;
                   10.1016/j.neuroimage.2004.12.057 [doi]},
  medline-da = {20050426},
  medline-dcom = {20050711},
  medline-edat = {2005/04/27 09:00},
  medline-fau = {Behzadi, Yashar ; Liu, Thomas T},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2005/07/12 09:00},
  medline-own = {NLM},
  medline-phst = {2004/07/19 [received] ; 2004/11/09 [revised] ;
                   2004/12/07 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15850728},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {0 (Hemoglobins) ; 124-38-9 (Carbon Dioxide) ;
                   7782-44-7 (Oxygen) ; 9008-02-0 (deoxyhemoglobin)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2005 May 1;25(4):1100-11.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15850728},
  year = 2005
}
@ARTICLE{BL06,
  author = {Bregadze, N. and Lavric, A.},
  title = {E{RP} differences with vs. without concurrent f{MRI}.},
  journal = {Int J Psychophysiol},
  abstract = {The acquisition of ERPs concurrently with fMRI in
                   cognitive paradigms is appealing, but technically
                   challenging. Little is known about the effects of the
                   fMRI environment on the time-course and topography of
                   previously documented ERP effects. We examined the
                   replicability of ERP differences in the scanner at the
                   level of individual subjects, using two cognitive
                   paradigms and two statistical procedures. ERP P3
                   differences found outside the scanner in both paradigms
                   were also robustly detected in the ERPs acquired during
                   fMRI scanning. These P3 effects had equivalent
                   time-courses and scalp topographies inside and outside
                   the scanner. This replication at the level of
                   individual data-sets has implications for the clinical
                   applicability of ERP-fMRI and, more generally, for the
                   quality of scanner recorded ERPs.},
  authoraddress = {School of Psychology, University of Exeter, UK; MRI
                   Research Centre, University of Exeter, UK.},
  language = {ENG},
  medline-aid = {S0167-8760(06)00024-9 [pii] ;
                   10.1016/j.ijpsycho.2006.01.010 [doi]},
  medline-da = {20060228},
  medline-dep = {20060224},
  medline-edat = {2006/03/01 09:00},
  medline-is = {0167-8760 (Print)},
  medline-jid = {8406214},
  medline-mhda = {2006/03/01 09:00},
  medline-own = {NLM},
  medline-phst = {2005/05/16 [received] ; 2005/12/20 [revised] ;
                   2006/01/05 [accepted]},
  medline-pmid = {16503359},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Int J Psychophysiol. 2006 Feb 24;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16503359},
  year = 2006
}
@ARTICLE{BNK+95,
  author = {Baumann, S. B. and Noll, D. C. and Kondziolka, D. S.
                   and Schneider, W. and Nichols, T. E. and Mintun, M. A.
                   and Lewine, J. D. and Yonas, H. and Orrison, Jr, W. W.
                   and Sclabassi, R. J.},
  title = {Comparison of functional magnetic resonance imaging
                   with positron emission tomography and
                   magnetoencephalography to identify the motor cortex in
                   a patient with an arteriovenous malformation},
  journal = {J Image Guid Surg},
  volume = {1},
  number = {4},
  pages = {191-197},
  abstract = {Alterations in gyral contour made it difficult to
                   identify the motor cortex thought to be near an
                   arteriovenous malformation (AVM) in a 24-year-old man
                   considered for stereotactic radiosurgery. Functional
                   imaging in three modalities was performed
                   preoperatively to compare the reliability of
                   localization using functional magnetic resonance
                   imaging (fMRI) on a conventional scanner with positron
                   emission tomography (PET) and magnetoencephalography
                   (MEG). Similar tasks were used for each imaging
                   modality in an attempt to activate and identify the
                   sensory and motor cortex. Data from all three
                   modalities converged for the sensory task, and fMRI and
                   PET data converged for the motor task. The right
                   hemisphere motor strip was localized adjacent and
                   anterior to the AVM. These data were used in planning
                   the radiosurgery isodose configuration to the AVM in
                   order to reduce the irradiation of motor cortex
                   parenchyma. A postoperative fMRI study was also
                   performed using newer techniques to reduce head motion
                   artifact and to improve signal-to-noise ratio. The data
                   confirmed the conclusions derived from the preoperative
                   evaluations. This study demonstrates how conventional
                   MRI scanners can be used for functional studies of use
                   in surgical planning.},
  authoraddress = {Department of Neurological Surgery, University of
                   Pittsburgh Medical Center, Pennsylvania 15213, USA.
                   sbb@neuronet.pitt.edu},
  keywords = {Adult ; Comparative Study ; Human ; Intracranial
                   Arteriovenous Malformations/*pathology/radionuclide
                   imaging/surgery ; *Magnetic Resonance Imaging ;
                   *Magnetoencephalography ; Male ; Motor
                   Cortex/*pathology/radionuclide imaging ; Radiosurgery ;
                   Somatosensory Cortex/pathology/radionuclide imaging ;
                   Stereotaxic Techniques ; *Tomography, Emission-Computed},
  language = {eng},
  medline-da = {19970416},
  medline-dcom = {19970416},
  medline-edat = {1995/01/01},
  medline-fau = {Baumann, S B ; Noll, D C ; Kondziolka, D S ;
                   Schneider, W ; Nichols, T E ; Mintun, M A ; Lewine, J D
                   ; Yonas, H ; Orrison, W W Jr ; Sclabassi, R J},
  medline-is = {1078-7844},
  medline-jid = {9508564},
  medline-lr = {20031114},
  medline-mhda = {2001/03/28 10:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9079445},
  medline-pst = {ppublish},
  medline-pt = {Case Reports ; Journal Article},
  medline-sb = {IM},
  medline-so = {J Image Guid Surg 1995;1(4):191-7.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9079445},
  year = 1995
}
@ARTICLE{BNS05,
  author = {Babajani, A. and Nekooei, M. H. and Soltanian-Zadeh,
                   H.},
  title = {Integrated {MEG} and f{MRI} model: synthesis and
                   analysis.},
  journal = {Brain Topogr},
  volume = {18},
  number = {2},
  pages = {101-13},
  abstract = {An integrated model for magnetoencephalography (MEG)
                   and functional Magnetic Resonance Imaging (fMRI) is
                   proposed. In the model, the neural activity is related
                   to the Post Synaptic Potentials (PSPs) which is common
                   link between MEG and fMRI. Each PSP is modeled by the
                   direction and strength of its current flow which are
                   treated as random variables. The overall neural
                   activity in each voxel is used for equivalent current
                   dipole in MEG and as input of extended Balloon model in
                   fMRI. The proposed model shows the possibility of
                   detecting activation by fMRI in a voxel while the voxel
                   is silent for MEG and vice versa. Parameters of the
                   model can illustrate situations like closed field due
                   to non-pyramidal cells, canceling effect of inhibitory
                   PSP on excitatory PSP, and effect of synchronicity. In
                   addition, the model shows that the crosstalk from
                   neural activities of the adjacent voxels in fMRI may
                   result in the detection of activations in these voxels
                   that contain no neural activities. The proposed model
                   is instrumental in evaluating and comparing different
                   analysis methods of MEG and fMRI. It is also useful in
                   characterizing the upcoming combined methods for
                   simultaneous analysis of MEG and fMRI.},
  authoraddress = {Control and Intelligent Processing Center of
                   Excellence, Electrical and Computer Engineering
                   Department, University of Tehran, Tehran, Iran.},
  keywords = {Algorithms ; Excitatory Postsynaptic
                   Potentials/physiology ; Humans ; Image Processing,
                   Computer-Assisted/*statistics & numerical data ; Linear
                   Models ; Magnetic Resonance Imaging/*statistics &
                   numerical data ; Magnetoencephalography/*statistics &
                   numerical data ; Models, Statistical ; Oxygen/blood},
  language = {eng},
  medline-aid = {10.1007/s10548-005-0279-5 [doi]},
  medline-da = {20051212},
  medline-dcom = {20060208},
  medline-dep = {20051205},
  medline-edat = {2005/12/13 09:00},
  medline-fau = {Babajani, Abbas ; Nekooei, Mohammad-Hossein ;
                   Soltanian-Zadeh, Hamid},
  medline-is = {0896-0267 (Print)},
  medline-jid = {8903034},
  medline-jt = {Brain topography},
  medline-lr = {20061115},
  medline-mhda = {2006/02/09 09:00},
  medline-own = {NLM},
  medline-phst = {2005/10/08 [accepted] ; 2005/12/05 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16341578},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Research Support, Non-U.S. Gov't},
  medline-pubm = {Print-Electronic},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Brain Topogr. 2005 Winter;18(2):101-13. Epub 2005 Dec
                   5.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16341578},
  year = 2005
}
@ARTICLE{BPJ+02,
  author = {Bonmassar, G. and Purdon, P. L. and Jaaskelainen, I.
                   P. and Chiappa, K. and Solo, V. and Brown, E. N. and
                   Belliveau, J. W.},
  title = {Motion and ballistocardiogram artifact removal for
                   interleaved recording of {EEG} and {EP}s during {MRI}},
  journal = {NeuroImage},
  volume = {16},
  number = {4},
  pages = {1127-1141},
  abstract = {Artifacts generated by motion (e.g., ballistocardiac)
                   of the head inside a high magnetic field corrupt
                   recordings of EEG and EPs. This paper introduces a
                   method for motion artifact cancellation. This method is
                   based on adaptive filtering and takes advantage of
                   piezoelectric motion sensor information to estimate the
                   motion artifact noise. This filter estimates the
                   mapping between motion sensor and EEG space,
                   subtracting the motion-related noise from the raw EEG
                   signal. Due to possible subject motion and changes in
                   electrode impedance, a time-varying mapping of the
                   motion versus EEG is required. We show that this filter
                   is capable of removing both ballistocardiogram and
                   gross motion artifacts, restoring EEG alpha waves (8-13
                   Hz), and visual evoked potentials (VEPs). This adaptive
                   filter outperforms the simple band-pass filter for
                   alpha detection because it is also capable of reducing
                   noise within the frequency band of interest. In
                   addition, this filter also removes the transient
                   responses normally visible in the EEG window after echo
                   planar image acquisition, observed during interleaved
                   EEG/fMRI recordings. Our adaptive filter approach can
                   be implemented in real-time to allow for continuous
                   monitoring of EEG and fMRI during clinical and
                   cognitive studies.},
  authoraddress = {NMR Center, Massachusetts General Hospital, Harvard
                   Medical School, Charlestown, Massachusetts 02129, USA.
                   giorgio@nmr.mgh.harvard.edu},
  keywords = {Adult ; Alpha Rhythm ; *Artifacts ;
                   Ballistocardiography ; Brain/*physiology ;
                   *Electroencephalography ; *Evoked Potentials, Visual ;
                   Female ; Human ; *Magnetic Resonance Imaging ; Male ;
                   Motion ; Support, Non-U.S. Gov't ; Support, U.S. Gov't,
                   P.H.S.},
  language = {eng},
  medline-aid = {S1053811902911250 [pii]},
  medline-da = {20020830},
  medline-dcom = {20021009},
  medline-edat = {2002/08/31 10:00},
  medline-fau = {Bonmassar, Giorgio ; Purdon, Patrick L ; Jaaskelainen,
                   Iiro P ; Chiappa, Keith ; Solo, Victor ; Brown, Emery N
                   ; Belliveau, John W},
  medline-gr = {NIH R01 NS37462/NS/NINDS ; P41 RR14075/RR/NCRR},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20021120},
  medline-mhda = {2002/10/10 04:00},
  medline-ot = {Non-programmatic},
  medline-oto = {NASA},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12202099},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM ; S},
  medline-so = {NeuroImage 2002 Aug;16(4):1127-41.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12202099},
  year = 2002
}
@ARTICLE{BRL+07,
  author = {Behzadi, Y. and Restom, K. and Liau, J. and Liu, T. T.},
  title = {A component based noise correction method
                   ({C}omp{C}or) for {BOLD} and perfusion based f{MRI}.},
  journal = {Neuroimage},
  abstract = {A component based method (CompCor) for the reduction
                   of noise in both blood oxygenation level-dependent
                   (BOLD) and perfusion-based functional magnetic
                   resonance imaging (fMRI) data is presented. In the
                   proposed method, significant principal components are
                   derived from noise regions-of-interest (ROI) in which
                   the time series data are unlikely to be modulated by
                   neural activity. These components are then included as
                   nuisance parameters within general linear models for
                   BOLD and perfusion-based fMRI time series data. Two
                   approaches for the determination of the noise ROI are
                   considered. The first method uses high-resolution
                   anatomical data to define a region of interest composed
                   primarily of white matter and cerebrospinal fluid,
                   while the second method defines a region based upon the
                   temporal standard deviation of the time series data.
                   With the application of CompCor, the temporal standard
                   deviation of resting-state perfusion and BOLD data in
                   gray matter regions was significantly reduced as
                   compared to either no correction or the application of
                   a previously described retrospective image based
                   correction scheme (RETROICOR). For both functional
                   perfusion and BOLD data, the application of CompCor
                   significantly increased the number of activated voxels
                   as compared to no correction. In addition, for
                   functional BOLD data, there were significantly more
                   activated voxels detected with CompCor as compared to
                   RETROICOR. In comparison to RETROICOR, CompCor has the
                   advantage of not requiring external monitoring of
                   physiological fluctuations.},
  authoraddress = {UCSD Center for Functional Magnetic Resonance Imaging
                   and Department of Radiology, 9500 Gilman Drive, MC
                   0677, La Jolla, CA 92093-0677, USA; Department of
                   Bioengineering, University of California San Diego, La
                   Jolla, CA, USA.},
  language = {ENG},
  medline-aid = {S1053-8119(07)00383-7 [pii] ;
                   10.1016/j.neuroimage.2007.04.042 [doi]},
  medline-da = {20070611},
  medline-dep = {20070503},
  medline-edat = {2007/06/15 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2007/06/15 09:00},
  medline-own = {NLM},
  medline-phst = {2006/12/18 [received] ; 2007/04/23 [revised] ;
                   2007/04/25 [accepted]},
  medline-pmid = {17560126},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2007 May 3;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17560126},
  year = 2007
}
@ARTICLE{BRM+01,
  author = {Baillet, S. and Riera, J.J. and Marin, G. and Mangin,
                   J.F. and Aubert, J. and Garnero, L.},
  title = {Evaluation of inverse methods and head models for
                   {EEG} source localization using a human skull phantom.},
  journal = {Phys Med Biol},
  volume = {46},
  number = {1},
  pages = {77-96},
  abstract = {We used a real-skull phantom head to investigate the
                   performances of representative methods for EEG source
                   localization when considering various head models. We
                   describe several experiments using a montage with
                   current sources located at multiple positions and
                   orientations inside a human skull filled with a
                   conductive medium. The robustness of selected methods
                   based on distributed source models is evaluated as
                   various solutions to the forward problem (from the
                   sphere to the finite element method) are considered.
                   Experimental results indicate that inverse methods
                   using appropriate cortex-based source models are almost
                   always able to locate the active source with excellent
                   precision, with little or no spurious activity in close
                   or distant regions, even when two sources are
                   simultaneously active. Superior regularization schemes
                   for solving the inverse problem can dramatically help
                   the estimation of sparse and focal active zones,
                   despite significant approximation of the head geometry
                   and the conductivity properties of the head tissues.
                   Realistic head models are necessary, though, to fit the
                   data with a reasonable level of residual variance.},
  authoraddress = {Cognitive Neuroscience and Brain Imaging Laboratory,
                   CNRS UPR640-LENA, H pital de la Salpetriere, Paris,
                   France. sylvain.baillet@chups.jussieu.fr},
  keywords = {Electroencephalography/*methods ; Head/*radiation
                   effects ; Human ; Models, Theoretical ; Phantoms,
                   Imaging ; Reproducibility of Results ; Skull/*radiation
                   effects ; Time Factors},
  language = {eng},
  medline-da = {20010124},
  medline-dcom = {20010329},
  medline-edat = {2001/02/24 12:00},
  medline-fau = {Baillet, S ; Riera, J J ; Marin, G ; Mangin, J F ;
                   Aubert, J ; Garnero, L},
  medline-is = {0031-9155},
  medline-jid = {0401220},
  medline-lr = {20030416},
  medline-mhda = {2001/04/03 10:01},
  medline-own = {NLM},
  medline-pl = {England},
  medline-pmid = {11197680},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Phys Med Biol 2001 Jan;46(1):77-96.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11197680},
  year = 2001
}
@ARTICLE{BS06,
  author = {Babajani, A. and Soltanian-Zadeh, H.},
  title = {Integrated {MEG}/{EEG} and f{MRI} model based on
                   neural masses.},
  journal = {IEEE Trans Biomed Eng},
  volume = {53},
  number = {9},
  pages = {1794-801},
  abstract = {We introduce a bottom-up model for integrating
                   electroencephalography (EEG) or magnetoencephalography
                   (MEG) with functional magnetic resonance imaging
                   (fMRI). An extended neural mass model is proposed based
                   on the physiological principles of cortical minicolumns
                   and their connections. The fMRI signal is extracted
                   from the proposed neural mass model by introducing a
                   relationship between the stimulus and the neural
                   activity and using the resultant neural activity as
                   input of the extended Balloon model. The proposed
                   model, validated using simulations, is instrumental in
                   evaluating the upcoming combined methods for
                   simultaneous analysis of MEG/EEG and fMRI.},
  authoraddress = {Control and Intelligent Processing Center of
                   Excellence, Electrical and Computer Engineering
                   Department, University of Tehran, Iran.
                   a.babajani@ece.ut.ac.ir},
  keywords = {Algorithms ; Brain/*physiology ; Brain
                   Mapping/*methods ; Computer Simulation ; Diagnosis,
                   Computer-Assisted/*methods ;
                   Electroencephalography/*methods ; Evoked
                   Potentials/physiology ; Humans ; Magnetic Resonance
                   Imaging/*methods ; Magnetoencephalography/*methods ;
                   *Models, Neurological ; Nerve Net/physiology ; Systems
                   Integration},
  language = {eng},
  medline-da = {20060831},
  medline-dcom = {20061005},
  medline-edat = {2006/09/01 09:00},
  medline-fau = {Babajani, Abbas ; Soltanian-Zadeh, Hamid},
  medline-is = {0018-9294 (Print)},
  medline-jid = {0012737},
  medline-jt = {IEEE transactions on bio-medical engineering},
  medline-lr = {20061115},
  medline-mhda = {2006/10/06 09:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {16941835},
  medline-pst = {ppublish},
  medline-pt = {Evaluation Studies ; Journal Article ; Research
                   Support, Non-U.S. Gov't},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng. 2006 Sep;53(9):1794-801.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16941835},
  year = 2006
}
@ARTICLE{BSL+01,
  author = {Bonmassar, G. and Schwartz, D. P. and Liu, A. K. and
                   Kwong, K. K. and Dale, A. M. and Belliveau, J. W.},
  title = {Spatiotemporal brain imaging of visual-evoked activity
                   using interleaved {EEG} and f{MRI} recordings},
  journal = {NeuroImage},
  volume = {13},
  number = {6.1},
  pages = {1035-1043},
  abstract = {Combined analysis of electroencephalography (EEG) and
                   functional magnetic resonance imaging (fMRI) has the
                   potential to provide higher spatiotemporal resolution
                   than either method alone. In some situations, in which
                   the activity of interest cannot be reliably reproduced
                   (e.g., epilepsy, learning, sleep states), accurate
                   combined analysis requires simultaneous acquisition of
                   EEG and fMRI. Simultaneous measurements ensure that the
                   EEG and fMRI recordings reflect the exact same brain
                   activity state. We took advantage of the spatial
                   filtering properties of the bipolar montage to allow
                   recording of very short (125--250 ms) visual-evoked
                   potentials (VEPs) during fMRI. These EEG and fMRI
                   measurements are of sufficient quality to allow source
                   localization of the cortical generators. In addition,
                   our source localization approach provides a combined
                   EEG/fMRI analysis that does not require any manual
                   selection of fMRI activations or placement of source
                   dipoles. The source of the VEP was found to be located
                   in the occipital cortex. Separate analysis of EEG and
                   fMRI data demonstrated good spatial overlap of the
                   observed activated sites. As expected, the combined
                   EEG/fMRI analysis provided better spatiotemporal
                   resolution than either approach alone. The resulting
                   spatiotemporal movie allows for the
                   millisecond-to-millisecond display of changes in
                   cortical activity caused by visual stimulation. These
                   data reveal two peaks in activity corresponding to the
                   N75 and the P100 components. This type of simultaneous
                   acquisition and analysis allows for the accurate
                   characterization of the location and timing of
                   neurophysiological activity in the human brain.},
  authoraddress = {NMR Center, Massachusetts General Hospital,
                   Charlestown, Massachusetts 02129, USA.
                   giorgio@nmr.mgh.harvard.edu},
  keywords = {Adult ; *Brain Mapping ; Computer Graphics ; Data
                   Display ; Dominance, Cerebral/physiology ;
                   *Electroencephalography ; Evoked Potentials,
                   Visual/*physiology ; Female ; Human ; *Image
                   Enhancement ; *Image Processing, Computer-Assisted ;
                   Imaging, Three-Dimensional ; *Magnetic Resonance
                   Imaging ; Male ; Occipital Lobe/*physiology ; Photic
                   Stimulation ; Support, Non-U.S. Gov't ; Support, U.S.
                   Gov't, P.H.S.},
  language = {eng},
  medline-aid = {10.1006/nimg.2001.0754 [doi] ; S1053811901907542 [pii]},
  medline-ci = {Copyright 2001 Academic Press.},
  medline-da = {20010515},
  medline-dcom = {20010726},
  medline-edat = {2001/05/16 10:00},
  medline-fau = {Bonmassar, G ; Schwartz, D P ; Liu, A K ; Kwong, K K ;
                   Dale, A M ; Belliveau, J W},
  medline-gr = {P41 RR14075/RR/NCRR ; RO1 NS37462/NS/NINDS},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20011119},
  medline-mhda = {2001/07/28 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11352609},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2001 Jun;13(6 Pt 1):1035-43.},
  medline-stat = {completed},
  year = 2001
}
@ARTICLE{BW97,
  author = {Bandettini, P. A. and Wong, E. C.},
  title = {A hypercapnia-based normalization method for improved
                   spatial localization of human brain activation with
                   f{MRI}.},
  journal = {NMR Biomed},
  volume = {10},
  number = {4-5},
  pages = {197-203},
  abstract = {An issue in blood oxygenation level dependent
                   contrast-based functional MRI is the accurate
                   interpretation of the activation-induced signal
                   changes. Hemodynamic factors other than
                   activation-induced changes in blood oxygenation are
                   known to contribute to the signal change magnitudes and
                   dynamics, and therefore need to be accounted for or
                   removed. In this paper, a general method for removal of
                   effects other than activation-induced blood oxygenation
                   changes from fMRI brain activation maps by the use of
                   hypercapnic stress normalization is introduced. First,
                   the effects of resting blood volume distribution across
                   voxels on activation-induced BOLD-based fMRI signal
                   changes are shown to be significant. Second, the
                   effects of hypercapnia and hypoxia on resting and
                   activation-induced signal changes are demonstrated.
                   These results suggest that global hemodynamic stresses
                   may be useful for non-invasive mapping of blood volume.
                   Third, the normalization technique is demonstrated.},
  authoraddress = {Medical College of Wisconsin, Biophysics Research
                   Institute, Milwaukee 53226, USA. pab@post.its.mcw.edu},
  keywords = {Brain/*anatomy & histology/blood supply/*physiology ;
                   Brain Mapping/*methods ; Carbon Dioxide/*blood ; Humans
                   ; Image Processing, Computer-Assisted/methods ;
                   Magnetic Resonance Imaging/*methods ; Oxygen/blood},
  language = {eng},
  medline-aid = {10.1002/(SICI)1099-1492(199706/08)10:4/5<197::AID-NBM466>3.0.CO;2-S
                   [pii]},
  medline-da = {19980204},
  medline-dcom = {19980204},
  medline-edat = {1997/06/01 00:00},
  medline-fau = {Bandettini, P A ; Wong, E C},
  medline-is = {0952-3480 (Print)},
  medline-jid = {8915233},
  medline-jt = {NMR in biomedicine.},
  medline-lr = {20041117},
  medline-mhda = {2000/06/20 09:00},
  medline-own = {NLM},
  medline-pl = {ENGLAND},
  medline-pmid = {9430348},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {124-38-9 (Carbon Dioxide) ; 7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {NMR Biomed. 1997 Jun-Aug;10(4-5):197-203.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9430348},
  year = 1997
}
@ARTICLE{CAS+05,
  author = {Comi, E. and Annovazzi, P. and Silva, A. M. and Cursi,
                   M. and Blasi, V. and Cadioli, M. and Inuggi, A. and
                   Falini, A. and Comi, G. and Leocani, L.},
  title = {Visual evoked potentials may be recorded
                   simultaneously with f{MRI} scanning: {A} validation
                   study.},
  journal = {Hum Brain Mapp},
  volume = {24},
  number = {4},
  pages = {291-8},
  abstract = {Integrating electroencephalography (EEG) and
                   functional magnetic resonance imaging (fMRI) data may
                   help to optimize anatomical and temporal resolution in
                   the investigation of cortical function. Successful
                   removal of fMRI scanning artifacts from continuous EEG
                   in simultaneous recordings has been reported. We
                   assessed the feasibility of recording reliable visual
                   evoked potentials (VEPs) during fMRI scanning using
                   available artifact removing procedures. EEG during
                   administration of visual stimuli was recorded using
                   MRI-compatible 32-channel equipment in nine normal
                   subjects (mean age, 23.9 +/- 2.5 years), with and
                   without fMRI acquisition. fMRI scanning and
                   cardioballistographic artifacts were removed after
                   subtraction of averaged artifact waveforms. Consistency
                   between VEPs waveforms and of P1 and N1 peak latencies
                   and amplitudes in the two conditions was assessed. Good
                   correlation was found between VEP waveforms (Pearson's
                   correlation coefficient: r(P) between 0.76-0.94 across
                   subjects; P < 0.0001) and between latency or amplitude
                   of P1 and N1 peaks (latencies: r = 0.7, P < 0.035;
                   amplitudes: r > 0.65, P < 0.05; Spearman rank
                   correlation coefficient) in the two recording
                   conditions. No significant differences were found
                   between P1 and N1 parameters in the two conditions
                   (Wilcoxon signed rank test). Consistent VEP waveforms,
                   latencies, and amplitudes with and without fMRI
                   scanning indicate that reliable VEPs may be obtained
                   simultaneously with fMRI recording. This possibility
                   might be helpful by shortening recording times and
                   reducing variability from learning, habituation, and
                   fatigue phenomena from separate recordings for the
                   integration of event-related EEG and fMRI data.},
  authoraddress = {Department of Neurology and Clinical Neurophysiology,
                   University Vita-Salute, Scientific Institute Hospital
                   San Raffaele, Milan, Italy.},
  keywords = {Adult ; *Artifacts ; Brain/*physiology ; *Brain
                   Mapping ; Electroencephalography ; Evoked Potentials,
                   Visual/*physiology ; Female ; Humans ; *Magnetic
                   Resonance Imaging ; Male ; Photic Stimulation ;
                   Research Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1002/hbm.20087 [doi]},
  medline-ci = {(c) 2005 Wiley-Liss, Inc.},
  medline-da = {20050307},
  medline-dcom = {20050512},
  medline-edat = {2005/01/29 09:00},
  medline-fau = {Comi, Eleonora ; Annovazzi, Pietro ; Silva, Ana
                   Martins ; Cursi, Marco ; Blasi, Valeria ; Cadioli,
                   Marcello ; Inuggi, Alberto ; Falini, Andrea ; Comi,
                   Giancarlo ; Leocani, Letizia},
  medline-is = {1065-9471 (Print)},
  medline-jid = {9419065},
  medline-jt = {Human brain mapping.},
  medline-mhda = {2005/05/13 09:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {15678479},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Validation Studies},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp. 2005 Apr;24(4):291-8.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15678479},
  year = 2005
}
@ARTICLE{CCH+06,
  author = {Choi, J. K. and Chen, Y. I. and Hamel, E. and Jenkins,
                   B. G.},
  title = {Brain hemodynamic changes mediated by dopamine
                   receptors: {R}ole of the cerebral microvasculature in
                   dopamine-mediated neurovascular coupling.},
  journal = {Neuroimage},
  abstract = {The coupling between neurotransmitter-induced changes
                   in neuronal activity and the resultant hemodynamic
                   response is central to the interpretation of
                   neuroimaging techniques. In the present study, MRI
                   experiments showed that dopamine transporter blockers
                   such as cocaine and dopamine releasers such as
                   amphetamine and D1 receptor agonists induced large
                   positive increases in relative cerebral blood volume
                   (rCBV) that were not sensitive to nitric oxide synthase
                   inhibition. However, D1/D5 receptor antagonism with
                   SCH-23390 prevented or blocked the hemodynamic response
                   without any concomitant effect on dopamine release.
                   Dopamine D2/D3 receptor agonists, in contrast, induced
                   negative changes in rCBV in brain regions corresponding
                   largely to those endowed with these receptors. D1 and
                   D5 receptor mRNAs were expressed in microvessels of
                   responsive brain areas, while D2 and D3 receptors were
                   not consistently associated with the microvascular bed.
                   D3 receptors had an astroglial localization. Together,
                   these experiments show that direct effects of dopamine
                   upon the vasculature cannot be ignored in measuring the
                   hemodynamic coupling associated with dopaminergic
                   drugs. These results further suggest that this coupling
                   is partially mediated through D1/D5 receptors on the
                   microvasculature leading to increased rCBV and through
                   astroglial D3 receptors leading to decreased rCBV.
                   These data provide additional support for the role of
                   local post-synaptic events in neurovascular coupling
                   and emphasize that the interpretation of fMRI signals
                   exclusively in terms of neuronal activity may be
                   incomplete.},
  authoraddress = {MGH-NMR Center and Athinoula A. Martinos Center for
                   Biomedical Imaging, Department of Radiology,
                   Massachusetts General Hospital and Harvard Medical
                   School, Building 149 13th Street Charlestown, MA 02129,
                   USA.},
  language = {ENG},
  medline-aid = {S1053-8119(05)00807-4 [pii] ;
                   10.1016/j.neuroimage.2005.10.029 [doi]},
  medline-da = {20060206},
  medline-dep = {20060202},
  medline-edat = {2006/02/07 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2006/02/07 09:00},
  medline-own = {NLM},
  medline-phst = {2005/06/30 [received] ; 2005/09/30 [revised] ;
                   2005/10/14 [accepted]},
  medline-pmid = {16459104},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2006 Feb 2;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16459104},
  year = 2006
}
@ARTICLE{CGL03,
  author = {Caesar, K. and Gold, L. and Lauritzen, M.},
  title = {Context sensitivity of activity-dependent increases in
                   cerebral blood flow.},
  journal = {Proc Natl Acad Sci U S A},
  volume = {100},
  number = {7},
  pages = {4239-44},
  abstract = {Functional neuroimaging in humans is used widely to
                   study brain function in relation to human disease and
                   cognition. The neural basis of neuroimaging signals is
                   probably synaptic activity, but the effect of context,
                   defined as the interaction between synaptic inhibition,
                   excitation, and the electroresponsive properties of the
                   targeted neurons, is not well understood. We examined
                   here the effect of interaction of synaptic excitation
                   and net inhibition on the relationship between
                   electrical activity and vascular signals in the
                   cerebellar cortex. We show that stimulation of the net
                   inhibitory parallel fibers simultaneously with
                   stimulation of the excitatory climbing fibers leads to
                   a further rise in total local field potentials (LFP)
                   and cerebral blood flow (CBF) amplitudes, not a
                   decrease, as predicted from theoretical studies.
                   However, the combined stimulation of the parallel and
                   climbing fiber systems produced changes in CBF and LFP
                   that were smaller than their algebraic sum evoked by
                   separate stimulation of either system. This finding was
                   independent of the starting condition, i.e., whether
                   inhibition was superimposed on a state of excitation or
                   vice versa. The attenuation of the increases in LFP and
                   CBF amplitudes was similar, suggesting that synaptic
                   activity and CBF were coupled under these conditions.
                   The result might be explained by a relative neuronal
                   refractoriness that relates to the intrinsic membrane
                   properties of Purkinje cells, which determine the
                   recovery time of these cells. Our work implies that
                   neuronal and vascular signals are context-sensitive and
                   that their amplitudes are modulated by the
                   electroresponsive properties of the targeted neurons.},
  authoraddress = {Department of Medical Physiology, The Panum Institute,
                   University of Copenhagen, Blegdamsvej 3, 2000
                   Copenhagen N, Denmark.},
  keywords = {Animals ; Blood Flow Velocity/*physiology ;
                   Brain/blood supply/*physiology ; Cerebrovascular
                   Circulation/*physiology ; Electric Stimulation ; Humans
                   ; Laser-Doppler Flowmetry ; Male ; Membrane
                   Potentials/physiology ; Microelectrodes ; Olivary
                   Nucleus/blood supply/physiology ; Purkinje
                   Cells/physiology ; Rats ; Rats, Wistar ; Research
                   Support, Non-U.S. Gov't ; Synapses/physiology},
  language = {eng},
  medline-aid = {10.1073/pnas.0635075100 [doi] ; 0635075100 [pii]},
  medline-cin = {Proc Natl Acad Sci U S A. 2003 Apr 1;100(7):3550-2.
                   PMID: 12657733},
  medline-da = {20030402},
  medline-dcom = {20030522},
  medline-dep = {20030324},
  medline-edat = {2003/03/26 05:00},
  medline-fau = {Caesar, Kirsten ; Gold, Lorenz ; Lauritzen, Martin},
  medline-is = {0027-8424 (Print)},
  medline-jid = {7505876},
  medline-jt = {Proceedings of the National Academy of Sciences of the
                   United States of America.},
  medline-lr = {20041117},
  medline-mhda = {2003/05/23 05:00},
  medline-own = {NLM},
  medline-phst = {2003/03/24 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {12655065},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Proc Natl Acad Sci U S A. 2003 Apr 1;100(7):4239-44.
                   Epub 2003 Mar 24.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12655065},
  year = 2003
}
@ARTICLE{CGS+01,
  author = {Cohen, M. S. and Goldman, R. I. and Stern, J. and
                   Engel, Jr., J.},
  title = {Simultaneous {EEG} and f{MRI} made easy},
  journal = {NeuroImage},
  volume = {13},
  number = {6 Supp.1},
  pages = {S6},
  month = JAN,
  url = {http://dx.doi.org/10.1016/S1053-8119(01)91349-7},
  year = 2001
}
@ARTICLE{CPM+03,
  author = {Ciuciu, P. and Poline, J. B. and Marrelec, G. and
                   Idier, J. and Pallier, C. and Benali, H.},
  title = {Unsupervised robust nonparametric estimation of the
                   hemodynamic response function for any f{MRI} experiment},
  journal = {IEEE Trans Med Imaging},
  volume = {22},
  number = {10},
  pages = {1235-1251},
  abstract = {This paper deals with the estimation of the blood
                   oxygen level-dependent response to a stimulus, as
                   measured in functional magnetic resonance imaging
                   (fMRI) data. A precise estimation is essential for a
                   better understanding of cerebral activations. The most
                   recent works have used a nonparametric framework for
                   this estimation, considering each brain region as a
                   system characterized by its impulse response, the
                   so-called hemodynamic response function (HRF). However,
                   the use of these techniques has remained limited since
                   they are not well-adapted to real fMRI data. Here, we
                   develop a threefold extension to previous works. We
                   consider asynchronous event-related paradigms, account
                   for different trial types and integrate several fMRI
                   sessions into the estimation. These generalizations are
                   simultaneously addressed through a badly conditioned
                   observation model. Bayesian formalism is used to model
                   temporal prior information of the underlying
                   physiological process of the brain hemodynamic
                   response. By this way, the HRF estimate results from a
                   tradeoff between information brought by the data and by
                   our prior knowledge. This tradeoff is modeled with
                   hyperparameters that are set to the maximum-likelihood
                   estimate using an expectation conditional maximization
                   algorithm. The proposed unsupervised approach is
                   validated on both synthetic and real fMRI data, the
                   latter originating from a speech perception experiment.},
  authoraddress = {SHFJ/CEA/INSERM U562, 91401 Orsay, France.
                   ciuciu@shfj.cea.fr},
  keywords = {*Algorithms ; Brain/*blood supply/*physiology ; Brain
                   Mapping/*methods ; Cerebrovascular
                   Circulation/physiology ; Comparative Study ; Computer
                   Simulation ; Hemodynamic Processes/physiology ; Human ;
                   Image Interpretation, Computer-Assisted/*methods ;
                   Imaging, Three-Dimensional/*methods ; Likelihood
                   Functions ; Magnetic Resonance Imaging/*methods ;
                   *Models, Cardiovascular ; Models, Statistical ;
                   Reproducibility of Results ; Sensitivity and
                   Specificity ; Speech Perception/physiology ; Support,
                   Non-U.S. Gov't},
  language = {eng},
  medline-da = {20031013},
  medline-dcom = {20040311},
  medline-edat = {2003/10/14 05:00},
  medline-fau = {Ciuciu, Philippe ; Poline, Jean-Baptiste ; Marrelec,
                   Guillaume ; Idier, Jerome ; Pallier, Christophe ;
                   Benali, Habib},
  medline-is = {0278-0062},
  medline-jid = {8310780},
  medline-mhda = {2004/03/12 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {14552578},
  medline-pst = {ppublish},
  medline-pt = {Evaluation Studies ; Journal Article ; Validation
                   Studies},
  medline-sb = {IM},
  medline-so = {IEEE Trans Med Imaging 2003 Oct;22(10):1235-51.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=14552578},
  year = 2003
}
@ARTICLE{CPS+98,
  author = {Cannestra, A.F. and Pouratian, N. and Shomer, M.H. and
                   Toga, A.W.},
  title = {Refractory periods observed by intrinsic signal and
                   fluorescent dye imaging.},
  journal = {J Neurophysiol},
  volume = {80},
  number = {3},
  pages = {1522-32},
  abstract = {All perfusion-based imaging modalities depend on the
                   relationship between neuronal and vascular activity.
                   However, the relationship between stimulus and response
                   was never fully characterized. With the use of optical
                   imaging (intrinsic signals and intravascular
                   fluorescent dyes) during repetitive stimulation
                   paradigms, we observed reduced responses with
                   temporally close stimuli. Cortical evoked potentials,
                   however, did not produce the same reduced
                   responsiveness. We therefore termed these intervals of
                   reduced responsiveness "refractory periods." During
                   these refractory periods an ability to respond was
                   retained, but at a near 60\% reduction in the initial
                   magnitude. Although increasing the initial stimulus
                   duration lengthened the observed refractory periods,
                   significantly novel or temporally spaced stimuli
                   overcame them. We observed this phenomenon in both
                   rodent and human subjects in somatosensory and auditory
                   cortices. These results have significant implications
                   for understanding the capacities, mechanisms, and
                   distributions of neurovascular coupling and thereby
                   possess relevance to all perfusion-dependent functional
                   imaging techniques.},
  authoraddress = {Department of Neurology, University of California, Los
                   Angeles School of Medicine 90095-1769, USA.},
  keywords = {Acoustic Stimulation ; Animals ; Evoked Potentials,
                   Somatosensory/physiology ; Fluorescent Dyes ; Humans ;
                   Image Processing, Computer-Assisted ; Male ; Optics ;
                   Proprioception/physiology ; Rats ; Rats, Sprague-Dawley
                   ; Refractory Period, Neurologic/*physiology ; Research
                   Support, U.S. Gov't, P.H.S. ; Somatosensory
                   Cortex/*physiology ; Temporal Lobe/physiology},
  language = {eng},
  medline-da = {19981203},
  medline-dcom = {19981203},
  medline-edat = {1998/09/24},
  medline-fau = {Cannestra, A F ; Pouratian, N ; Shomer, M H ; Toga, A
                   W},
  medline-gr = {GM-08042/GM/NIGMS ; MH-19950/MH/NIMH ;
                   MH/NS-52083/MH/NIMH},
  medline-is = {0022-3077 (Print)},
  medline-jid = {0375404},
  medline-jt = {Journal of neurophysiology.},
  medline-lr = {20041117},
  medline-mhda = {1998/09/24 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9744956},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {0 (Fluorescent Dyes)},
  medline-sb = {IM},
  medline-so = {J Neurophysiol. 1998 Sep;80(3):1522-32.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9744956},
  year = 1998
}
@ARTICLE{CRB+02,
  author = {Christmann, C. and Ruf, M. and Braus, D. F. and Flor,
                   H.},
  title = {Simultaneous electroencephalography and functional
                   magnetic resonance imaging of primary and secondary
                   somatosensory cortex in humans after electrical
                   stimulation.},
  journal = {Neurosci Lett},
  volume = {333},
  number = {1},
  pages = {69-73},
  abstract = {Simultaneous electroencephalography (EEG) and
                   functional magnetic resonance imaging (fMRI)
                   measurements were performed in six healthy subjects to
                   determine the representation of stimulation of the
                   right thumb in somatosensory cortex. In all subjects
                   EEG-based dipole locations could be determined in
                   primary (S1) and secondary (S2) somatosensory cortex.
                   The stimulus-induced blood oxygenation level dependent
                   response of the fMRI showed deviations of 23.5 mm
                   (standard deviation, SD = 6.9) for S1 and 15.7 mm (SD =
                   3.5) for S2 cortex. fMRI constrained dipole searches
                   lead to higher residual variances. The data show that
                   simultaneous EEG and fMRI measurements of somatosensory
                   activity are feasible and yield reliable and valid
                   results.},
  authoraddress = {Department of Clinical and Cognitive Neuroscience at
                   the University of Heidelberg, Central Institute of
                   Mental Health, D-68159 Mannheim, Germany.},
  keywords = {Adult ; Analysis of Variance ; Electric
                   Stimulation/methods ;
                   Electroencephalography/*methods/statistics & numerical
                   data ; Female ; Humans ; Linear Models ; Magnetic
                   Resonance Imaging/*methods/statistics & numerical data
                   ; Male ; Research Support, Non-U.S. Gov't ;
                   Somatosensory Cortex/*physiology},
  language = {eng},
  medline-aid = {S0304394002009692 [pii]},
  medline-ci = {Copyright 2002 Elsevier Science Ireland Ltd.},
  medline-da = {20021028},
  medline-dcom = {20021226},
  medline-edat = {2002/10/29 04:00},
  medline-fau = {Christmann, Christoph ; Ruf, Matthias ; Braus, Dieter
                   F ; Flor, Herta},
  medline-is = {0304-3940 (Print)},
  medline-jid = {7600130},
  medline-jt = {Neuroscience letters.},
  medline-lr = {20041117},
  medline-mhda = {2002/12/27 04:00},
  medline-own = {NLM},
  medline-pl = {Ireland},
  medline-pmid = {12401562},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neurosci Lett. 2002 Nov 15;333(1):69-73.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12401562},
  year = 2002
}
@ARTICLE{CRS+04,
  author = {Cohen, E. R. and Rostrup, E. and Sidaros, K. and Lund,
                   T. E. and Paulson, O. B. and Ugurbil, K. and Kim, S. G.},
  title = {Hypercapnic normalization of {BOLD} f{MRI}: comparison
                   across field strengths and pulse sequences.},
  journal = {Neuroimage},
  volume = {23},
  number = {2},
  pages = {613-24},
  abstract = {The blood oxygenation level-dependent (BOLD)
                   functional magnetic resonance imaging (fMRI) signal
                   response to neural stimulation is influenced by many
                   factors that are unrelated to the stimulus. These
                   factors are physiological, such as the resting venous
                   cerebral blood volume (CBV(v)) and vessel size, as well
                   as experimental, such as pulse sequence and static
                   magnetic field strength (B(0)). Thus, it is difficult
                   to compare task-induced fMRI signals across subjects,
                   field strengths, and pulse sequences. This problem can
                   be overcome by normalizing the neural activity-induced
                   BOLD fMRI response by a global hypercapnia-induced BOLD
                   signal. To demonstrate the effectiveness of the BOLD
                   normalization approach, gradient-echo BOLD fMRI at 1.5,
                   4, and 7 T and spin-echo BOLD fMRI at 4 T were
                   performed in human subjects. For neural stimulation,
                   subjects performed sequential finger movements at 2 Hz,
                   while for global stimulation, subjects breathed a 5%
                   CO(2) gas mixture. Under all conditions, voxels
                   containing primarily large veins and those containing
                   primarily active tissue (i.e., capillaries and small
                   veins) showed distinguishable behavior after
                   hypercapnic normalization. This allowed functional
                   activity to be more accurately localized and quantified
                   based on changes in venous blood oxygenation alone. The
                   normalized BOLD signal induced by the motor task was
                   consistent across different magnetic fields and pulse
                   sequences, and corresponded well with cerebral blood
                   flow measurements. Our data suggest that the
                   hypercapnic normalization approach can improve the
                   spatial specificity and interpretation of BOLD signals,
                   allowing comparison of BOLD signals across subjects,
                   field strengths, and pulse sequences. A theoretical
                   framework for this method is provided.},
  authoraddress = {Center for Magnetic Resonance Research, University of
                   Minnesota, Minneapolis, MN 15260, USA.},
  keywords = {Adult ; Algorithms ; Brain Mapping ; Cerebrovascular
                   Circulation ; Comparative Study ; Echo-Planar Imaging ;
                   Female ; Humans ; Hypercapnia/*blood ; Image
                   Interpretation, Computer-Assisted ; Magnetic Resonance
                   Imaging/*methods ; Male ; Oxygen/*blood ; Psychomotor
                   Performance/physiology ; Reference Values ; Research
                   Support, Non-U.S. Gov't ; Research Support, U.S. Gov't,
                   P.H.S.},
  language = {eng},
  medline-aid = {S1053-8119(04)00330-1 [pii] ;
                   10.1016/j.neuroimage.2004.06.021 [doi]},
  medline-da = {20041018},
  medline-dcom = {20050105},
  medline-edat = {2004/10/19 09:00},
  medline-fau = {Cohen, Eric R ; Rostrup, Egill ; Sidaros, Karam ;
                   Lund, Torben E ; Paulson, Olaf B ; Ugurbil, Kamil ;
                   Kim, Seong-Gi},
  medline-gr = {EB00201/EB/NIBIB ; EB00331/EB/NIBIB ; EB00337/EB/NIBIB
                   ; RR08079/RR/NCRR},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2005/01/06 09:00},
  medline-own = {NLM},
  medline-phst = {2004/02/14 [received] ; 2004/04/29 [revised] ;
                   2004/06/18 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15488411},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-pubm = {Print},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2004 Oct;23(2):613-24.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15488411},
  year = 2004
}
@ARTICLE{CWT01,
  author = {Cheng, K. and Waggoner, R. A. and Tanaka, K.},
  title = {Human ocular dominance columns as revealed by
                   high-field functional magnetic resonance imaging.},
  journal = {Neuron},
  volume = {32},
  number = {2},
  pages = {359-74},
  abstract = {We mapped ocular dominance columns (ODCs) in normal
                   human subjects using high-field (4 T) functional
                   magnetic resonance imaging (fMRI) with a segmented echo
                   planar imaging technique and an in-plane resolution of
                   0.47 x 0.47 mm(2). The differential responses to left
                   or right eye stimulation could be reliably resolved in
                   anatomically well-defined sections of V1. The
                   orientation and width ( approximately 1 mm) of mapped
                   ODC stripes conformed to those previously revealed in
                   postmortem brains stained with cytochrome oxidase. In
                   addition, we showed that mapped ODC patterns could be
                   largely reproduced in different experiments conducted
                   within the same experimental session or over different
                   sessions. Our results demonstrate that high-field fMRI
                   can be used for studying the functions of human brains
                   at columnar spatial resolution.},
  authoraddress = {Laboratory for Cognitive Brain Mapping, RIKEN Brain
                   Science Institute and CREST, Japan Science and
                   Technology Corporation, 2-1 Hirosawa, 351-0198, Wako,
                   Saitama, Japan. kcheng@mailman.riken.go.jp},
  keywords = {Adult ; *Brain Mapping ; Dominance,
                   Cerebral/*physiology ; Humans ; *Magnetic Resonance
                   Imaging ; Male ; *Ocular Physiology ; Photic
                   Stimulation ; Research Support, Non-U.S. Gov't ; Visual
                   Cortex/physiology},
  language = {eng},
  medline-aid = {S0896-6273(01)00477-9 [pii]},
  medline-da = {20011030},
  medline-dcom = {20011207},
  medline-edat = {2001/10/31 10:00},
  medline-fau = {Cheng, K ; Waggoner, R A ; Tanaka, K},
  medline-is = {0896-6273 (Print)},
  medline-jid = {8809320},
  medline-jt = {Neuron.},
  medline-lr = {20041117},
  medline-mhda = {2002/01/05 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11684004},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuron. 2001 Oct 25;32(2):359-74.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11684004},
  year = 2001
}
@ARTICLE{Coh97,
  author = {Cohen, M. S.},
  title = {Parametric analysis of f{MRI} data using linear
                   systems methods},
  journal = {NeuroImage},
  volume = {6},
  number = {2},
  pages = {93-103},
  abstract = {Using a model of the functional MRI (fMRI) impulse
                   response based on published data, we have demonstrated
                   that the form of the fMRI response to stimuli of freely
                   varied timing can be modeled well by convolution of the
                   impulse response with the behavioral stimulus. The
                   amplitudes of the responses as a function of
                   parametrically varied behavioral conditions are fitted
                   well using a piecewise linear approximation. Use of the
                   combined model, in conjunction with correlation
                   analysis, results in an increase in sensitivity for the
                   MRI study. This approach, based on the well-established
                   methods of linear systems analysis, also allows a
                   quantitative comparison of the response amplitudes
                   across subjects to a broad range of behavioral
                   conditions. Fit parameters, derived from the amplitude
                   data, are relatively insensitive to a variety of
                   MRI-related artifacts and yield results that are
                   compared readily across subjects.},
  authoraddress = {UCLA Division of Brain Mapping, RNRC 3256, 710
                   Westwood Plaza, Los Angeles, California 90095, USA.},
  keywords = {Adult ; Brain/anatomy & histology/*physiology ; Brain
                   Mapping ; Cerebrovascular Circulation/physiology ;
                   Human ; Linear Models ; Magnetic Resonance
                   Imaging/*statistics & numerical data ; Photic
                   Stimulation ; Psychomotor Performance/physiology},
  language = {eng},
  medline-aid = {S1053811997902780 [pii]},
  medline-ci = {Copyright 1997 Academic Press.},
  medline-da = {19971119},
  medline-dcom = {19971119},
  medline-edat = {1997/09/23},
  medline-fau = {Cohen, M S},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20001218},
  medline-mhda = {1997/09/23 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9299383},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 1997 Aug;6(2):93-103.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9299383},
  year = 1997
}
@ARTICLE{DDA+03,
  author = {Devor, A. and Dunn, A. K. and Andermann, M. L. and
                   Ulbert, I. and Boas, D. A. and Dale, A. M.},
  title = {Coupling of total hemoglobin concentration,
                   oxygenation, and neural activity in rat somatosensory
                   cortex},
  journal = {Neuron},
  volume = {39},
  number = {2},
  pages = {353-359},
  abstract = {Recent advances in brain imaging techniques, including
                   functional magnetic resonance imaging (fMRI), offer
                   great promise for noninvasive mapping of brain
                   function. However, the indirect nature of the imaging
                   signals to the underlying neural activity limits the
                   interpretation of the resulting maps. The present
                   report represents the first systematic study with
                   sufficient statistical power to quantitatively
                   characterize the relationship between changes in blood
                   oxygen content and the neural spiking and synaptic
                   activity. Using two-dimensional optical measurements of
                   hemodynamic signals, simultaneous recordings of neural
                   activity, and an event-related stimulus paradigm, we
                   demonstrate that (1) there is a strongly nonlinear
                   relationship between electrophysiological measures of
                   neuronal activity and the hemodynamic response, (2) the
                   hemodynamic response continues to grow beyond the
                   saturation of electrical activity, and (3) the initial
                   increase in deoxyhemoglobin that precedes an increase
                   in blood volume is counterbalanced by an equal initial
                   decrease in oxyhemoglobin.},
  authoraddress = {Massachusetts General Hospital NMR Center, Harvard
                   Medical School, Charlestown, MA 02129, USA.
                   adevor@nmr.mgh.harvard.edu},
  keywords = {Animals ; Brain Mapping ; Comparative Study ; Computer
                   Simulation ; Demography ; Electric Stimulation ;
                   Electrophysiology/methods ; Evoked Potentials,
                   Somatosensory/physiology ; Hemodynamic
                   Processes/physiology ; Hemoglobins/*metabolism ;
                   Magnetic Resonance Imaging/methods ;
                   Neurons/*physiology ; Nonlinear Dynamics ;
                   Oxygen/*metabolism ; Rats ; Somatosensory Cortex/blood
                   supply/cytology/*metabolism ; Spectrum Analysis/methods
                   ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.
                   ; Time Factors},
  language = {eng},
  medline-aid = {S0896627303004033 [pii]},
  medline-da = {20030722},
  medline-dcom = {20030818},
  medline-edat = {2003/07/23 05:00},
  medline-fau = {Devor, Anna ; Dunn, Andrew K ; Andermann, Mark L ;
                   Ulbert, Istvan ; Boas, David A ; Dale, Anders M},
  medline-gr = {P41 RR14075/RR/NCRR ; R01 EB00790-01A2/EB/NIBIB ; R01
                   NS044623/NS/NINDS ; R01 RR13609/RR/NCRR},
  medline-is = {0896-6273},
  medline-jid = {8809320},
  medline-lr = {20031114},
  medline-mhda = {2003/08/19 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12873390},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {0 (Hemoglobins) ; 7782-44-7 (Oxygen) ; 9008-02-0
                   (deoxyhemoglobin)},
  medline-sb = {IM},
  medline-so = {Neuron 2003 Jul 17;39(2):353-9.},
  medline-stat = {completed},
  year = 2003
}
@ARTICLE{DF03,
  author = {Dechent, P. and Frahm, J.},
  title = {Functional somatotopy of finger representations in
                   human primary motor cortex},
  journal = {Hum Brain Mapp},
  volume = {18},
  number = {4},
  pages = {272-283},
  abstract = {To assess the degree of fine-scale somatotopy within
                   the hand area of the human primary motor cortex (M1),
                   functional mapping of individual movements of all
                   fingers was performed in healthy young subjects (n = 7)
                   using MRI at 0.8 x 0.8 mm2 resolution and 4 mm section
                   thickness. The experimental design comprised both a
                   direct paradigm contrasting single digit movements vs.
                   motor rest and multiple differential paradigms
                   contrasting single digit movements vs. the movement of
                   another digit. Direct mapping resulted in largely
                   overlapping activations. A somatotopic arrangement was
                   only recognizable when considering the mean
                   center-of-mass coordinates of individual digit
                   representations averaged across subjects. In contrast,
                   differential paradigms revealed more segregated and
                   somatotopically ordered activations in single subjects.
                   The use of center-of-mass coordinates yielded
                   inter-digit distances ranging from 2.0 to 16.8 mm,
                   which reached statistical significance for pairs of
                   more distant digits. For the middle fingers, the
                   functional somatotopy obtained by differential mapping
                   was dependent on the choice of the digit used for
                   control. These results confirm previous concepts that
                   finger somatotopy in the human M1 hand area emerges as
                   a functional predominance of individual digit
                   representations sharing common areas in a distributed
                   though ordered network.},
  authoraddress = {Biomedizinische NMR Forschungs GmbH am
                   Max-Planck-Institut fur biophysikalische Chemie,
                   Gottingen, Germany. pdechen@gwdg.de},
  keywords = {Adult ; Analysis of Variance ; Brain Mapping/*methods
                   ; Female ; Fingers/*physiology ; Human ; Least-Squares
                   Analysis ; Male ; Motor Cortex/*physiology},
  language = {eng},
  medline-aid = {10.1002/hbm.10084 [doi]},
  medline-ci = {Copyright 2003 Wiley-Liss, Inc.},
  medline-da = {20030312},
  medline-dcom = {20030530},
  medline-edat = {2003/03/13 04:00},
  medline-fau = {Dechent, Peter ; Frahm, Jens},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-mhda = {2003/05/31 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12632465},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 2003 Apr;18(4):272-83.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12632465},
  year = 2003
}
@ARTICLE{DF06,
  author = {Deneux, T. and Faugeras, O.},
  title = {Using nonlinear models in f{MRI} data analysis:
                   {M}odel selection and activation detection.},
  journal = {Neuroimage},
  volume = {32},
  number = {4},
  pages = {1669-89},
  abstract = {There is an increasing interest in using
                   physiologically plausible models in fMRI analysis.
                   These models do raise new mathematical problems in
                   terms of parameter estimation and interpretation of the
                   measured data. In this paper, we show how to use
                   physiological models to map and analyze brain activity
                   from fMRI data. We describe a maximum likelihood
                   parameter estimation algorithm and a statistical test
                   that allow the following two actions: selecting the
                   most statistically significant hemodynamic model for
                   the measured data and deriving activation maps based on
                   such model. Furthermore, as parameter estimation may
                   leave much incertitude on the exact values of
                   parameters, model identifiability characterization is a
                   particular focus of our work. We applied these methods
                   to different variations of the Balloon Model (Buxton,
                   R.B., Wang, E.C., and Frank, L.R. 1998. Dynamics of
                   blood flow and oxygenation changes during brain
                   activation: the balloon model. Magn. Reson. Med. 39:
                   855-864; Buxton, R.B., Uludag, K., Dubowitz, D.J., and
                   Liu, T.T. 2004. Modelling the hemodynamic response to
                   brain activation. NeuroImage 23: 220-233; Friston, K.
                   J., Mechelli, A., Turner, R., and Price, C. J. 2000.
                   Nonlinear responses in fMRI: the balloon model,
                   volterra kernels, and other hemodynamics. NeuroImage
                   12: 466-477) in a visual perception checkerboard
                   experiment. Our model selection proved that hemodynamic
                   models better explain the BOLD response than linear
                   convolution, in particular because they are able to
                   capture some features like poststimulus undershoot or
                   nonlinear effects. On the other hand, nonlinear and
                   linear models are comparable when signals get noisier,
                   which explains that activation maps obtained in both
                   frameworks are comparable. The tools we have developed
                   prove that statistical inference methods used in the
                   framework of the General Linear Model might be
                   generalized to nonlinear models.},
  authoraddress = {ENS/INRIA Odyssee Team, Ecole Normale Superieure, 45
                   rue d'Ulm, 75 005 Paris, France.},
  language = {eng},
  medline-aid = {S1053-8119(06)00170-4 [pii] ;
                   10.1016/j.neuroimage.2006.03.006 [doi]},
  medline-da = {20060911},
  medline-dep = {20060714},
  medline-edat = {2006/07/18 09:00},
  medline-fau = {Deneux, Thomas ; Faugeras, Olivier},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2006/07/18 09:00},
  medline-own = {NLM},
  medline-phst = {2005/09/29 [received] ; 2006/02/21 [revised] ;
                   2006/03/07 [accepted] ; 2006/07/14 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16844388},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 Oct 1;32(4):1669-89. Epub 2006 Jul
                   14.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16844388},
  year = 2006
}
@ARTICLE{DFS99,
  author = {Dale, A. M. and Fischl, B. and Sereno, M. I.},
  title = {Cortical surface-based analysis. {I}. {S}egmentation
                   and surface reconstruction},
  journal = {NeuroImage},
  volume = {9},
  number = {2},
  pages = {179-194},
  abstract = {Several properties of the cerebral cortex, including
                   its columnar and laminar organization, as well as the
                   topographic organization of cortical areas, can only be
                   properly understood in the context of the intrinsic
                   two-dimensional structure of the cortical surface. In
                   order to study such cortical properties in humans, it
                   is necessary to obtain an accurate and explicit
                   representation of the cortical surface in individual
                   subjects. Here we describe a set of automated
                   procedures for obtaining accurate reconstructions of
                   the cortical surface, which have been applied to data
                   from more than 100 subjects, requiring little or no
                   manual intervention. Automated routines for unfolding
                   and flattening the cortical surface are described in a
                   companion paper. These procedures allow for the routine
                   use of cortical surface-based analysis and
                   visualization methods in functional brain imaging.},
  authoraddress = {Massachusetts General Hosp/Harvard Medical School,
                   Building 149, Charlestown, Massachusetts, 02129, USA.
                   dale@nmr.mgh.harvard.edu},
  keywords = {Brain Mapping/instrumentation ; Cerebral
                   Cortex/*anatomy & histology ; Human ; Image
                   Processing, Computer-Assisted/*instrumentation ;
                   Magnetic Resonance Imaging/*instrumentation ; Reference
                   Values ; Software},
  language = {eng},
  medline-aid = {S1053811998903950 [pii]},
  medline-ci = {Copyright 1999 Academic Press.},
  medline-da = {19990318},
  medline-dcom = {19990318},
  medline-edat = {1999/02/05},
  medline-fau = {Dale, A M ; Fischl, B ; Sereno, M I},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20001218},
  medline-mhda = {1999/02/05 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9931268},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 1999 Feb;9(2):179-94.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9931268},
  year = 1999
}
@ARTICLE{DGDP+02,
  author = {Del Gratta, C. and Della Penna, S. and Ferretti, A.
                   and Franciotti, R. and Pizzella, V. and Tartaro, A. and
                   Torquati, K. and Bonomo, L. and Romani, G. L. and
                   Rossini, P. M.},
  title = {Topographic organization of the human primary and
                   secondary somatosensory cortices: comparison of f{MRI}
                   and {MEG} findings.},
  journal = {Neuroimage},
  volume = {17},
  number = {3},
  pages = {1373-83},
  abstract = {We studied MEG and fMRI responses to electric median
                   and tibial nerve stimulation in five healthy
                   volunteers. The aim was to compare the results with
                   those of a previous study using only fMRI on the
                   primary and secondary somatosensory cortices in which
                   the somatotopic organization of SII was observed with
                   fMRI. In the present work we focus on the comparison
                   between fMRI activation and MEG equivalent current
                   dipole (ECD) localizations in the SII area. The
                   somatotopic organization of SII was confirmed by MEG,
                   with the upper limb areas located more anteriorly and
                   more inferiorly than the lower limb areas. In addition
                   a substantial consistency of the ECD locations with the
                   areas of fMRI activation was observed, with an average
                   mismatch of about 1 cm. MEG ECDs and fMRI activation
                   areas showed comparable differences in SI.},
  authoraddress = {Department of Clinical Sciences and Bio-imaging,
                   University of Chieti, Italy. cosimo@itab.unich.it},
  keywords = {Adult ; Brain Mapping/*methods ; Dominance,
                   Cerebral/physiology ; Electric Stimulation ; Evoked
                   Potentials, Somatosensory/physiology ; Female ; Humans
                   ; *Image Processing, Computer-Assisted ; *Magnetic
                   Resonance Imaging ; *Magnetoencephalography ; Male ;
                   Median Nerve/physiology ; Reference Values ; Research
                   Support, Non-U.S. Gov't ; Somatosensory
                   Cortex/*physiology ; Tibial Nerve/physiology},
  language = {eng},
  medline-aid = {S105381190291253X [pii]},
  medline-da = {20021104},
  medline-dcom = {20030213},
  medline-edat = {2002/11/05 04:00},
  medline-fau = {Del Gratta, C ; Della Penna, S ; Ferretti, A ;
                   Franciotti, R ; Pizzella, V ; Tartaro, A ; Torquati, K
                   ; Bonomo, L ; Romani, G L ; Rossini, P M},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-lr = {20041117},
  medline-mhda = {2003/02/14 04:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12414277},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2002 Nov;17(3):1373-83.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12414277},
  year = 2002
}
@ARTICLE{DH01,
  author = {Dale, A. M. and Halgren, E.},
  title = {Spatiotemporal mapping of brain activity by
                   integration of multiple imaging modalities},
  journal = {Curr Opin Neurobiol},
  volume = {11},
  number = {2},
  pages = {202-208},
  abstract = {Functional magnetic resonance imaging (fMRI) and
                   positron emission tomography measure local changes in
                   brain hemodynamics induced by cognitive or perceptual
                   tasks. These measures have a uniformly high spatial
                   resolution of millimeters or less, but poor temporal
                   resolution (about 1s). Conversely,
                   electroencephalography (EEG) and magnetoencephalography
                   (MEG) measure instantaneously the current flows induced
                   by synaptic activity, but the accurate localization of
                   these current flows based on EEG and MEG data alone
                   remains an unsolved problem. Recently, techniques have
                   been developed that, in the context of brain anatomy
                   visualized with structural MRI, use both hemodynamic
                   and electromagnetic measures to arrive at estimates of
                   brain activation with high spatial and temporal
                   resolution. These methods range from simple
                   juxtaposition to simultaneous integrated techniques.
                   Their application has already led to advances in our
                   understanding of the neural bases of perception,
                   attention, memory and language. Further advances in
                   multi-modality integration will require an improved
                   understanding of the coupling between the physiological
                   phenomena underlying the different signal modalities.},
  authoraddress = {Massachusetts General Hospital Nuclear Magnetic
                   Resonance Center, 149 13th Street, Charlestown, MA
                   02129, USA.},
  keywords = {Animals ; Brain Mapping/*methods ;
                   Electroencephalography/methods ; Human ; Magnetic
                   Resonance Imaging/methods ;
                   Magnetoencephalography/methods ; Perception/physiology
                   ; Spectroscopy, Near-Infrared/methods ; Support,
                   Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S. ; *Systems
                   Integration ; Tomography, Emission-Computed/methods},
  language = {eng},
  medline-aid = {S0959438800001975 [pii]},
  medline-da = {20010413},
  medline-dcom = {20010628},
  medline-edat = {2001/04/13 10:00},
  medline-fau = {Dale, A M ; Halgren, E},
  medline-gr = {P41-RR14075/RR/NCRR ; R01-NS18741/NS/NINDS ;
                   R01-NS39581/NS/NINDS ; R01-RR13609/RR/NCRR},
  medline-is = {0959-4388},
  medline-jid = {9111376},
  medline-lr = {20031114},
  medline-mhda = {2001/06/29 10:01},
  medline-own = {NLM},
  medline-pl = {England},
  medline-pmid = {11301240},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review Literature},
  medline-rf = {81},
  medline-sb = {IM},
  medline-so = {Curr Opin Neurobiol 2001 Apr;11(2):202-8.},
  medline-stat = {completed},
  year = 2001
}
@ARTICLE{DM04,
  author = {Delorme, A. and Makeig, S.},
  title = {E{EGLAB}: an open source toolbox for analysis of
                   single-trial {EEG} dynamics including independent
                   component analysis},
  journal = {J Neurosci Methods},
  volume = {134},
  number = {1},
  pages = {9-21},
  abstract = {We have developed a toolbox and graphic user
                   interface, EEGLAB, running under the crossplatform
                   MATLAB environment (The Mathworks, Inc.) for processing
                   collections of single-trial and/or averaged EEG data of
                   any number of channels. Available functions include EEG
                   data, channel and event information importing, data
                   visualization (scrolling, scalp map and dipole model
                   plotting, plus multi-trial ERP-image plots),
                   preprocessing (including artifact rejection, filtering,
                   epoch selection, and averaging), independent component
                   analysis (ICA) and time/frequency decompositions
                   including channel and component cross-coherence
                   supported by bootstrap statistical methods based on
                   data resampling. EEGLAB functions are organized into
                   three layers. Top-layer functions allow users to
                   interact with the data through the graphic interface
                   without needing to use MATLAB syntax. Menu options
                   allow users to tune the behavior of EEGLAB to available
                   memory. Middle-layer functions allow users to customize
                   data processing using command history and interactive
                   'pop' functions. Experienced MATLAB users can use
                   EEGLAB data structures and stand-alone signal
                   processing functions to write custom and/or batch
                   analysis scripts. Extensive function help and tutorial
                   information are included. A 'plug-in' facility allows
                   easy incorporation of new EEG modules into the main
                   menu. EEGLAB is freely available
                   (http://www.sccn.ucsd.edu/eeglab/) under the GNU public
                   license for noncommercial use and open source
                   development, together with sample data, user tutorial
                   and extensive documentation.},
  authoraddress = {Swartz Center for Computational Neuroscience,
                   Institute for Neural Computation, University of
                   California San Diego, La Jolla, CA 92093-0961, USA.
                   arno@sccn.ucsd.edu},
  keywords = {*Computer Simulation/trends ;
                   Electroencephalography/*methods ; Evoked
                   Potentials/*physiology ; *Software/trends ; Support,
                   Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {10.1016/j.jneumeth.2003.10.009 [doi] ;
                   S0165027003003479 [pii]},
  medline-da = {20040422},
  medline-dcom = {20040525},
  medline-edat = {2004/04/23 05:00},
  medline-fau = {Delorme, Arnaud ; Makeig, Scott},
  medline-is = {0165-0270},
  medline-jid = {7905558},
  medline-mhda = {2004/05/27 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Jun/17 [received] ; 2003/Sep/22 [revised] ;
                   2003/Oct/16 [accepted]},
  medline-pl = {Netherlands},
  medline-pmid = {15102499},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {J Neurosci Methods 2004 Mar 15;134(1):9-21.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15102499},
  year = 2004
}
@ARTICLE{DRB+06,
  author = {Damoiseaux, J. S. and Rombouts, S. A. and Barkhof, F.
                   and Scheltens, P. and Stam, C. J. and Smith, S. M. and
                   Beckmann, C. F.},
  title = {Consistent resting-state networks across healthy
                   subjects.},
  journal = {Proc Natl Acad Sci U S A},
  volume = {103},
  number = {37},
  pages = {13848-53},
  abstract = {Functional MRI (fMRI) can be applied to study the
                   functional connectivity of the human brain. It has been
                   suggested that fluctuations in the blood oxygenation
                   level-dependent (BOLD) signal during rest reflect the
                   neuronal baseline activity of the brain, representing
                   the state of the human brain in the absence of
                   goal-directed neuronal action and external input, and
                   that these slow fluctuations correspond to functionally
                   relevant resting-state networks. Several studies on
                   resting fMRI have been conducted, reporting an apparent
                   similarity between the identified patterns. The spatial
                   consistency of these resting patterns, however, has not
                   yet been evaluated and quantified. In this study, we
                   apply a data analysis approach called tensor
                   probabilistic independent component analysis to
                   resting-state fMRI data to find coherencies that are
                   consistent across subjects and sessions. We
                   characterize and quantify the consistency of these
                   effects by using a bootstrapping approach, and we
                   estimate the BOLD amplitude modulation as well as the
                   voxel-wise cross-subject variation. The analysis found
                   10 patterns with potential functional relevance,
                   consisting of regions known to be involved in motor
                   function, visual processing, executive functioning,
                   auditory processing, memory, and the so-called
                   default-mode network, each with BOLD signal changes up
                   to 3%. In general, areas with a high mean percentage
                   BOLD signal are consistent and show the least variation
                   around the mean. These findings show that the baseline
                   activity of the brain is consistent across subjects
                   exhibiting significant temporal dynamics, with
                   percentage BOLD signal change comparable with the
                   signal changes found in task-related experiments.},
  authoraddress = {Department of Neurology, VU University Medical Center,
                   De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands.
                   j.damoiseaux@vumc.nl},
  keywords = {Brain/*physiology ; *Brain Mapping ; Health ; Humans ;
                   Magnetic Resonance Imaging ; Research Support, Non-U.S.
                   Gov't ; Rest/*physiology},
  language = {eng},
  medline-aid = {0601417103 [pii] ; 10.1073/pnas.0601417103 [doi]},
  medline-da = {20060913},
  medline-dcom = {20061030},
  medline-dep = {20060831},
  medline-edat = {2006/09/02 09:00},
  medline-fau = {Damoiseaux, J S ; Rombouts, S A R B ; Barkhof, F ;
                   Scheltens, P ; Stam, C J ; Smith, S M ; Beckmann, C F},
  medline-is = {0027-8424 (Print)},
  medline-jid = {7505876},
  medline-jt = {Proceedings of the National Academy of Sciences of the
                   United States of America.},
  medline-mhda = {2006/10/31 09:00},
  medline-own = {NLM},
  medline-phst = {2006/08/31 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16945915},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Proc Natl Acad Sci U S A. 2006 Sep
                   12;103(37):13848-53. Epub 2006 Aug 31.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16945915},
  year = 2006
}
@ARTICLE{DSF+03,
  author = {Diehl, B. and Salek-haddadi, A. and Fish, D. R. and
                   Lemieux, L.},
  title = {Mapping of spikes, slow waves, and motor tasks in a
                   patient with malformation of cortical development using
                   simultaneous {EEG} and f{MRI}.},
  journal = {Magn Reson Imaging},
  volume = {21},
  number = {10},
  pages = {1167-73},
  abstract = {We report on the simultaneous and continuous
                   acquisition of EEG and functional MRI data in a patient
                   with a left hemiparesis and focal epilepsy secondary to
                   malformation of cortical development in the right
                   hemisphere. EEG-triggered fMRI localization was
                   previously demonstrated in this patient. In the
                   experiments reported here, 322 spikes maximum at
                   electrode C4 and 126 focal slow waves were identified
                   offline. A hierarchy of models was explored in order to
                   assess the relative contributions of each type of EEG
                   event. Modeling the BOLD response to C4 spikes alone
                   showed an area of activation within the large
                   malformation, adjacent to the area of infolding cortex.
                   However, also modeling slow-waves gave rise to a
                   broader and stronger activation, suggesting that the
                   generators overlap. Motor mapping of the right hand
                   showed activation in the left sensorimotor cortex;
                   left-hand tapping led to a more diffuse area of
                   activation, displaced superiorly into the superior
                   frontal gyrus, and a small area of activation within
                   the lesion. In conclusion, continuous EEG-fMRI is
                   useful to compare the functional mapping of
                   epileptiform activity and eloquent cortices in
                   individual patients.},
  authoraddress = {MRI Unit, Department of Clinical and Experimental
                   Epilepsy, Institute of Neurology, University College,
                   London, UK.},
  keywords = {Adult ; Brain/pathology/*physiopathology ; Cerebral
                   Cortex/*abnormalities ; *Electroencephalography ;
                   Epilepsies, Partial/*physiopathology ; Humans ;
                   *Magnetic Resonance Imaging ; Male ; Motor
                   Activity/physiology ; Paresis/physiopathology ;
                   Research Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S0730725X0300328X [pii]},
  medline-da = {20040116},
  medline-dcom = {20040514},
  medline-edat = {2004/01/17 05:00},
  medline-fau = {Diehl, Beate ; Salek-haddadi, Afraim ; Fish, David R ;
                   Lemieux, Louis},
  medline-is = {0730-725X (Print)},
  medline-jid = {8214883},
  medline-jt = {Magnetic resonance imaging.},
  medline-lr = {20041117},
  medline-mhda = {2004/05/15 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {14725924},
  medline-pst = {ppublish},
  medline-pt = {Case Reports ; Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Magn Reson Imaging. 2003 Dec;21(10):1167-73.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=14725924},
  year = 2003
}
@ARTICLE{DSR+00,
  author = {Disbrow, E.A. and Slutsky, D.A. and Roberts, T.P. and
                   Krubitzer, L.A.},
  title = {Functional {MRI} at 1.5 tesla: a comparison of the
                   blood oxygenation level-dependent signal and
                   electrophysiology.},
  journal = {Proc Natl Acad Sci U S A},
  volume = {97},
  number = {17},
  pages = {9718-23},
  abstract = {How well does the functional MRI (fMRI) signal reflect
                   underlying electrophysiology? Despite the ubiquity of
                   the technique, this question has yet to be adequately
                   answered. Therefore, we have compared cortical maps
                   generated based on the indirect blood oxygenation
                   level-dependent signal of fMRI with maps from
                   microelectrode recording techniques, which directly
                   measure neural activity. Identical somatosensory
                   stimuli were used in both sets of experiments in the
                   same anesthetized macaque monkeys. Our results
                   demonstrate that fMRI can be used to determine the
                   topographic organization of cortical fields with 55\%
                   concordance to electrophysiological maps. The variance
                   in the location of fMRI activation was greatest in the
                   plane perpendicular to local vessels. An appreciation
                   of the limitations of fMRI improves our ability to use
                   it effectively to study cortical organization.},
  authoraddress = {Center for Neuroscience, Department of Neurology, and
                   Department of Psychology, University of California,
                   Davis, CA 95616, USA.},
  keywords = {Animals ; Brain Mapping/*methods ; Cerebrovascular
                   Circulation ; Comparative Study ; Dose-Response
                   Relationship, Drug ; *Electrophysiology ;
                   Face/physiology ; Hand/physiology ; Humans ; Macaca
                   mulatta/*physiology ; Magnetic Resonance Imaging ;
                   Microelectrodes ; Oxygen/*blood ; Reproducibility of
                   Results ; Research Support, Non-U.S. Gov't ; Research
                   Support, U.S. Gov't, P.H.S. ; Somatosensory
                   Cortex/*blood supply/*physiology},
  language = {eng},
  medline-aid = {10.1073/pnas.170205497 [doi] ; 170205497 [pii]},
  medline-da = {20000919},
  medline-dcom = {20000919},
  medline-edat = {2000/08/10 11:00},
  medline-fau = {Disbrow, E A ; Slutsky, D A ; Roberts, T P ;
                   Krubitzer, L A},
  medline-gr = {RO1 NS35103-02A1/NS/NINDS},
  medline-is = {0027-8424},
  medline-jid = {7505876},
  medline-lr = {20041117},
  medline-mhda = {2000/09/23 11:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10931954},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Proc Natl Acad Sci U S A 2000 Aug 15;97(17):9718-23.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10931954},
  year = 2000,
  yoh-note = {XXXREADMEXXX}
}
@ARTICLE{DSS+07,
  author = {Debener, S. and Strobel, A. and Sorger, B. and Peters,
                   J. and Kranczioch, C. and Engel, A. K. and Goebel, R.},
  title = {Improved quality of auditory event-related potentials
                   recorded simultaneously with 3-{T} f{MRI}: {R}emoval of
                   the ballistocardiogram artefact.},
  journal = {Neuroimage},
  volume = {34},
  number = {2},
  pages = {587-97},
  abstract = {EEG signals recorded simultaneously with fMRI are
                   massively compromised by severe artefacts, among them
                   the cardiac cycle-related ballistocardiogram (BCG)
                   artefact. Different methods have been proposed to
                   remove the BCG artefact focusing on channel-wise
                   template subtraction procedures or spatial filtering
                   approaches such as independent component analysis
                   (ICA). Here we systematically compared the performance
                   of the optimal basis set (OBS), a channel-wise
                   correction approach, with ICA and a recently proposed
                   combination of both (OBS-ICA). The three different
                   procedures were applied to 60-channel EEG data from 12
                   subjects recorded during fMRI acquisition in a 3-T
                   scanner. In addition to examination of the residual BCG
                   artefact, the signal-to-noise ratio (SNR) and the
                   topography of the resulting auditory evoked potential
                   component N1 were compared. Whereas all three
                   approaches led to a significant artefact reduction, the
                   ICA procedure resulted in a significantly reduced N1
                   SNR and amplitude when compared to BCG-uncorrected
                   data, indicating a rather poor performance. In contrast
                   to ICA, OBS and OBS-ICA corrected data substantially
                   improved the SNR of the N1. The quality of the auditory
                   evoked potential N1 topography was investigated by
                   means of equivalent current dipole modelling. On a
                   descriptive level, all three correction procedures led
                   to a reduced localization error when compared to
                   BCG-uncorrected data. This improvement was significant
                   for OBS-ICA. We conclude that OBS and OBS-ICA can
                   efficiently remove BCG artefacts and substantially
                   improve the quality of EEG signals recorded inside the
                   scanner, a prerequisite for the successful integration
                   of simultaneously recorded EEG and fMRI.},
  authoraddress = {MRC Institute of Hearing Research Southampton, Royal
                   South Hants Hospital, Southampton, UK; School of
                   Medicine, University of Southampton, Southampton, UK.},
  language = {eng},
  medline-aid = {S1053-8119(06)00982-7 [pii] ;
                   10.1016/j.neuroimage.2006.09.031 [doi]},
  medline-da = {20061204},
  medline-dep = {20061116},
  medline-edat = {2006/11/23 09:00},
  medline-fau = {Debener, Stefan ; Strobel, Alexander ; Sorger, Bettina
                   ; Peters, Judith ; Kranczioch, Cornelia ; Engel,
                   Andreas K ; Goebel, Rainer},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage},
  medline-mhda = {2006/11/23 09:00},
  medline-own = {NLM},
  medline-phst = {2006/04/17 [received] ; 2006/09/15 [revised] ;
                   2006/09/22 [accepted] ; 2006/11/16 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {17112746},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2007 Jan 15;34(2):587-97. Epub 2006 Nov
                   16.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17112746},
  year = 2007
}
@ARTICLE{DUS+05,
  author = {Debener, S. and Ullsperger, M. and Siegel, M. and
                   Fiehler, K. and von Cramon, D. Y. and Engel, A. K.},
  title = {Trial-by-trial coupling of concurrent
                   electroencephalogram and functional magnetic resonance
                   imaging identifies the dynamics of performance
                   monitoring.},
  journal = {J Neurosci},
  volume = {25},
  number = {50},
  pages = {11730-7},
  abstract = {Goal-directed behavior requires the continuous
                   monitoring and dynamic adjustment of ongoing actions.
                   Here, we report a direct coupling between the
                   event-related electroencephalogram (EEG), functional
                   magnetic resonance imaging (fMRI), and behavioral
                   measures of performance monitoring in humans. By
                   applying independent component analysis to EEG signals
                   recorded simultaneously with fMRI, we found the
                   single-trial error-related negativity of the EEG to be
                   systematically related to behavior in the subsequent
                   trial, thereby reflecting immediate behavioral
                   adjustments of a cognitive performance monitoring
                   system. Moreover, this trial-by-trial EEG measure of
                   performance monitoring predicted the fMRI activity in
                   the rostral cingulate zone, a brain region thought to
                   play a key role in processing of response errors. We
                   conclude that investigations of the dynamic coupling
                   between EEG and fMRI provide a powerful approach for
                   the study of higher order brain functions.},
  authoraddress = {Institute of Neurophysiology and Pathophysiology,
                   Center of Experimental Medicine, University Medical
                   Center, Hamburg University, D-20246 Hamburg, Germany.
                   stefan@debener.de},
  keywords = {Adult ; Comparative Study ;
                   Electroencephalography/*methods ; Evoked
                   Potentials/*physiology ; Female ; Humans ; Magnetic
                   Resonance Imaging/*methods ; Male ; Photic
                   Stimulation/methods ; Psychomotor
                   Performance/*physiology ; Research Support, Non-U.S.
                   Gov't},
  language = {eng},
  medline-aid = {25/50/11730 [pii] ; 10.1523/JNEUROSCI.3286-05.2005
                   [doi]},
  medline-da = {20051215},
  medline-dcom = {20060511},
  medline-edat = {2005/12/16 09:00},
  medline-fau = {Debener, Stefan ; Ullsperger, Markus ; Siegel, Markus
                   ; Fiehler, Katja ; von Cramon, D Yves ; Engel, Andreas
                   K},
  medline-is = {1529-2401 (Electronic)},
  medline-jid = {8102140},
  medline-jt = {The Journal of neuroscience : the official journal of
                   the Society for Neuroscience.},
  medline-mhda = {2006/05/12 09:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {16354931},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {J Neurosci. 2005 Dec 14;25(50):11730-7.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16354931},
  year = 2005
}
@ARTICLE{DUS+06,
  author = {Debener, S. and Ullsperger, M. and Siegel, M. and
                   Engel, A. K.},
  title = {Single-trial {EEG}-f{MRI} reveals the dynamics of
                   cognitive function.},
  journal = {Trends Cogn Sci},
  volume = {10},
  number = {12},
  pages = {558-63},
  abstract = {Two major non-invasive techniques in cognitive
                   neuroscience, electroencephalography (EEG) and
                   functional magnetic resonance imaging (fMRI), have
                   complementary advantages with regard to their spatial
                   and temporal resolution. Recent hardware and software
                   developments have made it feasible to acquire EEG and
                   fMRI data simultaneously. We emphasize the potential of
                   simultaneous EEG and fMRI recordings to pursue new
                   strategies in cognitive neuroimaging. Specifically, we
                   propose that, by exploiting the combined spatiotemporal
                   resolution of the methods, the integration of EEG and
                   fMRI recordings on a single-trial level enables the
                   rich temporal dynamics of information processing to be
                   characterized within spatially well-defined neural
                   networks.},
  authoraddress = {MRC Institute of Hearing Research Southampton, Royal
                   South Hants Hospital, Southampton, SO14 0YG, UK.},
  language = {eng},
  medline-aid = {S1364-6613(06)00272-5 [pii] ;
                   10.1016/j.tics.2006.09.010 [doi]},
  medline-da = {20061204},
  medline-dep = {20061030},
  medline-edat = {2006/11/01 09:00},
  medline-fau = {Debener, Stefan ; Ullsperger, Markus ; Siegel, Markus
                   ; Engel, Andreas K},
  medline-is = {1364-6613 (Print)},
  medline-jid = {9708669},
  medline-jt = {Trends in cognitive sciences},
  medline-mhda = {2006/11/01 09:00},
  medline-own = {NLM},
  medline-phst = {2006/07/04 [received] ; 2006/09/04 [revised] ;
                   2006/09/19 [accepted] ; 2006/10/30 [aheadofprint]},
  medline-pl = {England},
  medline-pmid = {17074530},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Trends Cogn Sci. 2006 Dec;10(12):558-63. Epub 2006 Oct
                   30.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17074530},
  year = 2006
}
@ARTICLE{DXW+06,
  author = {Duff, E. and Xiong, J. and Wang, B. and Cunnington, R.
                   and Fox, P. and Egan, G.},
  title = {Complex spatio-temporal dynamics of f{MRI} {BOLD}: {A}
                   study of motor learning.},
  journal = {Neuroimage},
  abstract = {Many studies have investigated the temporal properties
                   of BOLD signal responses to task performance in regions
                   of interest, often noting significant departures from
                   the conventionally modelled response shape, and
                   significant variation between regions. However, these
                   investigations are rarely extended across the whole
                   brain nor incorporated into the routine analysis of
                   fMRI studies. As a result, little is known about the
                   range of response shapes generated in the brain by
                   common paradigms. The present study finds such temporal
                   dynamics can be complex. We made a detailed
                   investigation of BOLD signal responses across the whole
                   brain during a two minute motor-sequence task, and
                   tracked changes due to learning. The multi-component
                   OSORU (Onset, Sustained, Offset, Ramp, Undershoot)
                   linear model, developed by Harms and Melcher
                   (J.Neurophysiology, 2003), was extended to characterise
                   responses. In many regions, signal transients persisted
                   for over thirty seconds, with large signal spikes at
                   onset often followed by a dip in signal below the final
                   sustained level of activation. Training altered certain
                   features of the response shape, suggesting that
                   different features of the response may reflect
                   different aspects of neuro-vascular dynamics.
                   Unmodelled, this may give rise to inconsistent results
                   across paradigms of varying task durations. Few of the
                   observed effects have been thoroughly addressed in
                   physiological models of the BOLD response. The complex,
                   extended dynamics generated by this simple, often
                   employed task, suggests characterisation and modelling
                   of temporal aspects of BOLD responses needs to be
                   carried out routinely, informing experimental design
                   and analysis, and physiological modelling.},
  authoraddress = {The Howard Florey Institute and the Centre for
                   Neuroscience, The University of Melbourne, VIC 3010,
                   Australia; Department of Mathematics and Statistics,
                   University of Melbourne, Australia; Cooperative
                   Research Centre for Sensor Signal and Information
                   Processing, Department of Electrical and Electronic
                   Engineering, The University of Melbourne, Australia.},
  language = {ENG},
  medline-aid = {S1053-8119(06)00930-X [pii] ;
                   10.1016/j.neuroimage.2006.09.006 [doi]},
  medline-da = {20061103},
  medline-dep = {20061031},
  medline-edat = {2006/11/04 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2006/11/04 09:00},
  medline-own = {NLM},
  medline-phst = {2006/06/15 [received] ; 2006/08/17 [revised] ;
                   2006/09/03 [accepted]},
  medline-pmid = {17081770},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2006 Oct 31;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17081770},
  year = 2006
}
@ARTICLE{ECM+07,
  author = {Eichele, T. and Calhoun, V. D. and Moosmann, M. and
                   Specht, K. and Jongsma, M. L. and Quiroga, R. Q. and
                   Nordby, H. and Hugdahl, K.},
  title = {Unmixing concurrent {EEG}-f{MRI} with parallel
                   independent component analysis.},
  journal = {Int J Psychophysiol},
  abstract = {Concurrent event-related EEG-fMRI recordings pick up
                   volume-conducted and hemodynamically convoluted signals
                   from latent neural sources that are spatially and
                   temporally mixed across the brain, i.e. the observed
                   data in both modalities represent multiple,
                   simultaneously active, regionally overlapping neuronal
                   mass responses. This mixing process decreases the
                   sensitivity of voxel-by-voxel prediction of hemodynamic
                   activation by the EEG when multiple sources contribute
                   to either the predictor and/or the response variables.
                   In order to address this problem, we used independent
                   component analysis (ICA) to recover maps from the fMRI
                   and timecourses from the EEG, and matched these
                   components across the modalities by correlating their
                   trial-to-trial modulation. The analysis was implemented
                   as a group-level ICA that extracts a single set of
                   components from the data and directly allows for
                   population inferences about consistently expressed
                   function-relevant spatiotemporal responses. We
                   illustrate the utility of this method by extracting a
                   previously undetected but relevant EEG-fMRI component
                   from a concurrent auditory target detection experiment.},
  authoraddress = {Department of Biological and Medical Psychology,
                   University of Bergen, Jonas Lies Vei 91, 5011 Bergen,
                   Norway.},
  language = {ENG},
  medline-aid = {S0167-8760(07)00161-4 [pii] ;
                   10.1016/j.ijpsycho.2007.04.010 [doi]},
  medline-da = {20070810},
  medline-dep = {20070802},
  medline-edat = {2007/08/11 09:00},
  medline-is = {0167-8760 (Print)},
  medline-jid = {8406214},
  medline-mhda = {2007/08/11 09:00},
  medline-own = {NLM},
  medline-phst = {2006/11/17 [received] ; 2007/04/27 [accepted]},
  medline-pmid = {17688963},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Int J Psychophysiol. 2007 Aug 2;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17688963},
  year = 2007
}
@ARTICLE{ESM+05,
  author = {Eichele, T. and Specht, K. and Moosmann, M. and
                   Jongsma, M. L. and Quiroga, R. Q. and Nordby, H. and
                   Hugdahl, K.},
  title = {Assessing the spatiotemporal evolution of neuronal
                   activation with single-trial event-related potentials
                   and functional {MRI}.},
  journal = {Proc Natl Acad Sci U S A},
  volume = {102},
  number = {49},
  pages = {17798-803},
  abstract = {The brain acts as an integrated information processing
                   system, which methods in cognitive neuroscience have so
                   far depicted in a fragmented fashion. Here, we propose
                   a simple and robust way to integrate functional MRI
                   (fMRI) with single trial event-related potentials (ERP)
                   to provide a more complete spatiotemporal
                   characterization of evoked responses in the human
                   brain. The idea behind the approach is to find brain
                   regions whose fMRI responses can be predicted by
                   paradigm-induced amplitude modulations of
                   simultaneously acquired single trial ERPs. The method
                   was used to study a variant of a two-stimulus auditory
                   target detection (odd-ball) paradigm that manipulated
                   predictability through alternations of stimulus
                   sequences with random or regular target-to-target
                   intervals. In addition to electrophysiologic and
                   hemodynamic evoked responses to auditory targets per
                   se, single-trial modulations were expressed during the
                   latencies of the P2 (170-ms), N2 (200-ms), and P3
                   (320-ms) components and predicted spatially separated
                   fMRI activation patterns. These spatiotemporal matches,
                   i.e., the prediction of hemodynamic activation by
                   time-variant information from single trial ERPs, permit
                   inferences about regional responses using fMRI with the
                   temporal resolution provided by electrophysiology.},
  authoraddress = {Department of Biological and Medical Psychology,
                   University of Bergen, 5009 Bergen, Norway.
                   tom.eichele@psybp@uib.no},
  keywords = {Adult ; Brain/*cytology/*physiology ;
                   Electroencephalography ; Evoked Potentials/*physiology
                   ; Female ; Humans ; Magnetic Resonance Imaging ; Male ;
                   Neurons/*physiology ; Research Support, Non-U.S. Gov't
                   ; Time Factors},
  language = {eng},
  medline-aid = {0505508102 [pii] ; 10.1073/pnas.0505508102 [doi]},
  medline-da = {20051207},
  medline-dcom = {20060118},
  medline-dep = {20051128},
  medline-edat = {2005/11/30 09:00},
  medline-fau = {Eichele, Tom ; Specht, Karsten ; Moosmann, Matthias ;
                   Jongsma, Marijtje L A ; Quiroga, Rodrigo Quian ;
                   Nordby, Helge ; Hugdahl, Kenneth},
  medline-is = {0027-8424 (Print)},
  medline-jid = {7505876},
  medline-jt = {Proceedings of the National Academy of Sciences of the
                   United States of America.},
  medline-mhda = {2006/01/19 09:00},
  medline-own = {NLM},
  medline-phst = {2005/11/28 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16314575},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Proc Natl Acad Sci U S A. 2005 Dec
                   6;102(49):17798-803. Epub 2005 Nov 28.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16314575},
  year = 2005
}
@ARTICLE{FBW98,
  author = {Frank, L. R. and Buxton, R. B. and Wong, E. C.},
  title = {Probabilistic analysis of functional magnetic
                   resonance imaging data.},
  journal = {Magn Reson Med},
  volume = {39},
  number = {1},
  pages = {132-148},
  abstract = {Probability theory is applied to the analysis of fMRI
                   data. The posterior distribution of the parameters is
                   shown to incorporate all the information available from
                   the data, the hypotheses, and the prior information.
                   Under appropriate simplifying conditions, the theory
                   reduces to the standard statistical test, including the
                   general linear model. The theory is particularly suited
                   to handle the spatial variations in the noise present
                   in fMRI, allowing the comparison of activated voxels
                   that have different, and unknown, noise. The theory
                   also explicitly includes prior information, which is
                   shown to be critical in the attainment of reliable
                   activation maps.},
  authoraddress = {Department of Radiology, University of California at
                   San Diego, USA.},
  keywords = {Human ; Image Enhancement ; Likelihood Functions ;
                   Magnetic Resonance Imaging/*methods ; Models,
                   Statistical ; *Probability Theory ; Sensitivity and
                   Specificity ; Signal Processing, Computer-Assisted ;
                   Statistics},
  language = {eng},
  medline-cin = {Magn Reson Med. 1999 Jun;41(6):1279-80. PMID: 10371464},
  medline-da = {19980303},
  medline-dcom = {19980303},
  medline-edat = {1998/01/23},
  medline-fau = {Frank, L R ; Buxton, R B ; Wong, E C},
  medline-is = {0740-3194},
  medline-jid = {8505245},
  medline-lr = {20011126},
  medline-mhda = {1998/01/23 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9438447},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {35},
  medline-sb = {IM},
  medline-so = {Magn Reson Med 1998 Jan;39(1):132-48.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9438447},
  year = 1998
}
@ARTICLE{FFJ+98,
  author = {Friston, K. J. and Fletcher, P. and Josephs, O. and
                   Holmes, A. and Rugg, M. D. and Turner, R.},
  title = {Event-related f{MRI}: characterizing differential
                   responses.},
  journal = {NeuroImage},
  volume = {7},
  number = {1},
  pages = {30-40},
  abstract = {We present an approach to characterizing the
                   differences among event-related hemodynamic responses
                   in functional magnetic resonance imaging that are
                   evoked by different sorts of stimuli. This approach is
                   predicated on a linear convolution model and standard
                   inferential statistics as employed by statistical
                   parametric mapping. In particular we model evoked
                   responses, and their differences, in terms of basis
                   functions of the peri-stimulus time. This facilitates a
                   characterization of the temporal response profiles that
                   has a high effective temporal resolution relative to
                   the repetition time. To demonstrate the technique we
                   examined differential responses to visually presented
                   words that had been seen prior to scanning or that were
                   novel. The form of these differences involved both the
                   magnitude and the latency of the response components.
                   In this paper we focus on bilateral ventrolateral
                   prefrontal responses that show deactivations for
                   previously seen words and activations for novel words.},
  authoraddress = {The Wellcome Department of Cognitive Neurology,
                   Institute of Neurology, London, United Kingdom.},
  keywords = {Evoked Potentials/*physiology ; Frontal
                   Lobe/*physiology ; Hemodynamic Processes/*physiology ;
                   Human ; Linear Models ; *Magnetic Resonance Imaging ;
                   Memory/*physiology ; Models, Theoretical ; Reaction
                   Time ; Reference Values ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1053811997903062 [pii]},
  medline-da = {19980317},
  medline-dcom = {19980317},
  medline-edat = {1998/03/17},
  medline-fau = {Friston, K J ; Fletcher, P ; Josephs, O ; Holmes, A ;
                   Rugg, M D ; Turner, R},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {1998/03/17 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9500830},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 1998 Jan;7(1):30-40.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9500830},
  year = 1998
}
@ARTICLE{FG03,
  author = {Formisano, E. and Goebel, R.},
  title = {Tracking cognitive processes with functional {MRI}
                   mental chronometry},
  journal = {Curr Opin Neurobiol},
  volume = {13},
  number = {2},
  pages = {174-181},
  abstract = {Functional magnetic resonance imaging (fMRI) is used
                   widely to determine the spatial layout of brain
                   activation associated with specific cognitive tasks at
                   a spatial scale of millimeters. Recent methodological
                   improvements have made it possible to determine the
                   latency and temporal structure of the activation at a
                   temporal scale of few hundreds of milliseconds. Despite
                   the sluggishness of the hemodynamic response, fMRI can
                   detect a cascade of neural activations - the signature
                   of a sequence of cognitive processes. Decomposing the
                   processing into stages is greatly aided by measuring
                   intermediate responses. By combining event-related fMRI
                   and behavioral measurement in experiment and analysis,
                   trial-by-trial temporal links can be established
                   between cognition and its neural substrate.},
  authoraddress = {Department of Cognitive Neuroscience, Faculty of
                   Psychology, Maastricht University, Postbus 616, 6200
                   MD, Maastricht, The Netherlands.
                   e.formisano@psychology.unimass.nl},
  keywords = {Brain/*physiology ; *Brain Mapping ;
                   Cognition/*physiology ; Human ; *Magnetic Resonance
                   Imaging/methods},
  language = {eng},
  medline-aid = {S0959438803000448 [pii]},
  medline-da = {20030514},
  medline-dcom = {20030708},
  medline-edat = {2003/05/15 05:00},
  medline-fau = {Formisano, Elia ; Goebel, Rainer},
  medline-is = {0959-4388},
  medline-jid = {9111376},
  medline-mhda = {2003/07/09 05:00},
  medline-own = {NLM},
  medline-pl = {England},
  medline-pmid = {12744970},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {58},
  medline-sb = {IM},
  medline-so = {Curr Opin Neurobiol 2003 Apr;13(2):174-81.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12744970},
  year = 2003
}
@ARTICLE{FMJ03,
  author = {Foxe, J. J. and McCourt, M. E. and Javitt, D. C.},
  title = {Right hemisphere control of visuospatial attention:
                   line-bisection judgments evaluated with high-density
                   electrical mapping and source analysis},
  journal = {NeuroImage},
  volume = {19},
  number = {3},
  pages = {710-726},
  abstract = {The "line-bisection" task has proven an especially
                   useful clinical tool for assessment of spatial neglect
                   syndrome in neurological patients. Here, we
                   investigated the neural processes involved in
                   performing this task by recording high-density
                   event-related potentials from 128 scalp electrodes in
                   normal observers. We characterized a robust net
                   negative potential from 170-400 ms poststimulus
                   presentation that correlates with line-bisection
                   judgments. Topographic mapping shows three distinct
                   phases to this negativity. The first phase
                   (approximately 170-190 ms) has a scalp distribution
                   exclusively over the right parieto-occipital and
                   lateral occipital scalp, consistent with generators in
                   the region of the right temporo-parietal junction and
                   right lateral occipital cortices. The second phase
                   (approximately 190-240 ms) sees the emergence of a
                   second negative focus over the right central parietal
                   scalp, consistent with subsequent involvement of right
                   superior parietal cortices. In the third phase
                   (approximately 240-400 ms), the topography becomes
                   dominated by this right central parietal negativity.
                   Inverse source modeling confirmed that right hemisphere
                   lateral occipital, inferior parietal, and superior
                   parietal regions were the likeliest generators of the
                   bulk of the activity associated with this effect. The
                   line stimuli were also presented at three contrast
                   levels (3, 25, and 100\%) in order to manipulate both
                   the latency of stimulus processing and the relative
                   contributions from magnocellular and parvocellular
                   inputs. Through this manipulation, we show that the
                   line-bisection effect systematically tracks/follows the
                   latency of the N1 component, which is considered a
                   temporal marker for object processing in the ventral
                   visual stream. This pattern of effects suggests that
                   this task invokes an allocentric (object-based) form of
                   visuospatial attention. Further, at 3\% contrast, the
                   line-bisection effect was equivalent to the effects
                   seen at higher contrast levels, suggesting that
                   parvocellular inputs are not necessary for successful
                   performance of this task.},
  authoraddress = {The Cognitive Neurophysiology Laboratory, Nathan S.
                   Kline Institute for Psychiatric Research, Program in
                   Cognitive Neuroscience and Schizophrenia, 140 Old
                   Orangeburg Road, Orangeburg, NY 10962, USA.
                   foxe@nki.rfmh.org},
  keywords = {Adult ; Algorithms ; Attention/*physiology ; *Brain
                   Mapping ; Cerebral Cortex/*physiology ;
                   Electroencephalography ; Evoked Potentials,
                   Visual/physiology ; Female ; Human ; Image Processing,
                   Computer-Assisted ; Laterality/*physiology ; Male ;
                   Middle Aged ; Photic Stimulation ; Psychometrics ;
                   Space Perception/*physiology ; Support, Non-U.S. Gov't
                   ; Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {S1053811903000570 [pii]},
  medline-da = {20030725},
  medline-dcom = {20030909},
  medline-edat = {2003/07/26 05:00},
  medline-fau = {Foxe, John J ; McCourt, Mark E ; Javitt, Daniel C},
  medline-gr = {EY12267/EY/NEI ; MH49334/MH/NIMH ; MH63434/MH/NIMH},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {2003/09/10 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12880801},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2003 Jul;19(3):710-26.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12880801},
  year = 2003
}
@ARTICLE{FMT+00,
  author = {Friston, K. J. and Mechelli, A. and Turner, R. and
                   Price, C. J.},
  title = {Nonlinear responses in f{MRI}: the {B}alloon model,
                   {V}olterra kernels, and other hemodynamics},
  journal = {NeuroImage},
  volume = {12},
  number = {4},
  pages = {466-477},
  abstract = {There is a growing appreciation of the importance of
                   nonlinearities in evoked responses in fMRI,
                   particularly with the advent of event-related fMRI.
                   These nonlinearities are commonly expressed as
                   interactions among stimuli that can lead to the
                   suppression and increased latency of responses to a
                   stimulus that are incurred by a preceding stimulus. We
                   have presented previously a model-free characterization
                   of these effects using generic techniques from
                   nonlinear system identification, namely a Volterra
                   series formulation. At the same time Buxton et al.
                   (1998) described a plausible and compelling dynamical
                   model of hemodynamic signal transduction in fMRI.
                   Subsequent work by Mandeville et al. (1999) provided
                   important theoretical and empirical constraints on the
                   form of the dynamic relationship between blood flow and
                   volume that underpins the evolution of the fMRI signal.
                   In this paper we combine these system identification
                   and model-based approaches and ask whether the Balloon
                   model is sufficient to account for the nonlinear
                   behaviors observed in real time series. We conclude
                   that it can, and furthermore the model parameters that
                   ensue are biologically plausible. This conclusion is
                   based on the observation that the Balloon model can
                   produce Volterra kernels that emulate empirical
                   kernels. To enable this evaluation we had to embed the
                   Balloon model in a hemodynamic input-state-output model
                   that included the dynamics of perfusion changes that
                   are contingent on underlying synaptic activation. This
                   paper presents (i) the full hemodynamic model (ii), how
                   its associated Volterra kernels can be derived, and
                   (iii) addresses the model's validity in relation to
                   empirical nonlinear characterizations of evoked
                   responses in fMRI and other neurophysiological
                   constraints.},
  authoraddress = {The Wellcome Department of Cognitive Neurology,
                   Institute of Neurology, Queen Square, London WC1N 3BG,
                   United Kingdom.},
  keywords = {Brain/*physiology ; Cerebrovascular
                   Circulation/*physiology ; Hemodynamic
                   Processes/physiology ; *Magnetic Resonance Imaging ;
                   *Models, Cardiovascular ; *Models, Neurological ;
                   *Nonlinear Dynamics ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1006/nimg.2000.0630 [doi] ; S105381190090630X [pii]},
  medline-ci = {Copyright 2000 Academic Press.},
  medline-da = {20001023},
  medline-dcom = {20001101},
  medline-edat = {2000/09/16 11:00},
  medline-fau = {Friston, K J ; Mechelli, A ; Turner, R ; Price, C J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {2001/02/28 10:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10988040},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2000 Oct;12(4):466-77.},
  medline-stat = {completed},
  year = 2000
}
@ARTICLE{FOG04,
  author = {Foucher, J.R. and Otzenberger, H. and Gounot, D.},
  title = {Where arousal meets attention: a simultaneous f{MRI}
                   and {EEG} recording study.},
  journal = {Neuroimage},
  volume = {22},
  number = {2},
  pages = {688-697},
  abstract = {In this fMRI study, we looked for the regions
                   supporting interaction between cortical arousal and
                   attention during three conditions: detection,
                   observation, and rest. Arousal measurements were
                   obtained from the EEG low-frequency (LF) power (5-9.5
                   Hz) recorded continuously together with fMRI. Whatever
                   the condition, arousal was positively correlated with
                   the fMRI signal of the right dorsal-lateral prefrontal
                   and superior parietal cortices, closely overlapping
                   regions involved in the maintenance of attention.
                   Although the inferior temporal areas also presented a
                   correlation with arousal during detection, path
                   analysis suggests that this influence may be indirect,
                   through the top-down influence of the previously
                   mentioned network. However, those visual-processing
                   areas could account for the correlation between arousal
                   and performances. Lastly, the medial frontal cortex,
                   frontal opercula, and thalamus were inversely
                   correlated with arousal but only during detection and
                   observation so that they could account for the control
                   of arousal.},
  authoraddress = {Clinique Psychiatrique, Hopitaux Universitaires, BP
                   406-67091 Strasbourg Cedex, France.
                   foucher@alsace.u-strasbg.fr},
  keywords = {Adult ; Arousal/*physiology ; Attention/*physiology ;
                   Brain Mapping/methods ; Comparative Study ;
                   Electroencephalography/*methods ; Female ; Humans ;
                   Magnetic Resonance Imaging/methods ; Male ; Photic
                   Stimulation ; Reaction Time/physiology ; Reference
                   Values ; Research Support, Non-U.S. Gov't ; Visual
                   Perception/physiology},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2004.01.048 [doi] ;
                   S1053811904000898 [pii]},
  medline-da = {20040614},
  medline-dcom = {20040819},
  medline-edat = {2004/06/15 05:00},
  medline-fau = {Foucher, J R ; Otzenberger, H ; Gounot, D},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20041117},
  medline-mhda = {2004/08/20 05:00},
  medline-own = {NLM},
  medline-phst = {2003/09/16 [received] ; 2004/01/20 [revised] ;
                   2004/01/27 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15193597},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuroimage 2004 Jun;22(2):688-97.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15193597},
  year = 2004
}
@ARTICLE{FWK+99,
  author = {Fuchs, M. and Wagner, M. and Kohler, T. and Wischmann,
                   H.A.},
  title = {Linear and nonlinear current density reconstructions},
  journal = {J Clin Neurophysiol},
  volume = {16},
  number = {3},
  pages = {267-295},
  abstract = {Minimum norm algorithms for EEG source reconstruction
                   are studied in view of their spatial resolution,
                   regularization, and lead-field normalization
                   properties, and their computational efforts. Two
                   classes of minimum norm solutions are examined: linear
                   least squares methods and nonlinear L1-norm approaches.
                   Two special cases of linear algorithms, the well known
                   Minimum Norm Least Squares and an implementation with
                   Laplacian smoothness constraints, are compared to two
                   nonlinear algorithms comprising sparse and standard
                   L1-norm methods. In a signal-to-noise-ratio framework,
                   two of the methods allow automatic determination of the
                   optimum regularization parameter. Compensation methods
                   for the different depth dependencies of all approaches
                   by lead-field normalization are discussed. Simulations
                   with tangentially and radially oriented test dipoles at
                   two different noise levels are performed to reveal and
                   compare the properties of all approaches. Finally,
                   cortically constrained versions of the algorithms are
                   applied to two epileptic spike data sets and compared
                   to results of single equivalent dipole fits and
                   spatiotemporal source models.},
  authoraddress = {Philips Research Laboratories Hamburg, Germany.},
  keywords = {Algorithms ; Electroencephalography/*methods ;
                   Epilepsy/*diagnosis/pathology/physiopathology ; Female
                   ; Human ; Image Interpretation, Computer-Assisted ;
                   Linear Models ; Magnetic Resonance Imaging/*methods ;
                   Male ; Nonlinear Dynamics ; Signal Processing,
                   Computer-Assisted},
  language = {eng},
  medline-da = {19990902},
  medline-dcom = {19990902},
  medline-edat = {1999/07/30},
  medline-fau = {Fuchs, M ; Wagner, M ; Kohler, T ; Wischmann, H A},
  medline-is = {0736-0258},
  medline-jid = {8506708},
  medline-lr = {20001218},
  medline-mhda = {1999/07/30 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10426408},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {45},
  medline-sb = {IM},
  medline-so = {J Clin Neurophysiol 1999 May;16(3):267-95.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10426408},
  year = 1999
}
@ARTICLE{FWW+98,
  author = {Fuchs, M. and Wagner, M. and Wischmann, H. A. and
                   Kohler, T. and Theissen, A. and Drenckhahn, R. and
                   Buchner, H.},
  title = {Improving source reconstructions by combining
                   bioelectric and biomagnetic data},
  journal = {Electroencephalogr Clin Neurophysiol},
  volume = {107},
  number = {2},
  pages = {93-111},
  abstract = {OBJECTIVES: A framework for combining bioelectric and
                   biomagnetic data is presented. The data are transformed
                   to signal-to-noise ratios and reconstruction algorithms
                   utilizing a new regularization approach are introduced.
                   METHODS: Extensive simulations are carried out for 19
                   different EEG and MEG montages with radial and
                   tangential test dipoles at different eccentricities and
                   noise levels. The methods are verified by real SEP/SEF
                   measurements. A common realistic volume conductor is
                   used and the less well known in vivo conductivities are
                   matched by calibration to the magnetic data. Single
                   equivalent dipole fits as well as spatio-temporal
                   source models are presented for single and combined
                   modality evaluations and overlaid to anatomic MR
                   images. RESULTS: Normalized sensitivity and dipole
                   resolution profiles of the different EEG/MEG
                   acquisition systems are derived from the simulated
                   data. The methods and simulations are verified by
                   simultaneously measured somatosensory data.
                   CONCLUSIONS: Superior spatial resolution of the
                   combined data studies is revealed, which is due to the
                   complementary nature of both modalities and the
                   increased number of sensors. A better understanding of
                   the underlying neuronal processes can be achieved,
                   since an improved differentiation between
                   quasi-tangential and quasi-radial sources is possible.},
  authoraddress = {Philips Research Laboratories Hamburg, Germany.},
  keywords = {*Brain Mapping ; *Computer Simulation ;
                   Electroencephalography/*methods/standards ; Evoked
                   Potentials, Somatosensory/physiology ; Head ; Human ;
                   Image Processing, Computer-Assisted ;
                   Magnetoencephalography/*methods/standards ; Software},
  language = {eng},
  medline-aid = {S0013469498000467 [pii]},
  medline-da = {19981008},
  medline-dcom = {19981008},
  medline-edat = {1998/09/29},
  medline-fau = {Fuchs, M ; Wagner, M ; Wischmann, H A ; Kohler, T ;
                   Theissen, A ; Drenckhahn, R ; Buchner, H},
  medline-is = {0013-4694},
  medline-jid = {0375035},
  medline-lr = {20001218},
  medline-mhda = {1998/09/29 00:01},
  medline-own = {NLM},
  medline-pl = {IRELAND},
  medline-pmid = {9751281},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Electroencephalogr Clin Neurophysiol 1998
                   Aug;107(2):93-111.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9751281},
  year = 1998
}
@ARTICLE{Fri02,
  author = {Friston, K. J.},
  title = {Bayesian estimation of dynamical systems: an
                   application to f{MRI}.},
  journal = {Neuroimage},
  volume = {16},
  number = {2},
  pages = {513-30},
  abstract = {This paper presents a method for estimating the
                   conditional or posterior distribution of the parameters
                   of deterministic dynamical systems. The procedure
                   conforms to an EM implementation of a Gauss-Newton
                   search for the maximum of the conditional or posterior
                   density. The inclusion of priors in the estimation
                   procedure ensures robust and rapid convergence and the
                   resulting conditional densities enable Bayesian
                   inference about the model parameters. The method is
                   demonstrated using an input-state-output model of the
                   hemodynamic coupling between experimentally designed
                   causes or factors in fMRI studies and the ensuing BOLD
                   response. This example represents a generalization of
                   current fMRI analysis models that accommodates
                   nonlinearities and in which the parameters have an
                   explicit physical interpretation. Second, the approach
                   extends classical inference, based on the likelihood of
                   the data given a null hypothesis about the parameters,
                   to more plausible inferences about the parameters of
                   the model given the data. This inference provides for
                   confidence intervals based on the conditional density.},
  authoraddress = {The Wellcome Department of Cognitive Neurology,
                   Institute of Neurology, Queen Square, London, United
                   Kingdom WC1N 3BG.},
  keywords = {*Bayes Theorem ; Brain/*physiology ; Cerebrovascular
                   Circulation ; Hemodynamic Processes ; Humans ;
                   Likelihood Functions ; *Magnetic Resonance Imaging ;
                   Models, Cardiovascular ; Models, Neurological ;
                   Nonlinear Dynamics ; Oxygen/blood ; Probability ;
                   Research Support, Non-U.S. Gov't ; Statistics/methods},
  language = {eng},
  medline-aid = {10.1006/nimg.2001.1044 [doi] ; S1053811901910444 [pii]},
  medline-ci = {2002 Elsevier Science (USA)},
  medline-da = {20020528},
  medline-dcom = {20020724},
  medline-edat = {2002/05/29 10:00},
  medline-fau = {Friston, K J},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-lr = {20041117},
  medline-mhda = {2002/07/26 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12030834},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2002 Jun;16(2):513-30.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12030834},
  year = 2002
}
@ARTICLE{GB67,
  author = {Geddes, L. A. and Baker, L. E.},
  title = {The specific resistance of biological material--a
                   compendium of data for the biomedical engineer and
                   physiologist},
  journal = {Med Biol Eng},
  volume = {5},
  number = {3},
  pages = {271-293},
  keywords = {Animals ; Cats ; Cattle ; Dogs ; Electric Conductivity
                   ; *Electrodiagnosis ; *Electrophysiology ; Guinea Pigs
                   ; Human ; Rabbits},
  language = {eng},
  medline-da = {19671118},
  medline-dcom = {19671118},
  medline-edat = {1967/05/01},
  medline-fau = {Geddes, L A ; Baker, L E},
  medline-is = {0025-696X},
  medline-jid = {0043417},
  medline-lr = {20031114},
  medline-mhda = {1967/05/01 00:01},
  medline-own = {NLM},
  medline-pl = {ENGLAND},
  medline-pmid = {6068939},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Med Biol Eng 1967 May;5(3):271-93.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=6068939},
  year = 1967
}
@ARTICLE{GCG+03,
  author = {Garreffa, G. and Carni, M. and Gualniera, G. and
                   Ricci, G. B. and Bozzao, L. and De Carli, D. and
                   Morasso, P. and Pantano, P. and Colonnese, C. and Roma,
                   V. and Maraviglia, B.},
  title = {Real-time {MR} artifacts filtering during continuous
                   {EEG}/f{MRI} acquisition},
  journal = {Magn Reson Imaging},
  volume = {21},
  number = {10},
  pages = {1175-1189},
  abstract = {The purpose of this study was the development of a
                   real-time filtering procedure of MRI artifacts in order
                   to monitor the EEG activity during continuous EEG/fMRI
                   acquisition. The development of a combined EEG and fMRI
                   technique has increased in the past few years.
                   Preliminary "spike-triggered" applications have been
                   possible because in this method, EEG knowledge was only
                   necessary to identify a trigger signal to start a
                   delayed fMRI acquisition. In this way, the two methods
                   were used together but in an interleaved manner. In
                   real simultaneous applications, like event-related fMRI
                   study, artifacts induced by MRI events on EEG traces
                   represent a substantial obstacle for a right analysis.
                   Up until now, the methods proposed to solve this
                   problem are mainly based on procedures to remove
                   post-processing artifacts without the possibility to
                   control electrophysiological behavior of the patient
                   during fMRI scan. Moreover, these methods are not
                   characterized by a strong "prior knowledge" of the
                   artifact, which is an imperative condition to avoid any
                   loss of information on the physiological signals
                   recovered after filtering. In this work, we present a
                   new method to perform simultaneous EEG/fMRI study with
                   real-time artifacts filtering characterized by a
                   procedure based on a preliminary analytical study of
                   EPI sequence parameters-related EEG-artifact shapes.
                   Standard EEG equipment was modified in order to work
                   properly during ultra-fast MRI acquisitions. Changes
                   included: high-performance acquisition device;
                   electrodes/cap/wires/cables materials and geometric
                   design; shielding box for EEG signal receiver; optical
                   fiber link; and software. The effects of the RF pulse
                   and time-varying magnetic fields were minimized by
                   using a correct head cap wires-locked environment
                   montage and then removed during EEG/fMRI acquisition
                   with a subtraction algorithm that takes in account the
                   most significant EPI sequence parameters. The on-line
                   method also allows a further post-processing
                   utilization.},
  authoraddress = {Department of Physics, University of Rome, La
                   Sapienza, Rome, Italy.},
  keywords = {Algorithms ; *Artifacts ; Echo-Planar Imaging/methods
                   ; *Electroencephalography/methods ; Human ; *Magnetic
                   Resonance Imaging/methods ; *Signal Processing,
                   Computer-Assisted ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S0730725X03003291 [pii]},
  medline-da = {20040116},
  medline-dcom = {20040514},
  medline-edat = {2004/01/17 05:00},
  medline-fau = {Garreffa, G ; Carni, M ; Gualniera, G ; Ricci, G B ;
                   Bozzao, L ; De Carli, D ; Morasso, P ; Pantano, P ;
                   Colonnese, C ; Roma, V ; Maraviglia, B},
  medline-is = {0730-725X},
  medline-jid = {8214883},
  medline-mhda = {2004/05/15 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {14725925},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Magn Reson Imaging 2003 Dec;21(10):1175-89.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=14725925},
  year = 2003
}
@ARTICLE{GNH00,
  author = {Goutte, C. and Nielsen, F. A. and Hansen, L. K.},
  title = {Modeling the haemodynamic response in f{MRI} using
                   smooth {FIR} filters.},
  journal = {IEEE Trans Med Imaging},
  volume = {19},
  number = {12},
  pages = {1188-201},
  abstract = {Modeling the haemodynamic response in functional
                   magnetic resonance (fMRI) experiments is an important
                   aspect of the analysis of functional neuroimages. This
                   has been done in the past using parametric response
                   function, from a limited family. In this contribution,
                   we adopt a semi-parametric approach based on finite
                   impulse response (FIR) filters. In order to cope with
                   the increase in the number of degrees of freedom, we
                   introduce a Gaussian process prior on the filter
                   parameters. We show how to carry on the analysis by
                   incorporating prior knowledge on the filters,
                   optimizing hyper-parameters using the evidence
                   framework, or sampling using a Markov Chain Monte Carlo
                   (MCMC) approach. We present a comparison of our model
                   with standard haemodynamic response kernels on
                   simulated data, and perform a full analysis of data
                   acquired during an experiment involving visual
                   stimulation.},
  authoraddress = {Department of Mathematical Modeling, Technical
                   University of Denmark, Lyngby.
                   cyril.goutte@inrialpes.fr},
  keywords = {Hemodynamic Processes/*physiology ; Humans ; *Magnetic
                   Resonance Imaging ; Markov Chains ; Monte Carlo Method
                   ; Normal Distribution ; Photic Stimulation},
  language = {eng},
  medline-da = {20010209},
  medline-dcom = {20010503},
  medline-edat = {2001/02/24 12:00},
  medline-fau = {Goutte, C ; Nielsen, F A ; Hansen, L K},
  medline-gr = {P20 MH57180/MH/NIMH},
  medline-is = {0278-0062 (Print)},
  medline-jid = {8310780},
  medline-jt = {IEEE transactions on medical imaging},
  medline-lr = {20061115},
  medline-mhda = {2001/05/05 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11212367},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Research Support, Non-U.S. Gov't ;
                   Research Support, U.S. Gov't, P.H.S.},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {IEEE Trans Med Imaging. 2000 Dec;19(12):1188-201.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11212367},
  year = 2000
}
@ARTICLE{GNP+06,
  author = {Grummich, P. and Nimsky, C. and Pauli, E. and
                   Buchfelder, M. and Ganslandt, O.},
  title = {Combining f{MRI} and {MEG} increases the reliability
                   of presurgical language localization: {A} clinical
                   study on the difference between and congruence of both
                   modalities.},
  journal = {Neuroimage},
  abstract = {To avoid neurological impairment during surgery near
                   language-related eloquent brain areas, we performed
                   presurgical functional brain mapping with functional
                   magnetic resonance imaging (fMRI) and
                   magnetoencephalography (MEG) in 172 patients using
                   language tasks. For MEG localizations, we used either a
                   moving equivalent-current dipole fit or a
                   current-density reconstruction using a minimum variance
                   beamformer with a spatial filter algorithm. We
                   localized the Wernicke and Broca language areas for
                   every patient. We integrated the results into a
                   frameless stereotaxy system. To visualize the results
                   in the navigation microscope during surgery, we
                   superimposed the fMRI and MEG findings on the brain
                   surface. MEG and fMRI results differed in 4% of cases,
                   and in 19%, one modality showed activation but not the
                   other. In the vicinity of large gliomas, the BOLD
                   (blood oxygenation level-dependent) effect was
                   suppressed in 53% of our patients. Of the 124 patients
                   who had surgery, only 7 patients (5.6%) experienced a
                   transient language deterioration, which resolved in all
                   cases. We used MEG and fMRI to show different aspects
                   of brain activity and to establish validation between
                   MEG and fMRI. We conclude that measurement by both MEG
                   and fMRI increases the degree of reliability of
                   language area localization and that the combination of
                   fMRI and MEG is useful for presurgical localization of
                   language-related eloquent cortex.},
  authoraddress = {Department of Neurosurgery, University
                   Erlangen-Nuremberg, Germany; Biomagnetism Group,
                   Neurocenter, University Erlangen-Nuremberg, Germany.},
  language = {ENG},
  medline-aid = {S1053-8119(06)00555-6 [pii] ;
                   10.1016/j.neuroimage.2006.05.034 [doi]},
  medline-da = {20060807},
  medline-dep = {20060802},
  medline-edat = {2006/08/08 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2006/08/08 09:00},
  medline-own = {NLM},
  medline-phst = {2005/12/13 [received] ; 2006/04/05 [revised] ;
                   2006/05/03 [accepted]},
  medline-pmid = {16889984},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2006 Aug 2;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16889984},
  year = 2006
}
@ARTICLE{GPA+03,
  author = {Gitelman, D. R. and Penny, W. D. and Ashburner, J. and
                   Friston, K. J.},
  title = {Modeling regional and psychophysiologic interactions
                   in f{MRI}: the importance of hemodynamic deconvolution},
  journal = {NeuroImage},
  volume = {19},
  number = {1},
  pages = {200-207},
  abstract = {The analysis of functional magnetic resonance imaging
                   (fMRI) time-series data can provide information not
                   only about task-related activity, but also about the
                   connectivity (functional or effective) among regions
                   and the influences of behavioral or physiologic states
                   on that connectivity. Similar analyses have been
                   performed in other imaging modalities, such as positron
                   emission tomography. However, fMRI is unique because
                   the information about the underlying neuronal activity
                   is filtered or convolved with a hemodynamic response
                   function. Previous studies of regional connectivity in
                   fMRI have overlooked this convolution and have assumed
                   that the observed hemodynamic response approximates the
                   neuronal response. In this article, this assumption is
                   revisited using estimates of underlying neuronal
                   activity. These estimates use a parametric empirical
                   Bayes formulation for hemodynamic deconvolution.},
  authoraddress = {The Northwestern Cognitive Brain Mapping Group,
                   Cognitive Neurology and Alzheimer's Disease Center,
                   Northwestern University, Feinberg School of Medicine,
                   Chicago, IL 60611, USA. d-gitelman@northwestern.edu},
  keywords = {Bayes Theorem ; *Brain Mapping ; Hemodynamic Processes
                   ; Human ; *Magnetic Resonance Imaging ; *Models,
                   Neurological ; Neurons/physiology ; *Psychophysiology ;
                   Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {S1053811903000582 [pii]},
  medline-da = {20030603},
  medline-dcom = {20030721},
  medline-edat = {2003/06/05 05:00},
  medline-fau = {Gitelman, Darren R ; Penny, William D ; Ashburner,
                   John ; Friston, Karl J},
  medline-gr = {K23 00940-03/PHS},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {2003/07/23 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12781739},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2003 May;19(1):200-7.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12781739},
  year = 2003
}
@ARTICLE{GPK+07,
  author = {Goncalves, S. I. and Pouwels, P. J. and Kuijer, J. P.
                   and Heethaar, R. M. and de Munck, J. C.},
  title = {Artifact removal in co-registered {EEG}/f{MRI} by
                   selective average subtraction.},
  journal = {Clin Neurophysiol},
  abstract = {OBJECTIVE: Co-registration of EEG
                   (electroencephalogram) and fMRI (functional magnetic
                   resonance imaging) remains a challenge due to the large
                   artifacts induced on the EEG by the MR (magnetic
                   resonance) sequence magnetic fields. Thus, we present
                   an algorithm, based on the average-subtraction method,
                   which is able to correct EEG data for gradient and
                   pulse artifacts. METHODS: MR sequence timing parameters
                   are estimated from the EEG data and both slice and
                   volume artifact templates are subtracted from the data.
                   A clustering algorithm is proposed to account for the
                   variability of the pulse artifact. RESULTS: The
                   algorithm is able to keep the spontaneous EEG as well
                   as visual evoked potentials (VEPs), while removing
                   gradient and pulse artifacts with only a subtraction of
                   selectively averaged data. In the frequency domain, the
                   artifact frequencies are strongly attenuated. Estimated
                   MR sequence time parameters showed that the correction
                   is extremely sensitive to the slice time value. Pulse
                   artifact clustering showed that most of the variability
                   is due to the time jitter of the pulse artifact
                   markers. CONCLUSIONS: Selective subtraction of averages
                   in combination with proper time alignment is enough to
                   remove most of the MR-induced artifacts. SIGNIFICANCE:
                   Clean EEG can be obtained from raw signals that are
                   corrupted by MR-induced artifacts during simultaneous
                   EEG-fMRI scanning without using dedicated hardware to
                   synchronize EEG and fMRI clocks.},
  authoraddress = {Brain Imaging Section, Department of Physics and
                   Medical Technology, VU University Medical Centre, De
                   Boelelaan 1117, 1081 HV Amsterdam, The Netherlands;
                   Institute of Biophysics and Biomedical Engineering,
                   1749-016 Campo Grande, Lisbon, Portugal.},
  language = {ENG},
  medline-aid = {S1388-2457(07)00415-4 [pii] ;
                   10.1016/j.clinph.2007.08.017 [doi]},
  medline-da = {20070924},
  medline-dep = {20070920},
  medline-edat = {2007/09/25 09:00},
  medline-is = {1388-2457 (Print)},
  medline-jid = {100883319},
  medline-mhda = {2007/09/25 09:00},
  medline-own = {NLM},
  medline-phst = {2006/12/14 [received] ; 2007/08/13 [revised] ;
                   2007/08/18 [accepted]},
  medline-pmid = {17889599},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Clin Neurophysiol. 2007 Sep 20;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17889599},
  year = 2007
}
@ARTICLE{GSE+00,
  author = {Goldman, R. I. and Stern, J. M. and Engel, Jr, J. and
                   Cohen, M. S.},
  title = {Acquiring simultaneous {EEG} and functional {MRI}},
  journal = {Clin Neurophysiol},
  volume = {111},
  number = {11},
  pages = {1974-1980},
  abstract = {OBJECTIVE: Electroencephalography (EEG) is a challenge
                   to record simultaneously with functional MRI (fMRI),
                   for it is prone to large artifacts induced by both the
                   static and the time-variant fields of the MR scanner.
                   However, truly concurrent EEG/fMRI recording has great
                   potential for clinical and scientific neurological
                   applications. We have devised a method for acquiring
                   EEG simultaneously with fMRI that minimizes
                   contamination of the EEG signals. METHODS: We recorded
                   EEG differentially during fMRI using special twisted
                   dual-lead electrodes in a bipolar montage, and a
                   combination of analog pre-processing and digital
                   post-processing of the EEG data. We implemented a
                   functional scan protocol that typically yields
                   artifact-free EEG over 87\% of the MR scanning period.
                   RESULTS: Our approach greatly reduced gradient, radio
                   frequency, motion and ballistocardiographic artifact in
                   the EEG, and allowed continuous monitoring of the EEG
                   during functional scanning. To illustrate the quality
                   of the EEG following post-processing, we demonstrated
                   that EEG recorded during fMRI retains useful spectral
                   information. CONCLUSIONS: Quality EEG may be recorded
                   simultaneously with fMRI. With this union, activation
                   maps could be made of any relevant changes in the EEG,
                   such as inter-ictal spikes or spectral variations, or
                   of evoked response potentials (ERPs).},
  authoraddress = {UCLA Brain Mapping Division, Ahmanson-Lovelace Brain
                   Mapping Center, 660 Charles E. Young Drive South, Los
                   Angeles, CA 90095-7085, USA. rig@ucla.edu},
  keywords = {Brain/*anatomy & histology/*physiology ; Brain
                   Mapping/*methods ; Electroencephalography ; Human ;
                   Magnetic Resonance Imaging ; Support, Non-U.S. Gov't ;
                   Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {S1388245700004569 [pii]},
  medline-da = {20001215},
  medline-dcom = {20010111},
  medline-edat = {2000/11/09 11:00},
  medline-fau = {Goldman, R I ; Stern, J M ; Engel, J Jr ; Cohen, M S},
  medline-gr = {R01 DA13054-01/DA/NIDA},
  medline-is = {1388-2457},
  medline-jid = {100883319},
  medline-lr = {20010323},
  medline-mhda = {2001/02/28 10:01},
  medline-own = {NLM},
  medline-pl = {NETHERLANDS},
  medline-pmid = {11068232},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Clin Neurophysiol 2000 Nov;111(11):1974-80.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11068232},
  year = 2000
}
@ARTICLE{GSE+02,
  author = {Goldman, R. I. and Stern, J. M. and Engel, Jr, J. and
                   Cohen, M. S.},
  title = {Simultaneous {EEG} and f{MRI} of the alpha rhythm},
  journal = {Neuroreport},
  volume = {13},
  number = {18},
  pages = {2487-2492},
  abstract = {The alpha rhythm in the EEG is 8-12 Hz activity
                   present when a subject is awake with eyes closed. In
                   this study, we used simultaneous EEG and fMRI to make
                   maps of regions whose MRI signal changed reliably with
                   modulation in posterior alpha activity. We scanned 11
                   subjects as they rested with eyes closed. We found that
                   increased alpha power was correlated with decreased MRI
                   signal in multiple regions of occipital, superior
                   temporal, inferior frontal, and cingulate cortex, and
                   with increased signal in the thalamus and insula. These
                   results are consistent with animal experiments and
                   point to the alpha rhythm as an index of cortical
                   inactivity that may be generated in part by the
                   thalamus. These results also may have important
                   implications for interpretation of resting baseline in
                   fMRI studies.},
  authoraddress = {Department of Neurology, UCLA School of Medicine, Los
                   Angeles, CA, USA.},
  keywords = {Adult ; *Alpha Rhythm ; Female ; Human ; *Magnetic
                   Resonance Imaging ; Male ; Occipital Lobe/*physiology ;
                   Parietal Lobe/*physiology ; Support, Non-U.S. Gov't ;
                   Support, U.S. Gov't, P.H.S. ; Thalamus/physiology},
  language = {eng},
  medline-aid = {10.1097/01.wnr.0000047685.08940.d0 [doi]},
  medline-da = {20021224},
  medline-dcom = {20030404},
  medline-edat = {2002/12/25 04:00},
  medline-fau = {Goldman, Robin I ; Stern, John M ; Engel, Jerome Jr ;
                   Cohen, Mark S},
  medline-gr = {R01 DA 13054-01/DA/NIDA},
  medline-is = {0959-4965},
  medline-jid = {9100935},
  medline-mhda = {2003/04/05 05:00},
  medline-own = {NLM},
  medline-pl = {England},
  medline-pmid = {12499854},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Neuroreport 2002 Dec 20;13(18):2487-92.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12499854},
  year = 2002
}
@ARTICLE{GdM+03b,
  author = {Goncalves, S. I. and de Munck, J. C. and Verbunt, J.
                   P. and Bijma, F. and Heethaar, R. M. and Lopes da
                   Silva, F.},
  title = {In vivo measurement of the brain and skull
                   resistivities using an {EIT}-based method and realistic
                   models for the head},
  journal = {IEEE Trans Biomed Eng},
  volume = {50},
  number = {6},
  pages = {754-767},
  abstract = {In vivo measurements of equivalent resistivities of
                   skull (rho(skull)) and brain (rho(brain)) are performed
                   for six subjects using an electric impedance tomography
                   (EIT)-based method and realistic models for the head.
                   The classical boundary element method (BEM) formulation
                   for EIT is very time consuming. However, the
                   application of the Sherman-Morrison formula reduces the
                   computation time by a factor of 5. Using an optimal
                   point distribution in the BEM model to optimize its
                   accuracy, decreasing systematic errors of numerical
                   origin, is important because cost functions are
                   shallow. Results demonstrate that rho(skull)/rho(brain)
                   is more likely to be within 20 and 50 rather than equal
                   to the commonly accepted value of 80. The variation in
                   rho(brain)(average = 301 omega x cm, SD = 13\%) and
                   rho(skull)(average = 12230 omega x cm, SD = 18\%) is
                   decreased by half, when compared with the results using
                   the sphere model, showing that the correction for
                   geometry errors is essential to obtain realistic
                   estimations. However, a factor of 2.4 may still exist
                   between values of rho(skull)/rho(brain) corresponding
                   to different subjects. Earlier results show the
                   necessity of calibrating rho(brain) and rho(skull) by
                   measuring them in vivo for each subject, in order to
                   decrease errors associated with the
                   electroencephalogram inverse problem. We show that the
                   proposed method is suited to this goal.},
  authoraddress = {MEG Centre-VU University Medical Centre, P.O. Box
                   7057, 1007 MB Amsterdam, The Netherlands.
                   s.goncalves@vumc.nl},
  keywords = {Adult ; Brain/*physiology ; Brain Mapping/methods ;
                   Comparative Study ; Computer Simulation ; Electric
                   Impedance/*diagnostic use ;
                   Electroencephalography/methods ; Female ;
                   Head/*physiology ; Human ; Male ; *Models, Biological ;
                   Reproducibility of Results ; Sensitivity and
                   Specificity ; Skull/*physiology ; Support, Non-U.S.
                   Gov't ; Tomography/methods},
  language = {eng},
  medline-da = {20030619},
  medline-dcom = {20030729},
  medline-edat = {2003/06/20 05:00},
  medline-fau = {Goncalves, Sonia I ; de Munck, Jan C ; Verbunt, Jeroen
                   P A ; Bijma, Fetsje ; Heethaar, Rob M ; Lopes da Silva,
                   Fernando},
  medline-is = {0018-9294},
  medline-jid = {0012737},
  medline-mhda = {2003/07/30 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12814242},
  medline-pst = {ppublish},
  medline-pt = {Evaluation Studies ; Journal Article ; Validation
                   Studies},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng 2003 Jun;50(6):754-67.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12814242},
  year = 2003
}
@ARTICLE{GdM+05,
  author = {Goncalves, S.I. and de Munck, J.C. and Pouwels, P.J.
                   and Schoonhoven, R. and Kuijer, J.P. and Maurits, N.M.
                   and Hoogduin, J.M. and Van Someren, E.J. and Heethaar,
                   R.M. and Lopes da Silva, F.H.},
  title = {Correlating the alpha rhythm to {BOLD} using
                   simultaneous {EEG}/f{MRI}: {I}nter-subject variability.},
  journal = {Neuroimage},
  abstract = {Simultaneous recording of
                   electroencephalogram/functional magnetic resonance
                   images (EEG/fMRI) was applied to identify blood
                   oxygenation level-dependent (BOLD) changes associated
                   with spontaneous variations of the alpha rhythm, which
                   is considered the hallmark of the brain resting state.
                   The analysis was focused on inter-subject variability
                   associated with the resting state. Data from 7 normal
                   subjects are presented. Confirming earlier findings,
                   three subjects showed a negative correlation between
                   the BOLD signal and the average power time series
                   within the alpha band (8-12 Hz) in extensive areas of
                   the occipital, parietal and frontal lobes. In small
                   thalamic areas, the BOLD signal was positively
                   correlated with the alpha power. For subjects 3 and 4,
                   who displayed two different states during the data
                   acquisition time, it was shown that the corresponding
                   correlation patterns were different, thus demonstrating
                   the state dependency of the results. In subject 5, the
                   changes in BOLD were observed mainly in the frontal and
                   temporal lobes. Subject 6 only showed positive
                   correlations, thus contradicting the negative BOLD
                   alpha power cortical correlations that were found in
                   most subjects. Results suggest that the resting state
                   varies over subjects and, sometimes, even within one
                   subject. As the resting state plays an important role
                   in many fMRI experiments, the inter-subject variability
                   of this state should be addressed when comparing fMRI
                   results from different subjects.},
  authoraddress = {VU University Medical Centre (Dpt. PMT), De Boelelaan
                   1117, 1081 HV, Amsterdam, The Netherlands; Institute of
                   Biophysics and Biomedical Engineering, 1749-016 Campo
                   Grande, Lisbon, Portugal.},
  language = {ENG},
  medline-aid = {S1053-8119(05)00707-X [pii] ;
                   10.1016/j.neuroimage.2005.09.062 [doi]},
  medline-da = {20051117},
  medline-dep = {20051111},
  medline-edat = {2005/11/18 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2005/11/18 09:00},
  medline-own = {NLM},
  medline-phst = {2004/12/10 [received] ; 2005/09/01 [revised] ;
                   2005/09/07 [accepted]},
  medline-pmid = {16290018},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2005 Nov 11;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16290018},
  year = 2005
}
@ARTICLE{GdPM+04,
  author = {Grave de Peralta Menendez, R. and Murray, M. M. and
                   Michel, C. M. and Martuzzi, R. and Gonzalez Andino, S.
                   L.},
  title = {Electrical neuroimaging based on biophysical
                   constraints},
  journal = {NeuroImage},
  volume = {21},
  number = {2},
  pages = {527-539},
  abstract = {This paper proposes and implements biophysical
                   constraints to select a unique solution to the
                   bioelectromagnetic inverse problem. It first shows that
                   the brain's electric fields and potentials are
                   predominantly due to ohmic currents. This serves to
                   reformulate the inverse problem in terms of a
                   restricted source model permitting noninvasive
                   estimations of Local Field Potentials (LFPs) in depth
                   from scalp-recorded data. Uniqueness in the solution is
                   achieved by a physically derived regularization
                   strategy that imposes a spatial structure on the
                   solution based upon the physical laws that describe
                   electromagnetic fields in biological media. The
                   regularization strategy and the source model emulate
                   the properties of brain activity's actual generators.
                   This added information is independent of both the
                   recorded data and head model and suffices for obtaining
                   a unique solution compatible with and aimed at
                   analyzing experimental data. The inverse solution's
                   features are evaluated with event-related potentials
                   (ERPs) from a healthy subject performing a visuo-motor
                   task. Two aspects are addressed: the concordance
                   between available neurophysiological evidence and
                   inverse solution results, and the functional
                   localization provided by fMRI data from the same
                   subject under identical experimental conditions. The
                   localization results are spatially and temporally
                   concordant with experimental evidence, and the areas
                   detected as functionally activated in both imaging
                   modalities are similar, providing indices of
                   localization accuracy. We conclude that biophysically
                   driven inverse solutions offer a novel and reliable
                   possibility for studying brain function with the
                   temporal resolution required to advance our
                   understanding of the brain's functional networks.},
  authoraddress = {Functional Brain Mapping Laboratory, Neurology
                   Department, University Hospital of Geneva, 1211 Geneva,
                   Switzerland. Rolando.Grave@hcuge.ch},
  keywords = {Biophysics/*methods ; Brain Mapping/*methods ;
                   Cerebral Cortex/*physiology ; Dominance,
                   Cerebral/physiology ; Electroencephalography/*methods ;
                   Evoked Potentials/physiology ; Human ; Image
                   Processing, Computer-Assisted/*methods ; Imaging,
                   Three-Dimensional/*methods ; Linear Models ;
                   *Mathematical Computing ; *Models, Neurological ; Motor
                   Cortex/physiology ; Nerve Net/physiology ; Psychomotor
                   Performance/*physiology ; Reaction Time/physiology ;
                   Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.09.051 [doi] ;
                   S1053811903006013 [pii]},
  medline-da = {20040224},
  medline-dcom = {20040504},
  medline-edat = {2004/02/26 05:00},
  medline-fau = {Grave de Peralta Menendez, Rolando ; Murray, Micah M ;
                   Michel, Christoph M ; Martuzzi, Roberto ; Gonzalez
                   Andino, Sara L},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/05/05 05:00},
  medline-own = {NLM},
  medline-phst = {2003/05/06 [received] ; 2003/09/25 [revised] ;
                   2003/09/26 [accepted]},
  medline-pl = {United States},
  medline-pmid = {14980555},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Feb;21(2):527-39.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=14980555},
  year = 2004
}
@ARTICLE{Glo99,
  author = {Glover, G. H.},
  title = {Deconvolution of impulse response in event-related
                   {BOLD} f{MRI}.},
  journal = {NeuroImage},
  volume = {9},
  number = {4},
  pages = {416-429},
  abstract = {The temporal characteristics of the BOLD response in
                   sensorimotor and auditory cortices were measured in
                   subjects performing finger tapping while listening to
                   metronome pacing tones. A repeated trial paradigm was
                   used with stimulus durations of 167 ms to 16 s and
                   intertrial times of 30 s. Both cortical systems were
                   found to be nonlinear in that the response to a long
                   stimulus could not be predicted by convolving the 1-s
                   response with a rectangular function. In the short-time
                   regime, the amplitude of the response varied only
                   slowly with stimulus duration. It was found that this
                   character was predicted with a modification to Buxton's
                   balloon model. Wiener deconvolution was used to deblur
                   the response to concatenated short episodes of finger
                   tapping at different temporal separations and at rates
                   from 1 to 4 Hz. While the measured response curves were
                   distorted by overlap between the individual episodes,
                   the deconvolved response at each rate was found to
                   agree well with separate scans at each of the
                   individual rates. Thus, although the impulse response
                   cannot predict the response to fully overlapping
                   stimuli, linear deconvolution is effective when the
                   stimuli are separated by at least 4 s. The
                   deconvolution filter must be measured for each subject
                   using a short-stimulus paradigm. It is concluded that
                   deconvolution may be effective in diminishing the
                   hemodynamically imposed temporal blurring and may have
                   potential applications in quantitating responses in
                   eventrelated fMRI.},
  authoraddress = {Center for Advanced MR Technology at Stanford,
                   Department of Diagnostic Radiology, Stanford,
                   California, 94305-5488, USA.},
  keywords = {Acoustic Stimulation ; Auditory Cortex/*physiology ;
                   Data Interpretation, Statistical ; Evoked Potentials,
                   Auditory/*physiology ; Human ; Image Processing,
                   Computer-Assisted ; Magnetic Resonance Imaging/*methods
                   ; Nonlinear Dynamics ; Oxygen/*blood ; Somatosensory
                   Cortex/*physiology ; Support, Non-U.S. Gov't ; Support,
                   U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {S1053811998904190 [pii]},
  medline-ci = {Copyright 1999 Academic Press.},
  medline-da = {19990525},
  medline-dcom = {19990525},
  medline-edat = {1999/04/07},
  medline-fau = {Glover, G H},
  medline-gr = {P41 RR 09784/RR/NCRR},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20001218},
  medline-mhda = {1999/04/07 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10191170},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {NeuroImage 1999 Apr;9(4):416-29.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10191170},
  year = 1999
}
@ARTICLE{Gre93,
  author = {Greenblatt, R. E.},
  title = {Probabilistic reconstruction of multiple sources in
                   the bioelectromagnetic inverse problem},
  journal = {Inverse Problems},
  volume = {9},
  number = {2},
  pages = {271-284},
  abstract = {A probabilistic multiple source solution for the
                   bioelectromagnetic inverse problem is described. The
                   model-dependent solution assumes a finite number of
                   discrete primary sources at fixed locations within a
                   bounded conductor. Covariance statistics derived from a
                   set of detectors outside the conducting region are used
                   to determine a metric on the space of possible sources.
                   This metric function is used to construct a weighted
                   pseudo-inverse matrix, which, in turn, may be used to
                   estimate the spatio-temporal distribution of source
                   activity. The results are embodied in the form of the
                   PROMS (probabilistic reconstruction of (multiple
                   sources) algorithm. Computer simulations using the
                   algorithm are described. These methods are compared
                   with other algorithms, including minimum norm
                   estimation, and the MUSIC and spatial filtering
                   algorithms.},
  year = 1993
}
@ARTICLE{HB03,
  author = {Hillebrand, A. and Barnes, G. R.},
  title = {The use of anatomical constraints with {MEG}
                   beamformers},
  journal = {NeuroImage},
  volume = {20},
  number = {4},
  pages = {2302-2313},
  abstract = {Synthetic Aperture Magnetometry (SAM) is a beamformer
                   approach for the localisation of neuronal activity from
                   EEG/MEG data. SAM estimates the optimum orientation of
                   each source in a predefined source space by a nonlinear
                   search for the orientation that maximises the
                   beamformer output. However, MEG is most sensitive to
                   cortical sources and these sources are generally
                   oriented perpendicular to the surface. The
                   reconstructed neuronal activity can therefore
                   reasonably be constrained to the cortical surface,
                   orientated perpendicular to it, therefore removing the
                   search for the optimum orientation for the computation
                   of the beamformer weights. This paper sets out to
                   compare the performance of a constrained and
                   unconstrained beamformer (SAM), with respect to the
                   localisation accuracy of the source reconstructions and
                   the spatial resolution. Fifty sources were randomly
                   placed on a cortical surface estimated from an MRI, and
                   we simulated data over a range of different
                   signal-to-noise ratios (SNRs) for each source. These
                   datasets were analysed using both an unconstrained
                   beamformer (SAM) and a constrained beamformer (with the
                   sources orientated perpendicular to the cortical
                   surface). The influence of errors in the estimation of
                   the surface location and surface normals on the
                   performance of the constrained beamformer, representing
                   MEG/MRI coregistration and segmentation errors, were
                   also examined. The spatial resolution of the beamformer
                   improves, typically by a factor of four by applying
                   anatomical constraints, and the localisation accuracy
                   improves marginally. However, the advantage in spatial
                   resolution disappears when errors are introduced into
                   the orientation and location constraints, and,
                   moreover, the localisation accuracy of the inaccurately
                   constrained beamformer degrades rapidly. We conclude
                   that the use of anatomical constraints is only
                   advantageous if the MEG/MRI coregistration error is
                   smaller than 2 mm and the error in the estimation of
                   the cortical surface orientation is smaller than 10
                   degrees.},
  authoraddress = {The Wellcome Trust Laboratory for MEG Studies,
                   Neurosciences Research Institute, Aston University,
                   Birmingham, UK. hillebra@aston.ac.uk},
  keywords = {Algorithms ; Brain/*anatomy & histology ; Computer
                   Simulation ; Human ; Image Interpretation,
                   Computer-Assisted ; Magnetic Resonance Imaging ;
                   Magnetoencephalography/*instrumentation ; Nonlinear
                   Dynamics ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1053811903004610 [pii]},
  medline-da = {20031219},
  medline-dcom = {20040212},
  medline-edat = {2003/12/20 05:00},
  medline-fau = {Hillebrand, Arjan ; Barnes, Gareth R},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/02/13 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {14683731},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2003 Dec;20(4):2302-13.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=14683731},
  year = 2003
}
@ARTICLE{HBM+95,
  author = {Huang-Hellinger, F. R. and Breiter, H. C. and
                   McCormack, G. and Cohen, M. S. and Kwong, K. K. and
                   Sutton, J. P. and Savoy, R. L. and Weisskoff, R. M. and
                   Davis, T. L. and Baker, J. R. and Belliveau, J. W. and
                   Rosen, B. R.},
  title = {Simultaneous functional magnetic resonance imaging and
                   electrophysiological recording},
  journal = {Hum Brain Mapp},
  volume = {3},
  pages = {13-25},
  abstract = {The purpose of this study was to develop a method for
                   obtaining simultaneous electrophysiological and
                   functional magnetic resonance imaging data. Using
                   phantom experiments and tests on several of the
                   investigators, a method for obtaining simultaneous
                   electrophysiological and fMRI data was developed and
                   then tested in three volunteers including two task
                   activation experiments. It was then applied in a sleep
                   experiment (n = 12). Current limiting resistance and
                   low-pass filtering were added to the
                   electrophysiological circuit. Potential high frequency
                   current loops were avoided in the electrical layout
                   near the subject. MRI was performed at 1.5 T using
                   conventional and echo planar imaging sequences. There
                   was no evidence of subject injury. Expected
                   correlations were observed between the
                   electrophysiological and fMRI data in the task
                   activation experiments. The fMRI data were not
                   significantly degraded by the electrophysiological
                   apparatus. Alpha waves were detected from within the
                   magnet in seven of the 15 experimental sessions. There
                   was degradation of the electrophysiological data due to
                   ballistocardiographic artifacts (pulsatile whole body
                   motion time-locked to cardiac activity) which varied
                   between subjects from being minimal to becoming large
                   enough to make detection of alpha waves difficult. We
                   conduded that simultaneous fMRI and
                   electrophysiological recording is possible with minor
                   modifications of standard electrophysiological
                   equipment. Our initial results suggest this can be done
                   safely and without compromise of the fMRI data. The
                   usefulness of this technique for studies of such things
                   as sleep and epilepsy is promising. Applications
                   requiring higher precision electrophysiological data,
                   such as evoked response measurements, may require
                   modifications based on ballistocardiographic effects.},
  year = 1995
}
@ARTICLE{HCH+95,
  author = {Hill, R. A. and Chiappa, K. H. and Huang-Hellinger, F.
                   and Jenkins, B. G.},
  title = {E{EG} during {MR} imaging: differentiation of movement
                   artifact from paroxysmal cortical activity},
  journal = {Neurology},
  volume = {45},
  number = {10},
  pages = {1942-1943},
  authoraddress = {Department of Neurology, Massachusetts General
                   Hospital, Boston 02114, USA.},
  keywords = {Artifacts ; Brain/*physiology ; Echo-Planar Imaging ;
                   Electroencephalography/*methods ; Human ; Magnetic
                   Resonance Imaging ; Movement/*physiology},
  language = {eng},
  medline-da = {19951201},
  medline-dcom = {19951201},
  medline-edat = {1995/10/01},
  medline-fau = {Hill, R A ; Chiappa, K H ; Huang-Hellinger, F ;
                   Jenkins, B G},
  medline-is = {0028-3878},
  medline-jid = {0401060},
  medline-lr = {20001218},
  medline-mhda = {1995/10/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {7478002},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {AIM ; IM},
  medline-so = {Neurology 1995 Oct;45(10):1942-3.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=7478002},
  year = 1995
}
@ARTICLE{HD07,
  author = {Herrmann, C. S. and Debener, S.},
  title = {Simultaneous recording of {EEG} and {BOLD} responses:
                   {A} historical perspective.},
  journal = {Int J Psychophysiol},
  abstract = {Electromagnetic fields as measured with
                   electroencephalogram (EEG) are a direct consequence of
                   neuronal activity and feature the same timescale as the
                   underlying cognitive processes, while hemodynamic
                   signals as measured with functional magnetic resonance
                   imaging (fMRI) are related to the energy consumption of
                   neuronal populations. It is obvious that a combination
                   of both techniques is a very attractive aim in
                   neuroscience, in order to achieve both high temporal
                   and spatial resolution for the non-invasive study of
                   cognitive brain function. During the last decade a
                   number of research groups have taken up this challenge.
                   Here, we review the development of the combined
                   EEG-fMRI approach. We summarize the main data
                   integration approaches developed to achieve such a
                   combination, discuss the current state-of-the-art in
                   this field and outline challenges for the future
                   success of this promising approach.},
  authoraddress = {Department of Biological Psychology,
                   Otto-von-Guericke-University of Magdeburg, P.O. Box
                   4120, 39016 Magdeburg, Germany.},
  language = {ENG},
  medline-aid = {S0167-8760(07)00155-9 [pii] ;
                   10.1016/j.ijpsycho.2007.06.006 [doi]},
  medline-da = {20070827},
  medline-dep = {20070710},
  medline-edat = {2007/08/28 09:00},
  medline-is = {0167-8760 (Print)},
  medline-jid = {8406214},
  medline-mhda = {2007/08/28 09:00},
  medline-own = {NLM},
  medline-phst = {2007/05/22 [received] ; 2007/06/20 [accepted]},
  medline-pmid = {17719112},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Int J Psychophysiol. 2007 Jul 10;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17719112},
  year = 2007
}
@ARTICLE{HFT00,
  author = {Horwitz, B. and Friston, K. J. and Taylor, J. G.},
  title = {Neural modeling and functional brain imaging: an
                   overview},
  journal = {Neural Netw},
  volume = {13},
  number = {8-9},
  pages = {829-846},
  abstract = {This article gives an overview of the different
                   functional brain imaging methods, the kinds of
                   questions these methods try to address and some of the
                   questions associated with functional neuroimaging data
                   for which neural modeling must be employed to provide
                   reasonable answers.},
  authoraddress = {Language Section, National Institute on Deafness and
                   Other Communication Disorders, National Institutes of
                   Health, Bethesda, MD, USA. horwitz@helix.nih.gov},
  keywords = {Brain/metabolism/*physiology ; *Brain Mapping/methods
                   ; Cerebrovascular Circulation ; Cognition/*physiology ;
                   Hemodynamic Processes ; Human ; Magnetic Resonance
                   Imaging ; Nerve Net ; Neurons/physiology ; Tomography,
                   Emission-Computed ; Tomography, Emission-Computed,
                   Single-Photon},
  language = {eng},
  medline-da = {20010111},
  medline-dcom = {20010315},
  medline-edat = {2001/01/13 11:00},
  medline-fau = {Horwitz, B ; Friston, K J ; Taylor, J G},
  medline-is = {0893-6080},
  medline-jid = {8805018},
  medline-lr = {20031114},
  medline-mhda = {2001/03/17 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11156195},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Academic},
  medline-rf = {153},
  medline-sb = {IM},
  medline-so = {Neural Netw 2000 Oct-Nov;13(8-9):829-46.},
  medline-stat = {completed},
  year = 2000
}
@ARTICLE{HHD+06,
  author = {Huppert, T. J. and Hoge, R. D. and Diamond, S. G. and
                   Franceschini, M. A. and Boas, D. A.},
  title = {A temporal comparison of {BOLD}, {ASL}, and {NIRS}
                   hemodynamic responses to motor stimuli in adult humans.},
  journal = {Neuroimage},
  volume = {29},
  number = {2},
  pages = {368-82},
  abstract = {In this study, we have preformed simultaneous
                   near-infrared spectroscopy (NIRS) along with BOLD
                   (blood oxygen level dependent) and ASL (arterial spin
                   labeling)-based fMRI during an event-related motor
                   activity in human subjects in order to compare the
                   temporal dynamics of the hemodynamic responses recorded
                   in each method. These measurements have allowed us to
                   examine the validity of the biophysical models
                   underlying each modality and, as a result, gain greater
                   insight into the hemodynamic responses to neuronal
                   activation. Although prior studies have examined the
                   relationships between these two methodologies through
                   similar experiments, they have produced conflicting
                   results in the literature for a variety of reasons.
                   Here, by employing a short-duration, event-related
                   motor task, we have been able to emphasize the subtle
                   temporal differences between the hemodynamic parameters
                   with a high contrast-to-noise ratio. As a result of
                   this improved experimental design, we are able to
                   report that the fMRI measured BOLD response is more
                   correlated with the NIRS measure of deoxy-hemoglobin (R
                   = 0.98; P < 10(-20)) than with oxy-hemoglobin (R =
                   0.71), or total hemoglobin (R = 0.53). This result was
                   predicted from the theoretical grounds of the BOLD
                   response and is in agreement with several previous
                   works [Toronov, V.A.W., Choi, J.H., Wolf, M., Michalos,
                   A., Gratton, E., Hueber, D., 2001. "Investigation of
                   human brain hemodynamics by simultaneous near-infrared
                   spectroscopy and functional magnetic resonance
                   imaging." Med. Phys. 28 (4) 521-527.; MacIntosh, B.J.,
                   Klassen, L.M., Menon, R.S., 2003. "Transient
                   hemodynamics during a breath hold challenge in a two
                   part functional imaging study with simultaneous
                   near-infrared spectroscopy in adult humans". NeuroImage
                   20 1246-1252.; Toronov, V.A.W., Walker, S., Gupta, R.,
                   Choi, J.H., Gratton, E., Hueber, D., Webb, A., 2003.
                   "The roles of changes in deoxyhemoglobin concentration
                   and regional cerebral blood volume in the fMRI BOLD
                   signal" Neuroimage 19 (4) 1521-1531]. These data have
                   also allowed us to examine more detailed measurement
                   models of the fMRI signal and comment on the roles of
                   the oxygen saturation and blood volume contributions to
                   the BOLD response. In addition, we found high
                   correlation between the NIRS measured total hemoglobin
                   and ASL measured cerebral blood flow (R = 0.91; P <
                   10(-10)) and oxy-hemoglobin with flow (R = 0.83; P <
                   10(-05)) as predicted by the biophysical models.
                   Finally, we note a significant amount of
                   cross-modality, correlated, inter-subject variability
                   in amplitude change and time-to-peak of the hemodynamic
                   response. The observed co-variance in these parameters
                   between subjects is in agreement with hemodynamic
                   models and provides further support that fMRI and NIRS
                   have similar vascular sensitivity.},
  authoraddress = {Harvard Medical School- Graduate Program in
                   Biophysics, Massachusetts General Hospital,
                   Charlestown, MA 02129, USA.
                   thuppert@nmr.mgh.harvard.edu},
  keywords = {Adult ; Biological Markers ; Brain
                   Chemistry/physiology ; Cerebral Arteries/anatomy &
                   histology/*physiology ; Cerebrovascular
                   Circulation/*physiology ; Comparative Study ; *Electron
                   Spin Resonance Spectroscopy ; Female ;
                   Fingers/physiology ; Humans ; *Magnetic Resonance
                   Imaging ; Male ; Middle Aged ; Movement/*physiology ;
                   Oxygen/*blood ; Reproducibility of Results ; Research
                   Support, N.I.H., Extramural ; Research Support,
                   Non-U.S. Gov't ; *Spectroscopy, Near-Infrared ; Vitamin
                   E/metabolism ; Vitamins/metabolism},
  language = {eng},
  medline-aid = {S1053-8119(05)00582-3 [pii] ;
                   10.1016/j.neuroimage.2005.08.065 [doi]},
  medline-da = {20060113},
  medline-dcom = {20060321},
  medline-dep = {20051121},
  medline-edat = {2005/11/24 09:00},
  medline-fau = {Huppert, T J ; Hoge, R D ; Diamond, S G ;
                   Franceschini, M A ; Boas, D A},
  medline-gr = {P41-RR14075/RR/NCRR ; R01-EB001954/EB/NIBIB ;
                   R01-EB002482/EB/NIBIB},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2006/03/22 09:00},
  medline-own = {NLM},
  medline-phst = {2004/11/15 [received] ; 2005/07/24 [revised] ;
                   2005/08/01 [accepted] ; 2005/11/21 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16303317},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-pubm = {Print-Electronic},
  medline-rn = {0 (Biological Markers) ; 0 (Vitamins) ; 1406-18-4
                   (Vitamin E) ; 7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 Jan 15;29(2):368-82. Epub 2005 Nov
                   21.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16303317},
  year = 2006
}
@INBOOK{HHP05,
  author = {Y. O. Halchenko and S. J. Hanson and
                  B. A. Pearlmutter},
  title = {Multimodal Integration: {fMRI}, {MRI}, {EEG}, {MEG}},
  chapter = 8,
  keywords = {EEG, MEG, fMRI, MRI, multimodal analysis, fusion},
  booktitle = {Advanced Image Processing in Magnetic Resonance
                  Imaging},
  editor = {L. Landini and M. F. Santarelli and V. Positano},
  publisher = {Dekker},
  isbn = {0824725425},
  series = {Signal Processing and Communications},
  year = 2005,
  abstract = {This chapter provides a comprehensive survey of the
                  motivations, assumptions and pitfalls associated
                  with combining signals such as fMRI with EEG or
                  MEG. Our initial focus in the chapter concerns
                  mathematical approaches for solving the localization
                  problem in EEG and MEG. Next we document the most
                  recent and promising ways in which these signals can
                  be combined with fMRI. Specifically, we look at
                  correlative analysis, decomposition techniques,
                  equivalent dipole fitting, distributed sources
                  modeling, beamforming, and Bayesian methods. Due to
                  difficulties in assessing ground truth of a combined
                  signal in any realistic experiment---a difficulty
                  further confounded by lack of accurate biophysical
                  models of BOLD signal---we are cautious to be
                  optimistic about multimodal
                  integration. Nonetheless, as we highlight and
                  explore the technical and methodological
                  difficulties of fusing heterogeneous signals, it
                  seems likely that correct fusion of multimodal data
                  will allow previously inaccessible spatiotemporal
                  structures to be visualized and formalized and thus
                  eventually become a useful tool in brain imaging
                  research.},
  pages = {223--265},
  url-pdf = {http://www.onerussian.com/Sci/fusion/fusion-chapter/HHP05.pdf},
  urldate = {2005-10-07}
}
@ARTICLE{HHW03,
  author = {Hu, J. and Hu, J. and Wang, Y.},
  title = {{A}pplication of weighted minimum-norm estimation with
                   {T}ikhonov regularization for neuromagnetic source
                   imaging},
  journal = {Sheng Wu Yi Xue Gong Cheng Xue Za Zhi},
  volume = {20},
  number = {1},
  pages = {157-161},
  abstract = {In magnetoencepholography(MEG) inverse research,
                   according to the point source model and distributed
                   source model, the neuromagnetic source reconstruction
                   methods are classified as parametric current dipole
                   localization and nonparametric source imaging (or
                   current density reconstruction). MEG source imaging
                   technique can be formulated as an inherent ill-posed
                   and highly underdetermined linear inverse problem. In
                   order to yield a robust and plausible neural current
                   distribution image, various approaches have been
                   proposed. Among those, the weighted minimum-norm
                   estimation with Tikhonov regularization is a popular
                   technique. The authors present a relatively overall
                   theoretical framework Followed by a discussion of the
                   development, several regularized minimum-norm
                   algorithms have been described in detail, including the
                   depth normalization, low resolution electromagnetic
                   tomography(LORETA), focal underdetermined system
                   solver(FOCUSS), selective minimum-norm(SMN). In
                   addition, some other imaging methods, e.g., maximum
                   entropy method(MEM), the method incorporating other
                   brain functional information such as fMRI data and
                   maximum a posteriori(MAP) method using Markov random
                   field model, are explained as well. From the
                   generalized point of view based on minimum-norm
                   estimation with Tikhonov regularization, all these
                   algorithms are aiming to resolve the tradeoff between
                   fidelity to the measured data and the constraints
                   assumptions about the neural source configuration such
                   as anatomical and physiological information. In
                   conclusion, almost all the source imaging approaches
                   can be consistent with the regularized minimum-norm
                   estimation to some extent.},
  authoraddress = {College of Information Engineering, Zhejiang
                   University of Technology, Hangzhou 310014.},
  keywords = {*Algorithms ; Bayes Theorem ; English Abstract ; Image
                   Processing, Computer-Assisted/*methods ;
                   *Magnetoencephalography ; Models, Statistical ;
                   Nonlinear Dynamics ; Support, Non-U.S. Gov't},
  language = {chi},
  medline-da = {20030514},
  medline-dcom = {20030826},
  medline-edat = {2003/05/15 05:00},
  medline-fau = {Hu, Jing ; Hu, Jie ; Wang, Yuanmei},
  medline-is = {1001-5515},
  medline-jid = {9426398},
  medline-mhda = {2003/08/27 05:00},
  medline-own = {NLM},
  medline-pl = {China},
  medline-pmid = {12744189},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {22},
  medline-sb = {IM},
  medline-so = {Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 2003
                   Mar;20(1):157-61.},
  medline-stat = {completed},
  year = 2003
}
@ARTICLE{HM01,
  author = {Huettel, S. A. and McCarthy, G.},
  title = {Regional differences in the refractory period of the
                   hemodynamic response: an event-related f{MRI} study.},
  journal = {NeuroImage},
  volume = {14},
  number = {5},
  pages = {967-976},
  abstract = {We investigated the characteristics of the hemodynamic
                   response (HDR) to paired presentations of visual face
                   stimuli using functional magnetic resonance imaging
                   (fMRI). Photographs of faces were presented singly or
                   in pairs with either a 1-s or 6-s intrapair interval
                   (IPI). Each trial (single face or face pairs) was
                   followed by an intertrial interval of 16-20 s. Faces
                   were presented at fixation and passively viewed by the
                   10 subjects. Images were acquired at 1.5 Tesla using a
                   gradient-echo echo-planar imaging sequence sensitive to
                   blood-oxygenation-level-dependent (BOLD) contrast. To
                   examine the refractory properties of the HDR, we
                   subtracted the single-stimulus hemodynamic response
                   from the composite response evoked by face pairs for
                   all voxels significantly active on single face trials.
                   The residual represents the contribution of the second
                   stimulus to the fMRI signal. Event-related presentation
                   of faces evoked activity in medial calcarine cortex and
                   the fusiform gyrus bilaterally. In both calcarine and
                   fusiform regions, the hemodynamic response to the
                   second face in a pair was of lower amplitude and of
                   increased latency at 1 s IPI, with significant recovery
                   of both amplitude and latency toward single-stimulus
                   values at 6 s IPI. At 1 s IPI, significantly greater
                   recovery was found in posterior fusiform regions
                   (50-60\%) than in midfusiform regions (10-40\%). These
                   regional differences were not apparent at 6 s IPI. No
                   differences were found across slices in calcarine
                   cortex. There was a significant difference in mean
                   latency to HDR peak between calcarine and fusiform
                   cortex, with the HDR peaking about 400 ms earlier in
                   calcarine cortex. We conclude that characteristics of
                   the HDR, notably its amplitude, latency, and refractory
                   properties, differ across visual cortical areas.},
  authoraddress = {Brain Imaging and Analysis Center, Duke University,
                   Durham, North Carolina 27710, USA.},
  keywords = {Adult ; Arousal/*physiology ; Attention/*physiology ;
                   Brain Mapping ; Echo-Planar Imaging ; Evoked
                   Potentials, Visual/physiology ; Face ; Female ;
                   Hemodynamic Processes/*physiology ; Human ; Image
                   Enhancement ; *Magnetic Resonance Imaging ; Male ;
                   Oxygen Consumption/physiology ; Pattern Recognition,
                   Visual/*physiology ; Reaction Time ; Refractory Period,
                   Neurologic/*physiology ; Regional Blood Flow/physiology
                   ; Support, U.S. Gov't, Non-P.H.S. ; Support, U.S.
                   Gov't, P.H.S. ; Visual Cortex/*blood supply},
  language = {eng},
  medline-aid = {10.1006/nimg.2001.0900 [doi] ; S1053811901909000 [pii]},
  medline-ci = {Copyright 2001 Academic Press.},
  medline-da = {20011107},
  medline-dcom = {20020102},
  medline-edat = {2001/11/08 10:00},
  medline-fau = {Huettel, S A ; McCarthy, G},
  medline-gr = {MH-05286/MH/NIMH ; MH12541/MH/NIMH},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {2002/01/05 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11697929},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2001 Nov;14(5):967-76.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11697929},
  year = 2001
}
@ARTICLE{HM03,
  author = {Harms, M. P. and Melcher, J. R.},
  title = {Detection and quantification of a wide range of f{MRI}
                   temporal responses using a physiologically-motivated
                   basis set.},
  journal = {Hum Brain Mapp},
  volume = {20},
  number = {3},
  pages = {168-83},
  abstract = {The temporal dynamics of fMRI responses can span a
                   broad range, indicating a rich underlying physiology,
                   but also posing a significant challenge for detection.
                   For instance, in human auditory cortex, prolonged sound
                   stimuli ( approximately 30 sec) can evoke responses
                   ranging from sustained to highly phasic (i.e.,
                   characterized by prominent peaks just after sound onset
                   and offset). In the present study, we developed a
                   method capable of detecting a wide variety of
                   responses, while simultaneously extracting information
                   about individual response components, which may have
                   different neurophysiological underpinnings.
                   Specifically, we implemented the general linear model
                   using a novel set of basis functions chosen to reflect
                   temporal features of cortical fMRI responses. This
                   physiologically-motivated basis set (the "OSORU" basis
                   set) was tested against (1) the commonly employed
                   "sustained-only" basis "set" (i.e., a single smoothed
                   "boxcar" function), and (2) a sinusoidal basis set,
                   which is capable of detecting a broad range of
                   responses, but lacks a direct relationship to
                   individual response components. On data that included
                   many different temporal responses, the OSORU basis set
                   performed far better overall than the sustained-only
                   set, and as well or better than the sinusoidal basis
                   set. The OSORU basis set also proved effective in
                   exploring brain physiology. As an example, we
                   demonstrate that the OSORU basis functions can be used
                   to spatially map the relative amount of transient vs.
                   sustained activity within auditory cortex. The OSORU
                   basis set provides a powerful means for response
                   detection and quantification that should be broadly
                   applicable to any brain system and to both human and
                   non-human species.},
  authoraddress = {Eaton-Peabody Laboratory, Massachusetts Eye and Ear
                   Infirmary, Boston and Harvard-MIT Division of Health
                   Sciences and Technology, Hearing Bioscience and
                   Technology Program, Cambridge, Massachusetts, USA.
                   mharms@epl.meei.harvard.edu},
  keywords = {Acoustic Stimulation ; Auditory Cortex/*physiology ;
                   Brain Mapping ; Cerebral Cortex/physiology ; Evoked
                   Potentials, Auditory ; Humans ; Linear Models ;
                   Magnetic Resonance Imaging/*methods ; Research Support,
                   Non-U.S. Gov't ; Time Factors},
  language = {eng},
  medline-aid = {10.1002/hbm.10136 [doi]},
  medline-ci = {Copyright 2003 Wiley-Liss, Inc.},
  medline-da = {20031105},
  medline-dcom = {20040109},
  medline-edat = {2003/11/06 05:00},
  medline-fau = {Harms, Michael P ; Melcher, Jennifer R},
  medline-is = {1065-9471 (Print)},
  medline-jid = {9419065},
  medline-jt = {Human brain mapping.},
  medline-lr = {20041117},
  medline-mhda = {2004/01/10 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {14601143},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp. 2003 Nov;20(3):168-83.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=14601143},
  year = 2003
}
@ARTICLE{HNS+01,
  author = {Hansen, L. K. and Nielsen, F. A. and Strother, S. C.
                   and Lange, N.},
  title = {Consensus inference in neuroimaging.},
  journal = {Neuroimage},
  volume = {13},
  number = {6 Pt 1},
  pages = {1212-8},
  abstract = {We introduce model averaging in neuroimaging. We show
                   that model summary images can be directly compared and
                   averaged after histogram equalization. We demonstrate
                   that averaging enhances the ROC curve in a simulation
                   study. The averaging procedure is applied to a fMRI
                   study of motor cortex.},
  authoraddress = {Informatics and Mathematical Modelling, Technical
                   University of Denmark, DK-2800 Lyngby, Denmark.},
  keywords = {Brain Mapping ; Echo-Planar Imaging ;
                   Fingers/innervation ; Humans ; *Image Enhancement ;
                   *Image Processing, Computer-Assisted ; *Magnetic
                   Resonance Imaging ; Models, Statistical ; Motor
                   Activity/physiology ; Motor Cortex/*physiology ; Nerve
                   Net/physiology ; Research Support, Non-U.S. Gov't ;
                   Research Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {10.1006/nimg.2000.0718 [doi] ; S1053811900907183 [pii]},
  medline-ci = {Copyright 2001 Academic Press.},
  medline-da = {20010515},
  medline-dcom = {20010726},
  medline-edat = {2001/05/16 10:00},
  medline-fau = {Hansen, L K ; Nielsen , F A ; Strother, S C ; Lange, N},
  medline-gr = {NS34183/NS/NINDS ; P20 MH57180/MH/NIMH},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-lr = {20041117},
  medline-mhda = {2001/07/28 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11352627},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2001 Jun;13(6 Pt 1):1212-8.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11352627},
  year = 2001
}
@ARTICLE{HOG+98,
  author = {Huppertz, H. J. and Otte, M. and Grimm, C. and
                   Kristeva-Feige, R. and Mergner, T. and Lucking, C. H.},
  title = {Estimation of the accuracy of a surface matching
                   technique for registration of {EEG} and {MRI} data},
  journal = {Electroencephalogr Clin Neurophysiol},
  volume = {106},
  number = {5},
  pages = {409-415},
  abstract = {OBJECTIVES: We developed a method to register EEG and
                   MRI data used for the source reconstruction of electric
                   brain activity. METHODS: The method is based on
                   matching of the head surfaces as obtained by 3D
                   scanning after the EEG recording, and by segmentation
                   of MRI data. The registration accuracy was estimated by
                   calculating the residual error of the surface matching
                   and its intra-individual and inter-individual
                   variability. In addition, the test-retest reliability
                   concerning the transformation of electrode positions
                   was studied, to estimate how inaccuracies resulting
                   from the 3D scanning of the head surface translate into
                   registration uncertainty. RESULTS: For 61 measurements,
                   performed on 20 subjects, the average root mean square
                   of the Euclidean distances between the 3D-scanned and
                   the MRI-derived head surfaces amounted to 3.4 mm. An
                   inter-individual standard deviation of 0.24 mm, and an
                   intraindividual standard deviation of 0.003-0.31 mm
                   proved a high inter- and intra-subject stability of the
                   surface matching technique. The variation of
                   transformation results when studying the test-retest
                   reliability amounted to 1.6 mm on average. The maximum
                   error of transformation was smaller than the diameter
                   of the electrodes. CONCLUSIONS: The findings suggest
                   that the surface matching technique is a precise method
                   for determination of the transformation of electrode
                   positions and MRI data into a single co-ordinate system
                   and can successfully be used in a routine laboratory
                   setting.},
  authoraddress = {Department of Neurology, University of Freiburg,
                   Germany. huppertz@nz11.ukl.uni-freiburg.de},
  keywords = {Brain/anatomy & histology/physiology ;
                   *Electroencephalography ; Head/anatomy & histology ;
                   Human ; Image Processing, Computer-Assisted/*methods ;
                   *Magnetic Resonance Imaging ; Reproducibility of
                   Results},
  language = {eng},
  medline-aid = {S0013469498000212 [pii]},
  medline-da = {19980813},
  medline-dcom = {19980813},
  medline-edat = {1998/07/29},
  medline-fau = {Huppertz, H J ; Otte, M ; Grimm, C ; Kristeva-Feige, R
                   ; Mergner, T ; Lucking, C H},
  medline-is = {0013-4694},
  medline-jid = {0375035},
  medline-lr = {20001218},
  medline-mhda = {1998/07/29 00:01},
  medline-own = {NLM},
  medline-pl = {IRELAND},
  medline-pmid = {9680153},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Electroencephalogr Clin Neurophysiol 1998
                   May;106(5):409-15.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9680153},
  year = 1998
}
@ARTICLE{HP02,
  author = {Horwitz, B. and Poeppel, D.},
  title = {How can {EEG}/{MEG} and f{MRI}/{PET} data be combined?},
  journal = {Hum Brain Mapp},
  volume = {17},
  number = {1},
  pages = {1-3},
  authoraddress = {Language Section, National Institute on Deafness and
                   Other Communication Disorders, National Institutes of
                   Health, Bethesda, Maryland 20892, USA.
                   horwitz@helix.nih.gov},
  keywords = {Algorithms ; Brain Mapping/*methods ;
                   *Electroencephalography/standards ; Human ; Image
                   Enhancement ; Image Processing,
                   Computer-Assisted/methods ; *Magnetic Resonance
                   Imaging/standards ; *Magnetoencephalography/standards ;
                   Neural Networks (Computer) ; *Tomography,
                   Emission-Computed/standards},
  language = {eng},
  medline-aid = {10.1002/hbm.10057 [doi]},
  medline-da = {20020830},
  medline-dcom = {20021017},
  medline-edat = {2002/08/31 10:00},
  medline-fau = {Horwitz, Barry ; Poeppel, David},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-mhda = {2002/10/18 04:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12203682},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {18},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 2002 Sep;17(1):1-3.},
  medline-stat = {completed},
  year = 2002
}
@ARTICLE{HRS+04,
  author = {Horovitz, S. G. and Rossion, B. and Skudlarski, P. and
                   Gore, J. C.},
  title = {Parametric design and correlational analyses help
                   integrating f{MRI} and electrophysiological data during
                   face processing},
  journal = {NeuroImage},
  volume = {22},
  number = {4},
  pages = {1587-1595},
  abstract = {Face perception is typically associated with
                   activation in the inferior occipital, superior temporal
                   (STG), and fusiform gyri (FG) and with an
                   occipitotemporal electrophysiological component peaking
                   around 170 ms on the scalp, the N170. However, the
                   relationship between the N170 and the multiple
                   face-sensitive activations observed in neuroimaging is
                   unclear. It has been recently shown that the amplitude
                   of the N170 component monotonically decreases as
                   gaussian noise is added to a picture of a face [Jemel
                   et al., 2003]. To help clarify the sources of the N170
                   without a priori assumptions regarding their number and
                   locations, ERPs and fMRI were recorded in five subjects
                   in the same experiment, in separate sessions. We used a
                   parametric paradigm in which the amplitude of the N170
                   was modulated by varying the level of noise in a
                   picture, and identified regions where the percent
                   signal change in fMRI correlated with the ERP data.
                   N170 signals were observed for pictures of both cars
                   and faces but were stronger for faces. A monotonic
                   decrease with added noise was observed for the N170 at
                   right hemisphere sites but was less clear on the left
                   and occipital central sites. Correlations between fMRI
                   signal and N170 amplitudes for faces were highly
                   significant (P < 0.001) in bilateral fusiform gyrus and
                   superior temporal gyrus. For cars, the strongest
                   correlations were observed in the parahippocampal
                   region and in the STG (P < 0.005). Besides contributing
                   to clarify the spatiotemporal course of face
                   processing, this study illustrates how ERP information
                   may be used synergistically in fMRI analyses.
                   Parametric designs may be developed further to provide
                   some timing information on fMRI activity and help
                   identify the generators of ERP signals.},
  authoraddress = {Institute of Imaging Science, Vanderbilt University,
                   Nashville, TN 37203, USA.},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2004.04.018 [doi] ;
                   S1053811904002198 [pii]},
  medline-da = {20040727},
  medline-edat = {2004/07/28 05:00},
  medline-fau = {Horovitz, Silvina G ; Rossion, Bruno ; Skudlarski,
                   Pawel ; Gore, John C},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/07/28 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Nov/24 [received] ; 2004/Apr/09 [revised] ;
                   2004/Apr/15 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15275915},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Aug;22(4):1587-95.},
  medline-stat = {in-data-review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15275915},
  year = 2004
}
@ARTICLE{HS89,
  author = {Hamalainen, M. S. and Sarvas, J.},
  title = {Realistic conductivity geometry model of the human
                   head for interpretation of neuromagnetic data},
  journal = {IEEE Trans Biomed Eng},
  volume = {36},
  number = {2},
  pages = {165-171},
  abstract = {In this paper, the computational and practical aspects
                   of a realistically-shaped multilayer model for the
                   conductivity geometry of the human head are discussed.
                   A novel way to handle the numerical difficulties caused
                   by the presence of the poorly conducting skull is
                   presented. Using our method, both the potential on the
                   surface of the head and the magnetic field outside the
                   head can be computed accurately. The procedure was
                   tested with the multilayer sphere model, for which
                   analytical expressions are available. The method is
                   then applied to a realistically-shaped head model, and
                   it is numerically shown that for the computation of B,
                   produced by cerebral current sources, it is sufficient
                   to consider a brain-shaped homogeneous conductor only
                   since the secondary currents on the outer interfaces
                   give only a negligible contribution to the magnetic
                   field outside the head. Comparisons with the sphere
                   model are also included to pinpoint areas where the
                   homogeneous conductor model provides essential
                   improvements in the calculation of the magnetic field
                   outside the head.},
  keywords = {Brain/physiology ; Electric Conductivity ;
                   *Electromagnetic Fields ; *Electromagnetics ;
                   Head/*anatomy & histology ; Human ; Models, Anatomic ;
                   Models, Biological ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-da = {19890327},
  medline-dcom = {19890327},
  medline-edat = {1989/02/01},
  medline-fau = {Hamalainen, M S ; Sarvas, J},
  medline-is = {0018-9294},
  medline-jid = {0012737},
  medline-lr = {20001218},
  medline-mhda = {1989/02/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {2917762},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng 1989 Feb;36(2):165-71.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=2917762},
  year = 1989
}
@ARTICLE{HSG02,
  author = {Horovitz, S. G. and Skudlarski, P. and Gore, J. C.},
  title = {Correlations and dissociations between {BOLD} signal
                   and {P}300 amplitude in an auditory oddball task: a
                   parametric approach to combining f{MRI} and {ERP}},
  journal = {Magn Reson Imaging},
  volume = {20},
  number = {4},
  pages = {319-325},
  abstract = {A parametric method is proposed to examine the
                   relationship between neuronal activity, measured with
                   event related potentials (ERPs), and the hemodynamic
                   response, observed with functional magnetic resonance
                   imaging (fMRI), during an auditory oddball paradigm.
                   After verifying that the amplitude of the evoked
                   response P300 increases as the probability of oddball
                   target presentation decreases, we explored the
                   corresponding effect of target frequency on the fMRI
                   signal. We predicted and confirmed that some regions
                   that showed activation changes following each oddball
                   are affected by the rate of presentation of the
                   oddballs, or the probability of an oddball target. We
                   postulated that those regions that increased activation
                   with decreasing probability might be responsible for
                   the corresponding changes in the P300 amplitude. fMRI
                   regions that correlated with the amplitude of the P300
                   wave were supramarginal gyri, thalamus, insula and
                   right medial frontal gyrus, and are presumably sources
                   of the P300 wave. Other regions, such as anterior and
                   posterior cingulate cortex, were activated during the
                   oddball paradigm but their fMRI signal changes were not
                   correlated with the P300 amplitudes. This study thus
                   shows how combining fMRI and ERP in a parametric design
                   identifies task-relevant sources of activity and allows
                   separation of regions that have different response
                   properties.},
  authoraddress = {Department of Engineering and Applied Science, Yale
                   University, New Haven, CT, USA.
                   silvina.horovitz@yale.edu},
  keywords = {Acoustic Stimulation ; Adult ; Brain/anatomy &
                   histology/*physiology ; *Event-Related Potentials,
                   P300/physiology ; Female ; Human ; Magnetic Resonance
                   Imaging/*methods ; Male},
  language = {eng},
  medline-aid = {S0730725X02004964 [pii]},
  medline-ci = {Copyright 2002 Elsevier Science Inc.},
  medline-da = {20020807},
  medline-dcom = {20021002},
  medline-edat = {2002/08/08 10:00},
  medline-fau = {Horovitz, Silvina G ; Skudlarski, Pawel ; Gore, John C},
  medline-is = {0730-725X},
  medline-jid = {8214883},
  medline-mhda = {2002/10/03 04:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12165350},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Magn Reson Imaging 2002 May;20(4):319-25.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12165350},
  year = 2002
}
@ARTICLE{HSH+05,
  author = {Hamandi, K. and Salek Haddadi, A. and Liston, A. and
                   Laufs, H. and Fish, D. R. and Lemieux, L.},
  title = {{f}{MRI} temporal clustering analysis in patients with
                   frequent interictal epileptiform discharges: comparison
                   with {EEG}-driven analysis.},
  journal = {Neuroimage},
  volume = {26},
  number = {1},
  pages = {309-16},
  note = {desribes shortcomming of the Temporal Clustering done
                   by Morgan (Resting functional MRI with temporal
                   clustering without EEG)},
  abstract = {Temporal clustering analysis (TCA) is an exploratory
                   data-driven technique that has been proposed for the
                   analysis of resting fMRI to localise epileptiform
                   activity without need for simultaneous EEG.
                   Conventionally, fMRI of epileptic activity has been
                   limited to those patients with subtle clinical events
                   or frequent interictal epileptiform EEG discharges,
                   requiring simultaneous EEG recording, from which a
                   linear model is derived to make valid statistical
                   inferences from the fMRI data. We sought to evaluate
                   TCA by comparing the results with those of EEG
                   correlated fMRI in eight selected cases. Cases were
                   selected with clear epileptogenic localisation or
                   lateralisation on the basis of concordant EEG and
                   structural MRI findings, in addition to concordant
                   activations seen on EEG-derived fMRI analyses. In
                   three, areas of activation were seen with TCA but none
                   corresponding to the electro-clinical localisation or
                   activations obtained with EEG driven analysis. Temporal
                   clusters were closely coincident with times of maximal
                   head motion. We feel this is a serious confound to this
                   approach and recommend that interpretation of TCA that
                   does not address motion and physiological noise be
                   treated with caution. New techniques to localise
                   epileptogenic activity with fMRI alone require
                   validation with an appropriate independent measure. In
                   the investigation of interictal epileptiform activity,
                   this is best done with simultaneous EEG recording.},
  authoraddress = {Department of Clinical and Experimental Epilepsy,
                   Institute of Neurology, University College London, UK.
                   k.hamandi@ion.ucl.ac.uk},
  keywords = {Cluster Analysis ; Comparative Study ;
                   Electrocardiography ; *Electroencephalography ;
                   Epilepsies, Partial/*pathology/*physiopathology ;
                   Humans ; Image Processing, Computer-Assisted ; Magnetic
                   Resonance Imaging ; Research Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1053-8119(05)00073-X [pii] ;
                   10.1016/j.neuroimage.2005.01.052 [doi]},
  medline-da = {20050502},
  medline-dcom = {20050712},
  medline-edat = {2005/05/03 09:00},
  medline-fau = {Hamandi, K ; Salek Haddadi, A ; Liston, A ; Laufs, H ;
                   Fish, D R ; Lemieux, L},
  medline-gr = {Wellcome Trust},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2005/07/13 09:00},
  medline-own = {NLM},
  medline-phst = {2004/08/09 [received] ; 2005/01/16 [revised] ;
                   2005/01/21 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15862232},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2005 May 15;26(1):309-16.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15862232},
  year = 2005
}
@ARTICLE{HSL+04,
  author = {Huang, M. X. and Shih, J. J. and Lee, R. R. and
                   Harrington, D. L. and Thoma, R. J. and Weisend, M. P.
                   and Hanlon, F. and Paulson, K. M. and Li, T. and
                   Martin, K. and Millers, G. A. and Canive, J. M.},
  title = {Commonalities and differences among vectorized
                   beamformers in electromagnetic source imaging},
  journal = {Brain Topogr},
  volume = {16},
  number = {3},
  pages = {139-158},
  abstract = {A number of beamformers have been introduced to
                   localize neuronal activity using magnetoencephalography
                   (MEG) and electroencephalography (EEG). However,
                   currently available information about the major aspects
                   of existing beamformers is incomplete. In the present
                   study, detailed analyses are performed to study the
                   commonalities and differences among vectorized versions
                   of existing beamformers in both theory and practice. In
                   addition, a novel beamformer based on higher-order
                   covariance analysis is introduced. Theoretical formulas
                   are provided on all major aspects of each beamformer;
                   to examine their performance, computer simulations with
                   different levels of correlation and signal-to-noise
                   ratio are studied. Then, an empirical data set of human
                   MEG median-nerve responses with a large number of
                   neuronal generators is analyzed using the different
                   beamformers. The results show substantial differences
                   among existing MEG/EEG beamformers in their ways of
                   describing the spatial map of neuronal activity.
                   Differences in performance are observed among existing
                   beamformers in terms of their spatial resolution,
                   false-positive background activity, and robustness to
                   highly correlated signals. Superior performance is
                   obtained using our novel beamformer with higher-order
                   covariance analysis in simulated data. Excellent
                   agreement is also found between the results of our
                   beamformer and the known neurophysiology of the
                   median-nerve MEG response.},
  authoraddress = {Center for Functional Brain Imaging, New Mexico VA
                   Health Care System, Albuquerque, NM 87108, USA.
                   mhuang@unm.edu},
  keywords = {Brain/cytology/*radiation effects ; Brain Mapping ;
                   Comparative Study ; *Electroencephalography ;
                   Electromagnetics/methods ; Evoked Potentials/radiation
                   effects ; Human ; Image Interpretation,
                   Computer-Assisted ; Least-Squares Analysis ;
                   *Magnetoencephalography ; Median
                   Nerve/physiology/radiation effects ; *Models,
                   Neurological ; Neurons/physiology/radiation effects ;
                   Signal Processing, Computer-Assisted ; Support,
                   Non-U.S. Gov't ; Support, U.S. Gov't, Non-P.H.S. ;
                   Support, U.S. Gov't, P.H.S. ; Time Factors},
  language = {eng},
  medline-da = {20040527},
  medline-dcom = {20040630},
  medline-edat = {2004/05/28 05:00},
  medline-fau = {Huang, M X ; Shih, J J ; Lee, R R ; Harrington, D L ;
                   Thoma, R J ; Weisend, M P ; Hanlon, F ; Paulson, K M ;
                   Li, T ; Martin, K ; Millers, G A ; Canive, J M},
  medline-gr = {P20-RR15636-01/RR/NCRR ; R01-MH65304-01/MH/NIMH},
  medline-is = {0896-0267},
  medline-jid = {8903034},
  medline-mhda = {2004/07/01 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {15162912},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Brain Topogr 2004 Spring;16(3):139-58.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15162912},
  year = 2004
}
@ARTICLE{HTF+04,
  author = {Husain, F. T. and Tagamets, M. A. and Fromm, S. J. and
                   Braun, A. R. and Horwitz, B.},
  title = {Relating neuronal dynamics for auditory object
                   processing to neuroimaging activity: a computational
                   modeling and an f{MRI} study},
  journal = {NeuroImage},
  volume = {21},
  number = {4},
  pages = {1701-1720},
  abstract = {We investigated the neural basis of auditory object
                   processing in the cerebral cortex by combining neural
                   modeling and functional neuroimaging. We developed a
                   large-scale, neurobiologically realistic network model
                   of auditory pattern recognition that relates the
                   neuronal dynamics of cortical auditory processing of
                   frequency modulated (FM) sweeps to functional
                   neuroimaging data of the type obtained using PET and
                   fMRI. Areas included in the model extend from primary
                   auditory to prefrontal cortex. The electrical
                   activities of the neuronal units of the model were
                   constrained to agree with data from the
                   neurophysiological literature regarding the perception
                   of FM sweeps. We also conducted an fMRI experiment
                   using stimuli and tasks similar to those used in our
                   simulations. The integrated synaptic activity of the
                   neuronal units in each region of the model, convolved
                   with a hemodynamic response function, was used as a
                   correlate of the simulated fMRI activity, and generally
                   agreed with the experimentally observed fMRI data in
                   the brain areas corresponding to the regions of the
                   model. Our results demonstrate that the model is
                   capable of exhibiting the salient features of both
                   electrophysiological neuronal activities and fMRI
                   values that are in agreement with empirically observed
                   data. These findings provide support for our hypotheses
                   concerning how auditory objects are processed by
                   primate neocortex.},
  authoraddress = {Brain Imaging and Modeling Section, National Institute
                   on Deafness and Other Communication Disorders, National
                   Institutes of Health, Bethesda, MD 20892, USA.
                   husainf@nidcd.nih.gov},
  keywords = {Adult ; Auditory Cortex/physiology ; Auditory
                   Pathways/physiology ; Auditory Perception/*physiology ;
                   Brain Mapping ; Cerebral Cortex/*physiology ;
                   Dominance, Cerebral/physiology ; Female ; Human ;
                   *Image Enhancement ; *Image Processing,
                   Computer-Assisted ; *Imaging, Three-Dimensional ;
                   *Magnetic Resonance Imaging ; Male ; Memory,
                   Short-Term/physiology ; *Neural Networks (Computer) ;
                   Neurons/physiology ; Oxygen/*blood ; Pitch
                   Perception/physiology ; Prefrontal Cortex/physiology ;
                   Psychoacoustics ; Reference Values ; Retention
                   (Psychology)/physiology ; Sound Localization/physiology
                   ; Sound Spectrography ; Speech Perception/physiology ;
                   Support, U.S. Gov't, P.H.S. ; Tomography,
                   Emission-Computed},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.11.012 [doi] ;
                   S105381190300733X [pii]},
  medline-da = {20040330},
  medline-dcom = {20040806},
  medline-edat = {2004/03/31 05:00},
  medline-fau = {Husain, F T ; Tagamets, M-A ; Fromm, S J ; Braun, A R
                   ; Horwitz, B},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/08/07 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Aug/29 [received] ; 2003/Oct/09 [revised] ;
                   2003/Nov/03 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15050592},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Apr;21(4):1701-20.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15050592},
  year = 2004
}
@ARTICLE{HTR+02,
  author = {Haueisen, J. and Tuch, D. S. and Ramon, C. and
                   Schimpf, P.H. and Wedeen, V. J. and George, J. S. and
                   Belliveau, J.W.},
  title = {The influence of brain tissue anisotropy on human
                   {EEG} and {MEG}},
  journal = {NeuroImage},
  volume = {15},
  number = {1},
  pages = {159-166},
  abstract = {The influence of gray and white matter tissue
                   anisotropy on the human electroencephalogram (EEG) and
                   magnetoencephalogram (MEG) was examined with a high
                   resolution finite element model of the head of an adult
                   male subject. The conductivity tensor data for gray and
                   white matter were estimated from magnetic resonance
                   diffusion tensor imaging. Simulations were carried out
                   with single dipoles or small extended sources in the
                   cortical gray matter. The inclusion of anisotropic
                   volume conduction in the brain was found to have a
                   minor influence on the topology of EEG and MEG (and
                   hence source localization). We found a major influence
                   on the amplitude of EEG and MEG (and hence source
                   strength estimation) due to the change in conductivity
                   and the inclusion of anisotropy. We expect that
                   inclusion of tissue anisotropy information will improve
                   source estimation procedures.},
  authoraddress = {Biomagnetisches Zentrum,
                   Friedrich-Schiller-Universitat, Jena, Germany.},
  keywords = {Adult ; Anisotropy ; Brain/*physiology ; Brain Mapping
                   ; *Electroencephalography ; *Finite Element Analysis ;
                   Human ; *Magnetoencephalography ; Male ; Reference
                   Values ; Signal Processing, Computer-Assisted ;
                   Support, Non-U.S. Gov't ; Support, U.S. Gov't,
                   Non-P.H.S.},
  language = {eng},
  medline-aid = {10.1006/nimg.2001.0962 [doi] ; S1053811901909620 [pii]},
  medline-da = {20020104},
  medline-dcom = {20020320},
  medline-edat = {2002/01/05 10:00},
  medline-fau = {Haueisen, J ; Tuch, D S ; Ramon, C ; Schimpf, P H ;
                   Wedeen, V J ; George, J S ; Belliveau, J W},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2002/03/21 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11771984},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2002 Jan;15(1):159-66.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11771984},
  year = 2002
}
@ARTICLE{HWV+04,
  author = {Hinterberger, T. and Weiskopf, N. and Veit, R. and
                   Wilhelm, B. and Betta, E. and Birbaumer, N.},
  title = {An {EEG}-driven brain-computer interface combined with
                   functional magnetic resonance imaging (f{MRI}).},
  journal = {IEEE Trans Biomed Eng},
  volume = {51},
  number = {6},
  pages = {971-4},
  abstract = {Self-regulation of slow cortical potentials (SCPs) has
                   been successfully used to prevent epileptic seizures as
                   well as to communicate with completely paralyzed
                   patients. The thought translation device (TTD) is a
                   brain-computer interface (BCI) that was developed for
                   training and application of SCP self-regulation. To
                   investigate the neurophysiological mechanisms of SCP
                   regulation the TTD was combined with functional
                   magnetic resonance imaging (fMRI). The technical
                   aspects and pitfalls of combined fMRI data acquisition
                   and EEG neurofeedback are discussed. First data of SCP
                   feedback during fMRI are presented.},
  authoraddress = {Institute of Medical Psychology and Behavioral
                   Neurobiology, University of Tubingen, Tubingen 72076,
                   Germany. thilo.hinterberger@uni-tuebingen.de},
  keywords = {Biofeedback (Psychology)/*methods/physiology ;
                   Cerebral Cortex/*physiology ;
                   Electroencephalography/*methods ; Evoked
                   Potentials/*physiology ; Feasibility Studies ;
                   Feedback/physiology ; Hippocampus/physiology ; Humans ;
                   Image Interpretation, Computer-Assisted/*methods ;
                   Magnetic Resonance Imaging/*methods ; Motor
                   Cortex/physiology ; Online Systems ; Pilot Projects ;
                   Reproducibility of Results ; Research Support, Non-U.S.
                   Gov't ; Research Support, U.S. Gov't, P.H.S. ;
                   Sensitivity and Specificity ; *User-Computer Interface},
  language = {eng},
  medline-da = {20040610},
  medline-dcom = {20040901},
  medline-edat = {2004/06/11 05:00},
  medline-fau = {Hinterberger, Thilo ; Weiskopf, Nikolaus ; Veit, Ralf
                   ; Wilhelm, Barbara ; Betta, Elena ; Birbaumer, Niels},
  medline-is = {0018-9294 (Print)},
  medline-jid = {0012737},
  medline-jt = {IEEE transactions on bio-medical engineering.},
  medline-lr = {20041117},
  medline-mhda = {2004/09/02 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {15188866},
  medline-pst = {ppublish},
  medline-pt = {Evaluation Studies ; Journal Article ; Validation
                   Studies},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng. 2004 Jun;51(6):971-4.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15188866},
  year = 2004
}
@ARTICLE{Hau04,
  author = {Hauk, O.},
  title = {Keep it simple: a case for using classical minimum
                   norm estimation in the analysis of {EEG} and {MEG} data},
  journal = {NeuroImage},
  volume = {21},
  number = {4},
  pages = {1612-1621},
  abstract = {The present study aims at finding the optimal inverse
                   solution for the bioelectromagnetic inverse problem in
                   the absence of reliable a priori information about the
                   generating sources. Three approaches to tackle this
                   problem are compared theoretically: the
                   maximum-likelihood approach, the minimum norm approach,
                   and the resolution optimization approach. It is shown
                   that in all three of these frameworks, it is possible
                   to make use of the same kind of a priori information if
                   available, and the same solutions are obtained if the
                   same a priori information is implemented. In
                   particular, they all yield the minimum norm
                   pseudoinverse (MNP) in the complete absence of such
                   information. This indicates that the properties of the
                   MNP, and in particular, its limitations like the
                   inability to localize sources in depth, are not
                   specific to this method but are fundamental limitations
                   of the recording modalities. The minimum norm solution
                   provides the amount of information that is actually
                   present in the data themselves, and is therefore
                   optimally suited to investigate the general resolution
                   and accuracy limits of EEG and MEG measurement
                   configurations. Furthermore, this strongly suggests
                   that the classical minimum norm solution is a valuable
                   method whenever no reliable a priori information about
                   source generators is available, that is, when complex
                   cognitive tasks are employed or when very noisy data
                   (e.g., single-trial data) are analyzed. For that
                   purpose, an efficient and practical implementation of
                   this method will be suggested and illustrated with
                   simulations using a realistic head geometry.},
  authoraddress = {Cognition and Brain Sciences Unit, Medical Research
                   Council, Cambridge, UK. olaf.hauk@mrc-cbu.cam.ac.uk},
  keywords = {Action Potentials/physiology ; Brain Mapping ;
                   Cerebral Cortex/*physiology ; Computer Graphics ;
                   Computer Simulation ;
                   Electroencephalography/*statistics & numerical data ;
                   Human ; *Image Processing, Computer-Assisted ;
                   *Imaging, Three-Dimensional ; Likelihood Functions ;
                   Magnetoencephalography/*statistics & numerical data ;
                   Reference Values ; *Signal Processing,
                   Computer-Assisted},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.12.018 [doi] ;
                   S1053811903007845 [pii]},
  medline-da = {20040330},
  medline-dcom = {20040806},
  medline-edat = {2004/03/31 05:00},
  medline-fau = {Hauk, Olaf},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/08/07 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Aug/19 [received] ; 2003/Dec/06 [revised] ;
                   2003/Dec/09 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15050585},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Apr;21(4):1612-21.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15050585},
  year = 2004
}
@ARTICLE{Horn-etal88,
  author = {Horn, B. K. P. and Hilden, H. and Negahdaripour, S.},
  title = {Closed-Form Solution of Absolute Orientation Using
                  Orthonormal Matrices},
  journal = {J. Opt. Soc. Amer.},
  volume = 5,
  number = 7,
  month = JUL,
  year = 1988,
  pages = {1127-1135}
}
@ARTICLE{Horn87a,
  author = {Horn, B. K. P.},
  title = {Closed-form solution of absolute orientation using
                  unit quaternions},
  journal = {J. Opt. Soc. Amer.},
  year = 1987,
  volume = 4,
  number = 4,
  pages = {629-642},
  month = APR
}
@ARTICLE{ILZ+06,
  author = {Im, C. H. and Liu, Z. and Zhang, N. and Chen, W. and
                   He, B.},
  title = {Functional cortical source imaging from simultaneously
                   recorded {ERP} and f{MRI}.},
  journal = {J Neurosci Methods},
  abstract = {Feasibility of continuously and simultaneously
                   recording visual evoked potentials (VEPs) with fMRI was
                   assessed by quantitatively comparing cortical source
                   images by means of receiver operating characteristic
                   (ROC) curve analysis. The averaged EEG source images
                   coincided well with simultaneously acquired fMRI
                   activations. Strong correlation was found between the
                   cortical source images of VEPs recorded inside and
                   outside the scanner. Application of fMRI prior
                   information strengthened correlation between estimated
                   source images as well as resulted in source estimates
                   with higher spatial resolution. The present results
                   demonstrate that reliable cortical source images can be
                   acquired during simultaneous fMRI scanning and they may
                   be used for multimodal functional source imaging
                   studies.},
  authoraddress = {Department of Biomedical Engineering, University of
                   Minnesota, United States.},
  language = {ENG},
  medline-aid = {S0165-0270(06)00154-3 [pii] ;
                   10.1016/j.jneumeth.2006.03.015 [doi]},
  medline-da = {20060505},
  medline-dep = {20060502},
  medline-edat = {2006/05/06 09:00},
  medline-is = {0165-0270 (Print)},
  medline-jid = {7905558},
  medline-mhda = {2006/05/06 09:00},
  medline-own = {NLM},
  medline-phst = {2005/12/06 [received] ; 2006/03/05 [revised] ;
                   2006/03/15 [accepted]},
  medline-pmid = {16675026},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {J Neurosci Methods. 2006 May 2;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16675026},
  year = 2006
}
@ARTICLE{IWS+93,
  author = {Ives, J. R. and Warach, S. and Schmitt, F. and
                   Edelman, R. R. and Schomer, D. L.},
  title = {Monitoring the patient's {EEG} during echo planar
                   {MRI}},
  journal = {Electroencephalogr Clin Neurophysiol},
  volume = {87},
  number = {6},
  pages = {417-420},
  abstract = {The recording of an EEG while the patient is
                   undergoing magnetic resonance imaging (MRI) data
                   acquisition, as far as we are aware, has not been
                   previously accomplished. By careful selection and
                   arrangement of analog multiplexed cable-telemetry
                   equipment to eliminate both ferrous and RF sources, a
                   stable, readable EEG can be obtained without
                   interfering with the diagnostic quality of the MRI.
                   This arrangement does not cause localized heating or
                   burning at the electrode sites. This technical
                   capability permits more accurate neurophysiological
                   control during the acquisition of echo planar
                   functional MRI studies as well as providing indications
                   of anatomical localization of electrical sources.},
  authoraddress = {Department of Neurology (DA-807), Beth Israel
                   Hospital, Harvard Medical School, Boston, MA 02215.},
  keywords = {*Echo-Planar Imaging ; Electroencephalography/*methods
                   ; Human ; Monitoring, Physiologic},
  language = {eng},
  medline-da = {19940315},
  medline-dcom = {19940315},
  medline-edat = {1993/12/01},
  medline-fau = {Ives, J R ; Warach, S ; Schmitt, F ; Edelman, R R ;
                   Schomer, D L},
  medline-is = {0013-4694},
  medline-jid = {0375035},
  medline-lr = {20001218},
  medline-mhda = {1993/12/01 00:01},
  medline-own = {NLM},
  medline-pl = {IRELAND},
  medline-pmid = {7508375},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Electroencephalogr Clin Neurophysiol 1993
                   Dec;87(6):417-20.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=7508375},
  year = 1993
}
@ARTICLE{JBM+04,
  author = {Jerbi, K. and Baillet, S. and Mosher, J. C. and Nolte,
                   G. and Garnero, L. and Leahy, R. M.},
  title = {Localization of realistic cortical activity in {MEG}
                   using current multipoles},
  journal = {NeuroImage},
  volume = {22},
  number = {2},
  pages = {779-793},
  abstract = {We present a novel approach to MEG source estimation
                   based on a regularized first-order multipole solution.
                   The Gaussian regularizing prior is obtained by
                   calculation of the sample mean and covariance matrix
                   for the equivalent moments of realistic simulated
                   cortical activity. We compare the regularized multipole
                   localization framework to the classical dipole and
                   general multipole source estimation methods by
                   evaluating the ability of all three solutions to
                   localize the centroids of physiologically plausible
                   patches of activity simulated on the surface of a human
                   cerebral cortex. The results, obtained with a realistic
                   sensor configuration, a spherical head model, and given
                   in terms of field and localization error, depict the
                   performance of the dipolar and multipolar models as a
                   function of variable source surface area (50-500
                   mm(2)), noise conditions (20, 10, and 5 dB SNR), source
                   orientation (0-90 degrees ), and source depth (3-11
                   cm). We show that as the sources increase in size, they
                   become less accurately modeled as current dipoles. The
                   regularized multipole systematically outperforms the
                   single dipole model, increasingly so as the spatial
                   extent of the sources increases. In addition, our
                   simulations demonstrate that as the orientation of the
                   sources becomes more radial, dipole localization
                   accuracy decreases substantially, while the performance
                   of the regularized multipole model is far less
                   sensitive to orientation and even succeeds in
                   localizing quasi-radial source configurations.
                   Furthermore, our results show that the multipole model
                   is able to localize superficial sources with higher
                   accuracy than the current dipole. These results
                   indicate that the regularized multipole solution may be
                   an attractive alternative to current-dipole-based
                   source estimation methods in MEG.},
  authoraddress = {Cognitive Neuroscience and Brain Imaging Laboratory,
                   Hopital de la Salpetriere, CNRS,UPR 640, Paris, France.},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2004.02.010 [doi] ;
                   S1053811904001028 [pii]},
  medline-da = {20040614},
  medline-edat = {2004/06/15 05:00},
  medline-fau = {Jerbi, K ; Baillet, S ; Mosher, J C ; Nolte, G ;
                   Garnero, L ; Leahy, R M},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/06/15 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Sep/30 [received] ; 2004/Feb/09 [revised] ;
                   2004/Feb/12 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15193607},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Jun;22(2):779-93.},
  medline-stat = {in-data-review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15193607},
  year = 2004
}
@ARTICLE{JLS87,
  author = {Jeffs, B. and Leahy, R. and Singh, M.},
  title = {An evaluation of methods for neuromagnetic image
                   reconstruction},
  journal = {IEEE Trans Biomed Eng},
  volume = {34},
  number = {9},
  pages = {713-723},
  keywords = {Biomedical Engineering ; Brain/*anatomy &
                   histology/physiology ; Evaluation Studies ; Human ;
                   Image Processing, Computer-Assisted/methods ;
                   *Magnetics ; Models, Theoretical ; Neurons/physiology ;
                   Support, Non-U.S. Gov't},
  language = {eng},
  medline-da = {19871119},
  medline-dcom = {19871119},
  medline-edat = {1987/09/01},
  medline-fau = {Jeffs, B ; Leahy, R ; Singh, M},
  medline-is = {0018-9294},
  medline-jid = {0012737},
  medline-lr = {20001218},
  medline-mhda = {1987/09/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {3653912},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng 1987 Sep;34(9):713-23.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=3653912},
  year = 1987
}
@ARTICLE{KAS+00,
  author = {Krakow, K. and Allen, P. J. and Symms, M. R. and
                   Lemieux, L. and Josephs, O. and Fish, D. R.},
  title = {E{EG} recording during f{MRI} experiments: image
                   quality},
  journal = {Hum Brain Mapp},
  volume = {10},
  number = {1},
  pages = {10-15},
  abstract = {Electroencephalographic (EEG) monitoring during
                   functional magnetic resonance imaging (fMRI)
                   experiments is increasingly applied for studying
                   physiological and pathological brain function. However,
                   the quality of the fMRI data can be significantly
                   compromised by the EEG recording due to the magnetic
                   susceptibility of the EEG electrode assemblies and
                   electromagnetic noise emitted by the EEG recording
                   equipment. We therefore investigated the effect of
                   individual components of the EEG recording equipment on
                   the quality of echo planar images. The artifact
                   associated with each component was measured and
                   compared to the minimum scalp-cortex distance measured
                   in normal controls. The image noise originating from
                   the EEG recording equipment was identified as coherent
                   noise and could be eliminated by appropriate shielding
                   of the EEG equipment. It was concluded that concurrent
                   EEG and fMRI could be performed without compromising
                   the image quality significantly if suitable equipment
                   is used. The methods described and the results of this
                   study should be useful to other researchers as a
                   framework for testing of their own equipment and for
                   the selection of appropriate equipment for EEG
                   recording inside a MR scanner.},
  authoraddress = {Department of Clinical Neurology, Institute of
                   Neurology, University College London, UK.},
  keywords = {Adolescent ; Adult ; Artifacts ; Cerebral
                   Cortex/anatomy & histology/physiology ;
                   *Electroencephalography ; Female ; Human ; Image
                   Enhancement ; *Magnetic Resonance Imaging ; Male ;
                   Middle Aged ; Scalp/anatomy & histology/physiology ;
                   Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1002/(SICI)1097-0193(200005)10:1<10::AID-HBM20>3.0.CO;2-T
                   [pii]},
  medline-da = {20000914},
  medline-dcom = {20000914},
  medline-edat = {2000/06/08 09:00},
  medline-fau = {Krakow, K ; Allen, P J ; Symms, M R ; Lemieux, L ;
                   Josephs, O ; Fish, D R},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-lr = {20031114},
  medline-mhda = {2000/09/19 11:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10843514},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 2000 May;10(1):10-5.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10843514},
  year = 2000
}
@ARTICLE{KBG+06,
  author = {Kobayashi, E. and Bagshaw, A. P. and Grova, C. and
                   Gotman, J. and Dubeau, F.},
  title = {Grey matter heterotopia: what {EEG}-f{MRI} can tell us
                   about epileptogenicity of neuronal migration disorders.},
  journal = {Brain},
  volume = {129},
  number = {Pt 2},
  pages = {366-74},
  abstract = {Grey matter heterotopia are commonly associated with
                   refractory epilepsy. Depth electrodes recordings have
                   shown that epileptiform activity can be generated
                   within these lesions, and also at a distance in the
                   neocortex. Heterotopia seem to be part of a more
                   complex circuitry involving also the surrounding and
                   distant cerebral cortex. Blood oxygenation
                   level-dependent (BOLD) changes to interictal spikes
                   using continuous EEG and functional MRI (EEG-fMRI) can
                   help to understand non-invasively the mechanisms of
                   epileptogenicity in these patients. We studied 14
                   patients with epilepsy and heterotopia using
                   simultaneous recording of EEG-fMRI. EEG was
                   continuously acquired from inside the scanner during 2
                   h sessions. Epileptic spikes were visually identified
                   in the filtered EEG and each type of spike determined
                   one EEG-fMRI study. We looked at positive (activation)
                   and negative (deactivation) changes in the BOLD signal.
                   Eleven patients had nodular heterotopia and three band
                   heterotopia. Four patients had more than one type of
                   spikes, with a total of 26 EEG-fMRI studies. We
                   excluded three with less than three spikes, and
                   therefore a total of 23 studies (12 with nodular and 11
                   with band heterotopia) were analysed. Nodular
                   heterotopia: Activation was present in nine studies,
                   with involvement of the heterotopia or surrounding
                   cortex in six, three of which had concomitant distant
                   activation. Deactivation was also observed in nine
                   studies, with involvement of the heterotopia and
                   surrounding cortex in four, three of which had
                   concomitant distant deactivation. Band heterotopia:
                   Activation was present in all 11 studies, and always
                   involved the heterotopia and surrounding cortex, 9 of
                   which had concomitant distant activation. Deactivation
                   was also observed in all 11 studies, with involvement
                   of both the heterotopia and surrounding cortex, in
                   addition to distant deactivation in 5 studies. EEG-fMRI
                   studies reveal, non-invasively, metabolic responses in
                   the heterotopia despite the fact that spikes are
                   generated in the neocortex. The responses, activation
                   or deactivation, had different correlation with the
                   lesion and surrounding or distant cortex, activation
                   reflecting intense neuronal activity, or excitation,
                   and deactivation a possible distant (extra-lesional)
                   inhibition. EEG-fMRI may become a useful tool to
                   understand the epileptogenicity of such malformations.},
  authoraddress = {Montreal Neurological Institute and Hospital, McGill
                   University, Montreal, Canada.
                   eliane.kobayashi@mail.mcgill.ca},
  keywords = {Brain/*pathology ; Choristoma/*pathology ;
                   *Electroencephalography ; Epilepsy/*pathology ; Female
                   ; Humans ; *Magnetic Resonance Imaging ; Male ;
                   Research Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {awh710 [pii] ; 10.1093/brain/awh710 [doi]},
  medline-da = {20060125},
  medline-dcom = {20060224},
  medline-dep = {20051209},
  medline-edat = {2005/12/13 09:00},
  medline-fau = {Kobayashi, Eliane ; Bagshaw, Andrew P ; Grova,
                   Christophe ; Gotman, Jean ; Dubeau, Francois},
  medline-is = {1460-2156 (Electronic)},
  medline-jid = {0372537},
  medline-jt = {Brain : a journal of neurology.},
  medline-mhda = {2006/02/25 09:00},
  medline-own = {NLM},
  medline-phst = {2005/12/09 [aheadofprint]},
  medline-pl = {England},
  medline-pmid = {16339793},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {AIM ; IM},
  medline-so = {Brain. 2006 Feb;129(Pt 2):366-74. Epub 2005 Dec 9.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16339793},
  year = 2006
}
@ARTICLE{KCN01,
  author = {Kozinska, D. and Carducci, F. and Nowinski, K.},
  title = {Automatic alignment of {EEG}/{MEG} and {MRI} data sets},
  journal = {Clin Neurophysiol},
  volume = {112},
  number = {8},
  pages = {1553-1561},
  abstract = {OBJECTIVEs: We developed a new technique of fully
                   automatic alignment of brain data acquired with scalp
                   sensors (e.g. electroencephalography/evoked potential
                   (EP) electrodes, magnetoencephalography sensors) with a
                   magnetic resonance imaging (MRI) volume of the head.
                   METHODS: The method uses geometrical features (two sets
                   of head points: digitized from the subject and
                   extracted from MRI) to guide the alignment. It combines
                   matching on 3 dimensional (3D) geometrical moments that
                   perform the initial alignment, and 3D distance-based
                   alignment that provides the final tuning. To reduce
                   errors of the initial guessed computation resulting
                   from digitization of the head surface points we
                   introduced weights to compute geometrical moments, and
                   a procedure to remove outliers to eliminate incorrectly
                   digitized points. RESULTS: The method was tested on
                   simulated (Monte Carlo trials) and on real data sets.
                   The simulations demonstrated that for the number of
                   test points within the range of 0.1-1\% of the total
                   number of head surface points and for the digitization
                   error in the range of -2-2 mm the average map error was
                   between 0.7 and 2.1 mm. The average distance error was
                   less than 1 mm. Tests on real data gave the average
                   distance error between 2.1 and 2.5 mm. CONCLUSIONS: The
                   developed technique is fast, robust and comfortable for
                   the patient and for medical personnel. It registers
                   scalp sensor positions with MRI head volume with
                   accuracy that is satisfactory for localization of
                   biological processes examined with a commonly used
                   number of scalp sensors (32, 64, or 128).},
  authoraddress = {Interdisciplinary Center for Mathematical and
                   Computational Modelling, University of Warsaw, ul.
                   Pawinskiego 5a, 02-106, Warsaw, Poland.
                   kozinska@icm.edu.pl},
  keywords = {Automatic Data Processing/*methods ;
                   *Electroencephalography ; Equipment Design ; Evoked
                   Potentials, Somatosensory/*physiology ; Head ; Human ;
                   *Magnetic Resonance Imaging ; Magnetics ; *Models,
                   Theoretical ; Sensitivity and Specificity},
  language = {eng},
  medline-aid = {S1388245701005569 [pii]},
  medline-da = {20010718},
  medline-dcom = {20010823},
  medline-edat = {2001/07/19 10:00},
  medline-fau = {Kozinska, D ; Carducci, F ; Nowinski, K},
  medline-is = {1388-2457},
  medline-jid = {100883319},
  medline-mhda = {2001/08/24 10:01},
  medline-own = {NLM},
  medline-pl = {Netherlands},
  medline-pmid = {11459696},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Clin Neurophysiol 2001 Aug;112(8):1553-61.},
  medline-stat = {completed},
  year = 2001
}
@ARTICLE{KF04,
  author = {Kiebel, S.J. and Friston, K.J.},
  title = {Statistical parametric mapping for event-related
                   potentials ({II}): a hierarchical temporal model.},
  journal = {Neuroimage},
  volume = {22},
  number = {2},
  pages = {503-20},
  abstract = {In this paper, we describe a temporal model for
                   event-related potentials (ERP) in the context of
                   statistical parametric mapping (SPM). In brief, we
                   project channel data onto a two-dimensional scalp
                   surface or into three-dimensional brain space using
                   some appropriate inverse solution. We then treat the
                   spatiotemporal data in a mass-univariate fashion. This
                   implicitly factorises the model into spatial and
                   temporal components. The key contribution of this paper
                   is the use of observation models that afford an
                   explicit distinction between observation error and
                   variation in the expression of ERPs. This distinction
                   is created by employing a two-level hierarchical model,
                   in which the first level models the ERP effects
                   within-subject and trial type, while the second models
                   differences in ERP expression among trial types and
                   subjects. By bringing the analysis of ERP data into a
                   classical hierarchical (i.e., mixed effects) framework,
                   many apparently disparate approaches (e.g.,
                   conventional P300 analyses and time-frequency analyses
                   of stimulus-locked oscillations) can be reconciled
                   within the same estimation and inference procedure.
                   Inference proceeds in the normal way using t or F
                   statistics to test for effects that are localised in
                   peristimulus time or in some time-frequency window. The
                   use of F statistics is an important generalisation of
                   classical approaches, because it allows one to test for
                   effects that lie in a multidimensional subspace (i.e.,
                   of unknown but constrained form). We describe the
                   analysis procedures, the underlying theory and compare
                   its performance to established techniques.},
  authoraddress = {Functional Imaging Laboratory, Institute of Neurology,
                   Wellcome Department of Imaging Neuroscience, London
                   WC1N 3BG, UK. skiebel@fil.ion.ucl.ac.uk},
  keywords = {Analysis of Variance ; Brain Mapping/methods ;
                   Comparative Study ; Computer Simulation ; Event-Related
                   Potentials, P300/physiology ; Evoked
                   Potentials/*physiology ; Humans ; *Models, Neurological
                   ; Models, Statistical ; Reproducibility of Results ;
                   Research Support, Non-U.S. Gov't ; Time Factors},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2004.02.013 [doi] ;
                   S1053811904001053 [pii]},
  medline-da = {20040614},
  medline-dcom = {20040819},
  medline-edat = {2004/06/15 05:00},
  medline-fau = {Kiebel, Stefan J ; Friston, Karl J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20041117},
  medline-mhda = {2004/08/20 05:00},
  medline-own = {NLM},
  medline-phst = {2003/10/16 [received] ; 2004/02/07 [revised] ;
                   2004/02/12 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15193579},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuroimage 2004 Jun;22(2):503-20.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15193579},
  year = 2004
}
@ARTICLE{KF04b,
  author = {Kiebel, S.J. and Friston, K.J.},
  title = {Statistical parametric mapping for event-related
                   potentials: {I}. {G}eneric considerations.},
  journal = {Neuroimage},
  volume = {22},
  number = {2},
  pages = {492-502},
  abstract = {In this paper, we frame the strategy and motivations
                   behind developments in statistical parametric mapping
                   (SPM) for the analysis of electroencephalogram (EEG)
                   data. This work deals specifically with SPM procedures
                   for the analysis of event-related potentials (ERP). We
                   place these developments in the larger context of
                   integrating electrophysiological and hemodynamic
                   measurements of evoked brain responses through the
                   fusion of EEG and fMRI data. In this paper, we consider
                   some fundamental issues when selecting an appropriate
                   statistical model that enables diverse questions to be
                   asked of the data and at the same time retains maximum
                   sensitivity. The three key issues addressed in this
                   paper are as follows: (i) should multivariate or mass
                   univariate analyses be adopted, (ii) should time be
                   treated as an experimental factor or as a dimension of
                   the measured response variable, and (iii) how to form
                   appropriate explanatory variables in a hierarchical
                   observation model. We review the relative merits of the
                   different options and explain the rationale for our
                   choices. In brief, we motivate a mass univariate
                   approach in terms of sensitivity to region-specific
                   responses. This involves modeling responses at each
                   voxel or space bin separately. In contradistinction, we
                   treat time as an experimental factor to enable
                   inferences about temporally distributed responses that
                   encompass multiple time bins. In a companion paper, we
                   develop statistical models of ERPs in the time domain
                   that follow from the heuristics established here and
                   illustrate the approach using simulated and real data.},
  authoraddress = {Functional Imaging Laboratory, Wellcome Department of
                   Imaging Neuroscience, Institute of Neurology, WC1N 3BG,
                   London, UK. skiebel@fil.ucl.ac.uk},
  keywords = {Analysis of Variance ; Brain/anatomy &
                   histology/*physiology ; Brain Mapping ;
                   Electroencephalography ; Evoked Potentials/*physiology
                   ; Humans ; Magnetic Resonance Imaging ; *Models,
                   Neurological ; Models, Statistical ; Multivariate
                   Analysis ; Research Support, Non-U.S. Gov't ;
                   Sensitivity and Specificity},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2004.02.012 [doi] ;
                   S1053811904001041 [pii]},
  medline-da = {20040614},
  medline-dcom = {20040819},
  medline-edat = {2004/06/15 05:00},
  medline-fau = {Kiebel, Stefan J ; Friston, Karl J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20041117},
  medline-mhda = {2004/08/20 05:00},
  medline-own = {NLM},
  medline-phst = {2003/10/16 [received] ; 2004/02/07 [revised] ;
                   2004/02/12 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15193578},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuroimage 2004 Jun;22(2):492-502.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15193578},
  year = 2004
}
@ARTICLE{KGF00,
  author = {Kiebel, S. J. and Goebel, R. and Friston, K. J.},
  title = {Anatomically informed basis functions},
  journal = {NeuroImage},
  volume = {11},
  number = {6.1},
  pages = {656-667},
  abstract = {This paper introduces the general framework, concepts,
                   and procedures of anatomically informed basis functions
                   (AIBF), a new method for the analysis of functional
                   magnetic resonance imaging (fMRI) data. In
                   contradistinction to existing voxel-based univariate or
                   multivariate methods the approach described here can
                   incorporate various forms of prior anatomical knowledge
                   to specify sophisticated spatiotemporal models for fMRI
                   time-series. In particular, we focus on anatomical
                   prior knowledge, based on reconstructed gray matter
                   surfaces and assumptions about the location and spatial
                   smoothness of the blood oxygenation level dependent
                   (BOLD) effect. After reconstruction of the grey matter
                   surface from an individual's high-resolution
                   T1-weighted MRI, we specify a set of anatomically
                   informed basis functions, fit the model parameters for
                   a single time point, using a regularized solution, and
                   finally make inferences about the estimated parameters
                   over time. Significant effects, induced by the
                   experimental paradigm, can then be visualized in the
                   native voxel-space or on the reconstructed folded,
                   inflated, or flattened cortical surface. As an example,
                   we apply the approach to a fMRI study (finger
                   opposition task) and compare the results to those of a
                   voxel-based analysis as implemented in the Statistical
                   Parametric Mapping package (SPM99). Additionally, we
                   show, using simulated data, that the approach offers
                   several desirable features particularly in terms of
                   superresolution and localization.},
  authoraddress = {Department of Neurology,
                   Friedrich-Schiller-University, Jena, 07740, Germany.},
  keywords = {Brain/*anatomy & histology/*physiology ;
                   Cerebrovascular Circulation ; Computer Simulation ;
                   Fingers/physiology ; Human ; Image Processing,
                   Computer-Assisted ; Magnetic Resonance Imaging/*methods
                   ; *Models, Anatomic ; *Models, Neurological ;
                   Movement/physiology ; Oxygen/blood ; Support, Non-U.S.
                   Gov't},
  language = {eng},
  medline-aid = {10.1006/nimg.1999.0542 [doi] ; S1053811999905426 [pii]},
  medline-ci = {Copyright 2000 Academic Press.},
  medline-da = {20000823},
  medline-dcom = {20000823},
  medline-edat = {2000/06/22 10:00},
  medline-fau = {Kiebel, S J ; Goebel, R ; Friston, K J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20011114},
  medline-mhda = {2000/08/29 11:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10860794},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM ; S},
  medline-so = {NeuroImage 2000 Jun;11(6 Pt 1):656-67.},
  medline-stat = {completed},
  year = 2000
}
@ARTICLE{KHS+99,
  author = {Korvenoja, A. and Huttunen, J. and Salli, E. and
                   Pohjonen, H. and Martinkauppi, S. and Palva, J. M. and
                   Lauronen, L. and Virtanen, J. and Ilmoniemi, R. J. and
                   Aronen, H. J.},
  title = {Activation of multiple cortical areas in response to
                   somatosensory stimulation: combined
                   magnetoencephalographic and functional magnetic
                   resonance imaging},
  journal = {Hum Brain Mapp},
  volume = {8},
  number = {1},
  pages = {13-27},
  abstract = {We combined information from functional magnetic
                   resonance imaging (fMRI) and magnetoencephalography
                   (MEG) to assess which cortical areas and in which
                   temporal order show macroscopic activation after right
                   median nerve stimulation. Five healthy subjects were
                   studied with the two imaging modalities, which both
                   revealed significant activation in the contra- and
                   ipsilateral primary somatosensory cortex (SI), the
                   contra- and ipsilateral opercular areas, the walls of
                   the contralateral postcentral sulcus (PoCS), and the
                   contralateral supplementary motor area (SMA). In fMRI,
                   two separate foci of activation in the opercular cortex
                   were discerned, one posteriorly in the parietal
                   operculum (PO), and one anteriorly near the insula or
                   frontal operculum (anterior operculum, AO). The
                   activation sites from fMRI were used to constrain the
                   solution of the inverse problem of MEG, which allowed
                   us to construct a model of the temporal sequence of
                   activation of the different sites. According to this
                   model, the mean onset latency for significant
                   activation at the contralateral SI was 20 msec (range,
                   17-22 msec), followed by activation of PoCS at 23 msec
                   (range, 21-25 msec). The contralateral PO was activated
                   at 26 msec (range, 19-32 msec) and AO at 33 msec
                   (range, 22-51 msec). The contralateral SMA became
                   active at 36 msec (range, 24-48 msec). The ipsilateral
                   SI, PO, and AO became activated at 54-67 msec. We
                   conclude that fMRI provides a useful means to constrain
                   the inverse problem of MEG, allowing the construction
                   of spatiotemporal models of cortical activation, which
                   may have significant implications for the understanding
                   of cortical network functioning.},
  authoraddress = {BioMag Laboratory, Helsinki University Central
                   Hospital, Finland. antti.korvenoja@helsinki.fi},
  keywords = {Adult ; Brain Mapping/*methods ; Cerebral
                   Cortex/*physiology ; Human ; Magnetic Resonance Imaging
                   ; Magnetoencephalography ; Male ; Median
                   Nerve/*physiology ; Reaction Time ; Somatosensory
                   Cortex/*physiology ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1002/(SICI)1097-0193(1999)8:1<13::AID-HBM2>3.0.CO;2-B
                   [pii]},
  medline-da = {19990908},
  medline-dcom = {19990908},
  medline-edat = {1999/08/04 10:00},
  medline-fau = {Korvenoja, A ; Huttunen, J ; Salli, E ; Pohjonen, H ;
                   Martinkauppi, S ; Palva, J M ; Lauronen, L ; Virtanen,
                   J ; Ilmoniemi, R J ; Aronen, H J},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-lr = {20001218},
  medline-mhda = {2000/08/12 11:00},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10432179},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 1999;8(1):13-27.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10432179},
  year = 1999
}
@ARTICLE{KHW+01,
  author = {Kruggel, F. and Herrmann, C. S. and Wiggins, C. J. and
                   von Cramon, D. Y.},
  title = {Hemodynamic and electroencephalographic responses to
                   illusory figures: recording of the evoked potentials
                   during functional {MRI}},
  journal = {NeuroImage},
  volume = {14},
  number = {6},
  pages = {1327-1336},
  abstract = {The feasibility of recording event-related potentials
                   (ERP) during functional MRI (fMRI) scanning using
                   higher level cognitive stimuli was studied. Using
                   responses to illusory figures in a visual oddball task,
                   evoked potentials were obtained with their expected
                   configurations and latencies. A rapid stimulation
                   scheme using randomly varied trial lengths was
                   employed, and class-wise characteristics of the
                   hemodynamic response were obtained by a nonlinear
                   analysis of the fMRI time series. Implications and
                   limitations of conducting combined ERP-fMRI experiments
                   using higher level cognitive stimuli are discussed.
                   EEG/fMRI results revealed a sequential activation of
                   striate and extrastriate occipital cortex along the
                   ventral path of object processing for Kanizsa figures.
                   Interestingly, Kanizsa figures activated the human
                   motion area MT. Targets resulted in activations of
                   frontal and parietal cortex which were not activated
                   for standard stimuli.},
  authoraddress = {Max-Planck-Institute of Cognitive Neuroscience,
                   Stephanstrasse 1, 04103 Leipzig, Germany.},
  keywords = {Adult ; Arousal/physiology ; Brain Mapping ;
                   *Electroencephalography ; Evoked Potentials,
                   Visual/physiology ; Female ; Frontal Lobe/blood
                   supply/physiology ; Human ; *Magnetic Resonance Imaging
                   ; Male ; Occipital Lobe/blood supply/*physiology ;
                   Optical Illusions/*physiology ; Orientation/physiology
                   ; Parietal Lobe/blood supply/physiology ; Pattern
                   Recognition, Visual/*physiology ; Reference Values ;
                   Regional Blood Flow/physiology ; Visual Cortex/blood
                   supply/*physiology ; Visual Pathways/blood
                   supply/physiology},
  language = {eng},
  medline-aid = {10.1006/nimg.2001.0948 [doi] ; S1053811901909486 [pii]},
  medline-ci = {Copyright 2001 Academic Press.},
  medline-da = {20011114},
  medline-dcom = {20020115},
  medline-edat = {2001/11/15 10:00},
  medline-fau = {Kruggel, F ; Herrmann, C S ; Wiggins, C J ; von
                   Cramon, D Y},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2002/01/16 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11707088},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2001 Dec;14(6):1327-36.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11707088},
  year = 2001
}
@ARTICLE{KLM+01,
  author = {Krakow, K. and Lemieux, L. and Messina, D. and Scott,
                   C. A. and Symms, M. R. and Duncan, J. S. and Fish, D.
                   R.},
  title = {Spatio-temporal imaging of focal interictal
                   epileptiform activity using {EEG}-triggered functional
                   {MRI}},
  journal = {Epileptic Disord},
  volume = {3},
  number = {2},
  pages = {67-74},
  abstract = {EEG-triggered, blood oxygen level-dependent functional
                   MRI (BOLD-fMRI) was used in 24 patients with
                   localization-related epilepsy and frequent interictal
                   epileptiform discharges (spikes) to identify those
                   brain areas involved in generating the spikes, and to
                   study the evolution of the BOLD signal change over
                   time. The location of the fMRI activation was compared
                   with the scalp EEG spike focus and the structural MR
                   abnormality. Twelve patients (50\%) had an fMRI
                   activation concordant with the EEG focus and structural
                   brain abnormalities where present (n = 7). In 2 other
                   patients, the fMRI activation was non-concordant with
                   electroclinical findings. The remaining 10 patients
                   (41.7\%) showed no significant fMRI activation. These
                   patients had significantly lower mean spike amplitudes
                   compared to those with positive fMRI results (p =
                   0.03). The time course of the BOLD response was studied
                   in 3 patients and this revealed a maximum signal change
                   1.5 to 7.5 sec after the spike. In conclusion,
                   EEG-triggered fMRI can directly identify the generators
                   of interictal epileptiform activity, with high spatial
                   resolution, in selected patients with frequent spikes.
                   The superior spatial resolution obtainable through
                   EEG-triggered fMRI may provide an additional
                   non-invasive tool in the presurgical evaluation of
                   patients with intractable focal seizures.},
  authoraddress = {MRI Unit, National Society for Epilepsy, Chalfont St.
                   Peter, Buckinghamshire SL9 0RJ, UK.},
  keywords = {Action Potentials/physiology ; Adolescent ; Adult ;
                   *Electroencephalography ; Epilepsies,
                   Partial/*pathology/*physiopathology ; Female ;
                   Hemodynamic Processes/physiology ; Human ; *Magnetic
                   Resonance Imaging ; Male ; Middle Aged ; Support,
                   Non-U.S. Gov't ; Temporal
                   Lobe/*pathology/*physiopathology},
  language = {eng},
  medline-da = {20010629},
  medline-dcom = {20010830},
  medline-edat = {2001/06/30 10:00},
  medline-fau = {Krakow, K ; Lemieux, L ; Messina, D ; Scott, C A ;
                   Symms, M R ; Duncan, J S ; Fish, D R},
  medline-is = {1294-9361},
  medline-jid = {100891853},
  medline-lr = {20031114},
  medline-mhda = {2001/08/31 10:01},
  medline-own = {NLM},
  medline-pl = {France},
  medline-pmid = {11431168},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Epileptic Disord 2001 Jun;3(2):67-74.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11431168},
  year = 2001
}
@ARTICLE{KMH+05,
  author = {Kilner, J.M. and Mattout, J. and Henson, R. and
                   Friston, K.J.},
  title = {Hemodynamic correlates of {EEG}: {A} heuristic.},
  journal = {Neuroimage},
  volume = {28},
  number = {1},
  pages = {280-6},
  abstract = {In this note we describe a heuristic, starting with a
                   dimensional analysis, which relates hemodynamic changes
                   to the spectral profile of ongoing EEG activity. In
                   brief, this analysis suggests that 'activation', as
                   indexed by increases in hemodynamic signals, should be
                   associated with a loss of power in lower EEG
                   frequencies, relative to higher frequencies. The fact
                   that activation is expressed in terms of frequency
                   (i.e., per second) is consistent with a dimensional
                   analysis in the sense that activations reflect the rate
                   of energy dissipation (per second). In this heuristic,
                   activation causes an acceleration of temporal dynamics
                   leading to (i) increased energy dissipation; (ii)
                   decreased effective membrane time constants; (iii)
                   increased effective coupling among neuronal ensembles;
                   and (iv) a shift in the EEG spectral profile to higher
                   frequencies. These predictions are consistent with
                   empirical observations of how changes in the EEG
                   spectrum are expressed hemodynamically. Furthermore,
                   the heuristic provides a simple measure of neuronal
                   activation based on spectral analyses of EEG.},
  authoraddress = {The Wellcome Department of Imaging Neuroscience,
                   Institute of Neurology, London, 12 Queen Square,
                   London, WC1N 3BG, UK.},
  language = {eng},
  medline-aid = {S1053-8119(05)00416-7 [pii] ;
                   10.1016/j.neuroimage.2005.06.008 [doi]},
  medline-da = {20051003},
  medline-dep = {20050714},
  medline-edat = {2005/07/19 09:00},
  medline-fau = {Kilner, J M ; Mattout, J ; Henson, R ; Friston, K J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2005/07/19 09:00},
  medline-own = {NLM},
  medline-phst = {2004/09/20 [received] ; 2005/05/17 [revised] ;
                   2005/06/07 [accepted] ; 2005/07/14 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16023377},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage 2005 Oct 15;28(1):280-6. Epub 2005 Jul 14.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16023377},
  year = 2005
}
@ARTICLE{KNM+01,
  author = {Kober, H. and Nimsky, C. and Moller, M. and
                   Hastreiter, P. and Fahlbusch, R. and Ganslandt, O.},
  title = {Correlation of sensorimotor activation with functional
                   magnetic resonance imaging and magnetoencephalography
                   in presurgical functional imaging: a spatial analysis},
  journal = {NeuroImage},
  volume = {14},
  number = {5},
  pages = {1214-1228},
  abstract = {In this study we investigated the spatial heterotopy
                   of MEG and fMRI localizations after sensory and motor
                   stimulation tasks. Both methods are frequently used to
                   study the topology of the primary and secondary motor
                   cortex, as well as a tool for presurgical brain
                   mapping. fMRI was performed with a 1.5T MR system,
                   using echo-planar imaging with a motor and a sensory
                   task. Somatosensory and motor evoked fields were
                   recorded with a biomagnetometer. fMRI activation was
                   determined with a cross-correlation analysis. MEG
                   source localization was performed with a single
                   equivalent current dipole model and a current density
                   localization approach. Distances between MEG and fMRI
                   activation sites were measured within the same
                   anatomical 3-D-MR image set. The central region could
                   be identified by MEG and fMRI in 33 of 34 cases.
                   However, MEG and fMRI localization results showed
                   significantly different activation sites for the motor
                   and sensory task with a distance of 10 and 15 mm,
                   respectively. This reflects the different
                   neurophysiological mechanisms: direct neuronal current
                   flow (MEG) and secondary changes in cerebral blood flow
                   and oxygenation level of activated versus non activated
                   brain structures (fMRI). The result of our study has
                   clinical implications when MEG and fMRI localizations
                   are used for pre- and intraoperative brain mapping.
                   Although both modalities are useful for the estimation
                   of the motor cortex, a single modality may err in the
                   exact topographical labeling of the motor cortex. In
                   some unclear cases a combination of both methods should
                   be used in order to avoid neurological deficits.},
  authoraddress = {Department of Neurosurgery and Neurocenter, University
                   Erlangen-Nurnberg, Erlangen, 91054, Germany.},
  keywords = {Adolescent ; Adult ; Aged ; Aged, 80 and over ; Brain
                   Neoplasms/physiopathology/*surgery ; Female ; Human ;
                   *Imaging, Three-Dimensional ; *Magnetic Resonance
                   Imaging ; *Magnetoencephalography ; Male ; Middle Aged
                   ; Motor Cortex/physiopathology/*surgery ; Somatosensory
                   Cortex/physiopathology/*surgery ; *Stereotaxic
                   Techniques ; Support, Non-U.S. Gov't ; *Surgery,
                   Computer-Assisted},
  language = {eng},
  medline-aid = {10.1006/nimg.2001.0909 [doi] ; S1053811901909097 [pii]},
  medline-ci = {Copyright 2001 Academic Press.},
  medline-da = {20011107},
  medline-dcom = {20020102},
  medline-edat = {2001/11/08 10:00},
  medline-fau = {Kober, H ; Nimsky, C ; Moller, M ; Hastreiter, P ;
                   Fahlbusch, R ; Ganslandt, O},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {2002/01/05 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11697953},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2001 Nov;14(5):1214-28.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11697953},
  year = 2001
}
@ARTICLE{KNV+02,
  author = {Kober, H. and Nimsky, C. and Vieth, J. and Fahlbusch,
                   R. and Ganslandt, O.},
  title = {Co-registration of function and anatomy in frameless
                   stereotaxy by contour fitting},
  journal = {Stereotact Funct Neurosurg},
  volume = {79},
  number = {3-4},
  pages = {272-283},
  abstract = {We investigated a co-registration algorithm using a
                   contour-fitting procedure to integrate functional data
                   from magnetoencephalography (MEG) and functional
                   magnetic resonance imaging (fMRI) for frameless
                   stereotaxy. In fMRI the shape of the head was
                   reconstructed from anatomical images, in MEG it was
                   scanned using an electromagnetic sensor position
                   indicator. Functional information was transferred to
                   the 3D-MR image set used for frameless stereotaxy by
                   fitting the digitized (MEG) and reconstructed head
                   shape (fMRI) to the 3D-MR images. The mean residual
                   error of the contour fit was 2.3 mm for the MEG and 1.3
                   mm for the fMRI registration. According to computer
                   simulations, the achievable transformation error is
                   0.75 and 0.5 mm, respectively. This method enables
                   independent recording of functional and anatomical
                   measurements with a co-registration accuracy better
                   than 2 mm.},
  authoraddress = {Department of Neurosurgery, University
                   Erlangen-Nurnberg, Erlangen, Germany.},
  keywords = {Brain/anatomy & histology/*surgery ; Human ; Imaging,
                   Three-Dimensional ; Magnetic Resonance Imaging/*methods
                   ; *Magnetoencephalography ; Models, Biological ;
                   Neuronavigation/*methods ; Surgery,
                   Computer-Assisted/methods},
  language = {eng},
  medline-aid = {10.1159/000072396 [doi] ; SFN20020793\_4272 [pii]},
  medline-ci = {Copyright 2002 S. Karger AG, Basel},
  medline-da = {20030731},
  medline-dcom = {20031001},
  medline-edat = {2003/08/02 05:00},
  medline-fau = {Kober, Helmut ; Nimsky, Christopher ; Vieth, Jurgen ;
                   Fahlbusch, Rudolf ; Ganslandt, Oliver},
  medline-is = {1011-6125},
  medline-jid = {8902881},
  medline-mhda = {2003/10/02 05:00},
  medline-own = {NLM},
  medline-pl = {Switzerland},
  medline-pmid = {12890986},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Stereotact Funct Neurosurg 2002;79(3-4):272-83.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12890986},
  year = 2002
}
@ARTICLE{KRO+04,
  author = {Kim, D. S. and Ronen, I. and Olman, C. and Kim, S. G.
                   and Ugurbil, K. and Toth, L. J.},
  title = {Spatial relationship between neuronal activity and
                   {BOLD} functional {MRI}.},
  journal = {Neuroimage},
  volume = {21},
  number = {3},
  pages = {876-85},
  abstract = {Despite the ubiquitous use of functional magnetic
                   resonance imaging (fMRI), the extent to which the
                   magnitude and spatial scale of the fMRI signal
                   correlates with neuronal activity is poorly understood.
                   In this study, we directly compared single and
                   multiunit neuronal activity with blood oxygenation
                   level-dependent (BOLD) fMRI responses across a large
                   area of the cat area 18. Our data suggest that at the
                   scale of several millimeters, the BOLD contrast
                   correlates linearly with the underlying neuronal
                   activity. At the level of individual electrode
                   recording sites, however, the correlation between the
                   two signals varied substantially. We conclude from our
                   study that T(2)*-based positive BOLD signals are a
                   robust predictor for neuronal activity only at
                   supra-millimeter spatial scales.},
  authoraddress = {Center for Magnetic Resonance Research, University of
                   Minnesota Medical School, Minneapolis, MN 55455, USA.
                   dskim@bu.edu},
  keywords = {Animals ; Brain/cytology/*physiology ; Cats ; Cerebral
                   Cortex/cytology/physiology ; Cerebrovascular
                   Circulation/physiology ; Electrodes, Implanted ;
                   Magnetic Resonance Imaging ; Neurons/*physiology ;
                   Oxygen/*blood ; Photic Stimulation ; Research Support,
                   Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S. ;
                   Visual Cortex/cytology/physiology},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.10.018 [doi] ;
                   S1053811903006694 [pii]},
  medline-da = {20040309},
  medline-dcom = {20040503},
  medline-edat = {2004/03/10 05:00},
  medline-fau = {Kim, Dae-Shik ; Ronen, Itamar ; Olman, Cheryl ; Kim,
                   Seong-Gi ; Ugurbil, Kamil ; Toth, Louis J},
  medline-gr = {MH57180/MH/NIMH ; MH67530/MH/NIMH ; NS38295/NS/NINDS ;
                   RR08079/RR/NCRR},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-lr = {20041117},
  medline-mhda = {2004/05/05 05:00},
  medline-own = {NLM},
  medline-phst = {2003/05/21 [received] ; 2003/10/07 [revised] ;
                   2003/10/14 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15006654},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2004 Mar;21(3):876-85.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15006654},
  year = 2004
}
@ARTICLE{KWH+00,
  author = {Kruggel, F. and Wiggins, C. J. and Herrmann, C. S. and
                   von Cramon, D. Y.},
  title = {Recording of the event-related potentials during
                   functional {MRI} at 3.0 {T}esla field strength},
  journal = {Magn Reson Med},
  volume = {44},
  number = {2},
  pages = {277-282},
  abstract = {The feasibility of recording event-related potentials
                   (ERP) during functional MRI (fMRI) scanning was
                   studied. Using an alternating checkerboard stimulus in
                   a blocked presentation, visually evoked potentials were
                   obtained with their expected configuration and
                   latencies. A clustered echoplanar imaging protocol was
                   applied to observe the hemodynamic response due to the
                   visual stimulus interleaved with measuring ERPs.
                   Influences of the electrode/amplifier set up on MRI
                   scanning and the scanning process on the recording of
                   electrophysiological signals are reported and
                   discussed. Artifacts overlaid on the
                   electrophysiological recordings were corrected by post
                   hoc filtering methods presented here. Implications and
                   limitations of conducting combined ERP/fMRI experiments
                   using higher-level cognitive stimuli are discussed.
                   Magn Reson Med 44:277-282, 2000.},
  authoraddress = {Max-Planck-Institute of Cognitive Neuroscience
                   Stephanstrasse 1, 04103 Leipzig, Germany.
                   kruggel@cns.mpg.de},
  keywords = {Adult ; Echo-Planar Imaging ; Electrodes ;
                   *Electroencephalography ; Evoked Potentials,
                   Visual/*physiology ; Feasibility Studies ; Female ;
                   Human ; Image Processing, Computer-Assisted ; Magnetic
                   Resonance Imaging/*methods ; Male ; Signal Processing,
                   Computer-Assisted},
  language = {eng},
  medline-aid = {10.1002/1522-2594(200008)44:2<277::AID-MRM15>3.0.CO;2-X
                   [pii]},
  medline-ci = {Copyright 2000 Wiley-Liss, Inc.},
  medline-da = {20001019},
  medline-dcom = {20001019},
  medline-edat = {2000/08/05 11:00},
  medline-fau = {Kruggel, F ; Wiggins, C J ; Herrmann, C S ; von
                   Cramon, D Y},
  medline-is = {0740-3194},
  medline-jid = {8505245},
  medline-lr = {20001218},
  medline-mhda = {2000/10/21 11:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10918327},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Magn Reson Med 2000 Aug;44(2):277-82.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10918327},
  year = 2000
}
@ARTICLE{KWS+99,
  author = {Krakow, K. and Woermann, F. G. and Symms, M. R. and
                   Allen, P. J. and Lemieux, L. and Barker, G. J. and
                   Duncan, J. S. and Fish, D. R.},
  title = {E{EG}-triggered functional {MRI} of interictal
                   epileptiform activity in patients with partial seizures},
  journal = {Brain},
  volume = {122},
  number = {9},
  pages = {1679-1688},
  abstract = {EEG-triggered functional MRI (fMRI) offers the
                   potential to localize the generators of scalp EEG
                   events, such as interictal epileptiform discharges,
                   using a biological measurement as opposed to relying
                   solely on modelling techniques. Although recent studies
                   have demonstrated these possibilities in a small number
                   of patients, wider application has been limited by
                   concerns about patient safety, severe problems due to
                   pulse-related artefact obscuring the EEG trace, and
                   lack of reproducibility data. We have systematically
                   studied and resolved the issues of patient safety and
                   pulse artefact and now report the application of the
                   technique in 24 experiments in 10 consecutive patients
                   with localization-related epilepsy and frequent
                   interictal epileptiform discharges (spikes or spike
                   wave). At least two experiments were performed for each
                   patient. In each experiment, 10- or 20-slice snapshot
                   gradient-echo planar images were acquired approximately
                   3.5 s after a single typical epileptiform discharge
                   (activation image) and in the absence of discharges
                   (control image). Between 21 and 50 epileptiform
                   discharges were sampled in each experiment. The
                   significance of functional activation was tested using
                   the t test at 95\% confidence on a pixel-by-pixel
                   basis. Six of the 10 patients showed reproducible focal
                   changes of the blood oxygen level-dependent (BOLD)
                   signal, which occurred in close spatial relationship to
                   the maximum of the epileptiform discharges in the
                   concurrent EEG. No reproducible focal BOLD signal
                   changes were observed in the remaining four patients.
                   In conclusion, EEG-triggered fMRI is now a sufficiently
                   developed technique to be more widely used in clinical
                   studies, demonstrating that it can reproducibly
                   localize the brain areas involved in the generation of
                   spikes and spike wave in epilepsy patients with
                   frequent interictal discharges.},
  authoraddress = {The Epilepsy Research Group and NMR Research Unit,
                   Department of Clinical Neurology, Institute of
                   Neurology, London, United Kingdom.
                   kkrakow@ion.ucl.ac.uk},
  keywords = {Adult ; Brain/pathology/*physiopathology ; Brain
                   Mapping ; Electroencephalography/*methods ; Epilepsies,
                   Partial/*diagnosis/*physiopathology ; Female ; Human ;
                   Magnetic Resonance Imaging/*methods ; Male ; Middle
                   Aged ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-da = {19991012},
  medline-dcom = {19991012},
  medline-edat = {1999/09/01},
  medline-fau = {Krakow, K ; Woermann, F G ; Symms, M R ; Allen, P J ;
                   Lemieux, L ; Barker, G J ; Duncan, J S ; Fish, D R},
  medline-is = {0006-8950},
  medline-jid = {0372537},
  medline-lr = {20031114},
  medline-mhda = {1999/09/01 00:01},
  medline-own = {NLM},
  medline-pl = {ENGLAND},
  medline-pmid = {10468507},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {AIM ; IM},
  medline-so = {Brain 1999 Sep;122 ( Pt 9):1679-88.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10468507},
  year = 1999
}
@ARTICLE{KWW+99,
  author = {Krakow, K. and Wieshmann, U. C. and Woermann, F. G.
                   and Symms, M. R. and McLean, M. A. and Lemieux, L. and
                   Allen, P. J. and Barker, G. J. and Fish, D. R. and
                   Duncan, J. S.},
  title = {Multimodal {MR} imaging: functional, diffusion tensor,
                   and chemical shift imaging in a patient with
                   localization-related epilepsy},
  journal = {Epilepsia},
  volume = {40},
  number = {10},
  pages = {1459-1462},
  abstract = {PURPOSE: To demonstrate the integration of
                   complementary functional and structural data acquired
                   with magnetic resonance imaging (MRI) in a patient with
                   localization-related epilepsy. METHODS: We studied a
                   patient with partial and secondarily generalized
                   seizures and a hemiparesis due to a malformation of
                   cortical development (MCD) in the right hemisphere by
                   using EEG-triggered functional MRI (fMRI), diffusion
                   tensor imaging (DTI), and chemical shift imaging (CSI).
                   RESULTS: fMRI revealed significant changes in regional
                   blood oxygenation associated with interictal
                   epileptiform discharges within the MCD. DTI showed a
                   heterogeneous microstructure of the MCD with reduced
                   fractional anisotropy, a high mean diffusivity, and
                   displacement of myelinated tracts. CSI demonstrated low
                   N-acetyl aspartate (NAA) concentrations in parts of the
                   MCD. CONCLUSIONS: The applied MR methods described
                   functional, microstructural, and biochemical
                   characteristics of the epileptogenic tissue that cannot
                   be obtained with other noninvasive means and thus
                   improve the understanding of the pathophysiology of
                   epilepsy.},
  authoraddress = {Department of Clinical Neurology, Institute of
                   Neurology, University College London, England, UK.
                   kkrakow@ion.ucl.ac.uk},
  keywords = {Adult ; Anisotropy ; Aspartic Acid/analogs &
                   derivatives/analysis ; Cerebral
                   Cortex/abnormalities/chemistry/physiopathology ;
                   Electroencephalography/statistics & numerical data ;
                   Epilepsies, Partial/blood/*diagnosis/physiopathology ;
                   Human ; Magnetic Resonance Imaging/methods/*statistics
                   & numerical data ; Male ; Nervous System
                   Malformations/diagnosis ; Oxygen/blood},
  language = {eng},
  medline-da = {19991022},
  medline-dcom = {19991022},
  medline-edat = {1999/10/21},
  medline-fau = {Krakow, K ; Wieshmann, U C ; Woermann, F G ; Symms, M
                   R ; McLean, M A ; Lemieux, L ; Allen, P J ; Barker, G J
                   ; Fish, D R ; Duncan, J S},
  medline-is = {0013-9580},
  medline-jid = {2983306R},
  medline-lr = {20031114},
  medline-mhda = {1999/10/21 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10528945},
  medline-pst = {ppublish},
  medline-pt = {Case Reports ; Journal Article},
  medline-rn = {56-84-8 (Aspartic Acid) ; 7782-44-7 (Oxygen) ;
                   997-55-7 (N-acetylaspartate)},
  medline-sb = {IM},
  medline-so = {Epilepsia 1999 Oct;40(10):1459-62.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10528945},
  year = 1999
}
@ARTICLE{KYP04,
  author = {Kim, K. H. and Yoon, H. W. and Park, H. W.},
  title = {Improved ballistocardiac artifact removal from the
                   electroencephalogram recorded in f{MRI}.},
  journal = {J Neurosci Methods},
  volume = {135},
  number = {1-2},
  pages = {193-203},
  abstract = {The simultaneous recording of electroencephalogram
                   (EEG) and functional magnetic resonance image (fMRI) is
                   a promising tool that is capable of providing high
                   spatiotemporal brain mapping, with each modality
                   supplying complementary information. One of the major
                   barriers to obtain high-quality simultaneous EEG/fMRI
                   data is that pulsatile activity due to the heartbeat
                   induces significant artifacts in the EEG. The purpose
                   of this study was to develop a novel algorithm for
                   removing heartbeat artifact, thus overcoming problems
                   associated with previous methods. Our method consists
                   of a mean artifact wave form subtraction, the selective
                   removal of wavelet coefficients, and a recursive
                   least-square adaptive filtering. The recursive
                   least-square adaptive filtering operates without
                   dedicated sensor for the reference signal, and only
                   when the mean subtraction and wavelet-based noise
                   removal is not satisfactory. The performance of our
                   system has been assessed using simulated data based on
                   experimental data of various spectral characteristics,
                   and actual experimental data of alpha-wave-dominant
                   normal EEG and epileptic EEG.},
  authoraddress = {Department of Biomedical Engineering, Yonsei
                   University, 234 Maeji-ri, Heungup-myun, Wonju,
                   Kangwon-do 220-710, South Korea. khkim@ieee.org},
  keywords = {Adult ; *Algorithms ; *Artifacts ;
                   Ballistocardiography/methods ; Brain/*physiology ;
                   Brain Mapping ; Comparative Study ;
                   Electroencephalography/*methods ;
                   Epilepsy/physiopathology ; Female ; Heart
                   Rate/*physiology ; Humans ; Image Processing,
                   Computer-Assisted ; Magnetic Resonance Imaging/*methods
                   ; Male ; Middle Aged ; Research Support, Non-U.S. Gov't
                   ; Signal Processing, Computer-Assisted ; Subtraction
                   Technique ; Time Factors},
  language = {eng},
  medline-aid = {10.1016/j.jneumeth.2003.12.016 [doi] ;
                   S0165027003004370 [pii]},
  medline-da = {20040315},
  medline-dcom = {20040607},
  medline-edat = {2004/03/17 05:00},
  medline-fau = {Kim, Kyung Hwan ; Yoon, Hyo Woon ; Park, Hyun Wook},
  medline-is = {0165-0270 (Print)},
  medline-jid = {7905558},
  medline-jt = {Journal of neuroscience methods.},
  medline-lr = {20041117},
  medline-mhda = {2004/06/21 10:00},
  medline-own = {NLM},
  medline-phst = {2003/08/19 [received] ; 2003/12/22 [revised] ;
                   2003/12/22 [accepted]},
  medline-pl = {Netherlands},
  medline-pmid = {15020103},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {J Neurosci Methods. 2004 May 30;135(1-2):193-203.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15020103},
  year = 2004
}
@ARTICLE{Kim05,
  author = {Kim, D.S.},
  title = {The cutting edge of f{MRI} and high-field f{MRI}.},
  journal = {Int Rev Neurobiol},
  volume = {66},
  pages = {147-66},
  authoraddress = {Center for Biomedical Imaging, Boston University
                   School of Medicine Boston, Massachusetts 02118, USA.},
  keywords = {Brain/blood supply/*physiology ; Humans ; Magnetic
                   Resonance Imaging/*methods/*trends ; Oxygen/blood ;
                   Research Support, N.I.H., Extramural ; Research
                   Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S0074-7742(05)66005-9 [pii] ;
                   10.1016/S0074-7742(05)66005-9 [doi]},
  medline-da = {20060102},
  medline-dcom = {20060118},
  medline-edat = {2006/01/03 09:00},
  medline-fau = {Kim, Dae-Shik},
  medline-gr = {MH61937/MH/NIMH ; MH67530/MH/NIMH ; RR08079/RR/NCRR},
  medline-is = {0074-7742 (Print)},
  medline-jid = {0374740},
  medline-jt = {International review of neurobiology.},
  medline-mhda = {2006/01/19 09:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {16387203},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review},
  medline-pubm = {Print},
  medline-rf = {72},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Int Rev Neurobiol. 2005;66:147-66.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16387203},
  year = 2005
}
@ARTICLE{LAF+97,
  author = {Lemieux, L. and Allen, P. J. and Franconi, F. and
                   Symms, M. R. and Fish, D. R.},
  title = {Recording of {EEG} during f{MRI} experiments: patient
                   safety},
  journal = {Magn Reson Med},
  volume = {38},
  number = {6},
  pages = {943-952},
  abstract = {The acquisition of electroencephalograms (EEG) during
                   functional magnetic resonance imaging (fMRI)
                   experiments raises important practical issues of
                   patient safety. The presence of electrical wires
                   connected to the patient in rapidly changing magnetic
                   fields results in currents flowing through the patient
                   due to induced electromotive forces (EMF), by three
                   possible mechanisms: fixed loop in rapidly changing
                   gradient fields; fixed loop in a RF electromagnetic
                   field; moving loop in the static magnetic field.
                   RF-induced EMFs were identified as the most important
                   potential hazard. We calculated the minimum value of
                   current-limiting resistance to be fitted in each EEG
                   electrode lead for a representative worst case loop,
                   and measured RF magnetic field intensity and heating in
                   a specific type of current-limiting resistors. The
                   results show that electrode resistance should be > or =
                   13 k(omega) for our setup. The methodology presented is
                   general and can be useful for other centers.},
  authoraddress = {Department of Clinical Neurology, Institute of
                   Neurology, London, United Kingdom.},
  keywords = {*Electroencephalography ; Electromagnetic
                   Fields/adverse effects ; Human ; *Magnetic Resonance
                   Imaging ; Models, Theoretical ; Safety ; Support,
                   Non-U.S. Gov't ; Temperature},
  language = {eng},
  medline-da = {19980128},
  medline-dcom = {19980128},
  medline-edat = {1997/12/24},
  medline-fau = {Lemieux, L ; Allen, P J ; Franconi, F ; Symms, M R ;
                   Fish, D R},
  medline-is = {0740-3194},
  medline-jid = {8505245},
  medline-lr = {20001218},
  medline-mhda = {1997/12/24 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9402196},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Magn Reson Med 1997 Dec;38(6):943-52.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9402196},
  year = 1997
}
@ARTICLE{LBD98,
  author = {Liu, A. K. and Belliveau, J. W. and Dale, A. M.},
  title = {Spatiotemporal imaging of human brain activity using
                   functional {MRI} constrained magnetoencephalography
                   data: {M}onte {C}arlo simulations},
  journal = {Proc Natl Acad Sci U S A},
  volume = {95},
  number = {15},
  pages = {8945-8950},
  abstract = {The goal of our research is to develop an experimental
                   and analytical framework for spatiotemporal imaging of
                   human brain function. Preliminary studies suggest that
                   noninvasive spatiotemporal maps of cerebral activity
                   can be produced by combining the high spatial
                   resolution (millimeters) of functional MRI (fMRI) with
                   the high temporal resolution (milliseconds) of
                   electroencephalography (EEG) and magnetoencephalography
                   (MEG). Although MEG and EEG are sensitive to
                   millisecond changes in mental activity, the ability to
                   resolve source localization and timing is limited by
                   the ill-posed "inverse" problem. We conducted Monte
                   Carlo simulations to evaluate the use of MRI
                   constraints in a linear estimation inverse procedure,
                   where fMRI weighting, cortical location and
                   orientation, and sensor noise statistics were
                   realistically incorporated. An error metric was
                   computed to quantify the effects of fMRI invisible
                   ("missing") sources, "extra" fMRI sources, and cortical
                   orientation errors. Our simulation results demonstrate
                   that prior anatomical and functional information from
                   MRI can be used to regularize the EEG/MEG inverse
                   problem, giving an improved solution with high spatial
                   and temporal resolution. An fMRI weighting of
                   approximately 90\% was determined to provide the best
                   compromise between separation of activity from
                   correctly localized sources and minimization of error
                   caused by missing sources. The accuracy of the estimate
                   was relatively independent of the number and extent of
                   the sources, allowing for incorporation of
                   physiologically realistic multiple distributed sources.
                   This linear estimation method provides an
                   operator-independent approach for combining information
                   from fMRI, MEG, and EEG and represents a significant
                   advance over traditional dipole modeling.},
  authoraddress = {Massachusetts General Hospital NMR Center, Building
                   149, Room 2301, 13th Street, Charlestown, MA 02129,
                   USA.},
  keywords = {Brain/*physiopathology/radiography ; Human ; Magnetic
                   Resonance Imaging ; Magnetoencephalography ; Monte
                   Carlo Method ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-da = {19980820},
  medline-dcom = {19980820},
  medline-edat = {1998/07/22},
  medline-fau = {Liu, A K ; Belliveau, J W ; Dale, A M},
  medline-is = {0027-8424},
  medline-jid = {7505876},
  medline-lr = {20001218},
  medline-mhda = {1998/07/22 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9671784},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Proc Natl Acad Sci U S A 1998 Jul 21;95(15):8945-50.},
  medline-stat = {completed},
  year = 1998
}
@ARTICLE{LBG+06,
  author = {Lu, Y. and Bagshaw, A. P. and Grova, C. and Kobayashi,
                   E. and Dubeau, F. and Gotman, J.},
  title = {Using voxel-specific hemodynamic response function in
                   {EEG}-f{MRI} data analysis.},
  journal = {Neuroimage},
  volume = {32},
  number = {1},
  pages = {238-47},
  abstract = {Most existing analytical techniques for EEG-fMRI data
                   need specific assumptions about the hemodynamic
                   response function (HRF). These assumptions may not be
                   appropriate when the HRF varies from subject to subject
                   or from region to region. In this article, we introduce
                   a deconvolution method for EEG-fMRI activation
                   detection, which can be implemented with voxel-specific
                   HRFs. A comparison of performance is made between three
                   fixed HRFs and the deconvolution method under the
                   framework of the general linear model. The main results
                   are as follows: (1) the volume of detected regions from
                   the deconvolved HRFs is larger. (2) In some subjects,
                   the deconvolution technique can find areas of
                   activation that have not been detected with the three
                   fixed HRFs at our threshold of significance. (3)
                   Deconvolution obtained higher adjusted coefficients of
                   multiple determination compared to those obtained with
                   the three fixed HRFs. The results suggest that the
                   fixed HRF methods may not be the most appropriate for
                   the analysis of epileptic activity with EEG-fMRI, and
                   the deconvolution method may be a better choice.},
  authoraddress = {Montreal Neurological Institute, McGill University,
                   3801 University Street, Montreal, Quebec, Canada H3A
                   2B4.},
  keywords = {Brain/*anatomy & histology/pathology/*physiology ;
                   *Brain Mapping ; Cerebrovascular
                   Circulation/*physiology ; Comparative Study ;
                   *Electroencephalography ; Epilepsies,
                   Partial/pathology/*physiopathology ;
                   Epilepsy/classification/pathology/physiopathology ;
                   Hemodynamic Processes/*physiology ; Humans ; *Magnetic
                   Resonance Imaging ; Reference Values ; Research
                   Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1053-8119(05)02498-5 [pii] ;
                   10.1016/j.neuroimage.2005.11.040 [doi]},
  medline-da = {20060724},
  medline-dcom = {20060915},
  medline-dep = {20060613},
  medline-edat = {2006/06/16 09:00},
  medline-fau = {Lu, Yingli ; Bagshaw, Andrew P ; Grova, Christophe ;
                   Kobayashi, Eliane ; Dubeau, Francois ; Gotman, Jean},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2006/09/16 09:00},
  medline-own = {NLM},
  medline-phst = {2005/06/24 [received] ; 2005/11/21 [revised] ;
                   2005/11/28 [accepted] ; 2006/06/13 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16774839},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 Aug 1;32(1):238-47. Epub 2006 Jun 13.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16774839},
  year = 2006
}
@ARTICLE{LBP+00,
  author = {Lazeyras, F. and Blanke, O. and Perrig, S. and Zimine,
                   I. and Golay, X. and Delavelle, J. and Michel, C. M.
                   and de Tribolet, N. and Villemure, J. G. and Seeck, M.},
  title = {E{EG}-triggered functional {MRI} in patients with
                   pharmacoresistant epilepsy},
  journal = {J Magn Reson Imaging},
  volume = {12},
  number = {1},
  pages = {177-185},
  abstract = {Functional magnetic resonance imaging (fMRI) triggered
                   by scalp electroencephalography (EEG) recordings has
                   become a promising new tool for noninvasive epileptic
                   focus localization. Studies to date have shown that it
                   can be used safely and that highly localized
                   information can be obtained. So far, no reports using
                   comprehensive clinical information and/or long-term
                   follow-up after epilepsy surgery in a larger patient
                   group have been given that would allow a valuable
                   judgment of the utility of this technique. Here, the
                   results of 11 patients with EEG-triggered fMRI exams
                   who also underwent presurgical evaluation of their
                   epilepsy are given. In most patients we were able to
                   record good quality EEG inside the magnet, allowing us
                   to trigger fMRI acquisition by interictal discharges.
                   The fMRI consisted of echoplanar multislice acquisition
                   permitting a large anatomical coverage of the patient's
                   brain. In 8 of the 11 patients the exam confirmed
                   clinical diagnosis, either by the presence (n = 7) or
                   absence (n = 1) of focal signal enhancement. In six
                   patients, intracranial recordings were carried out, and
                   in five of them, the epileptogenic zone as determined
                   by fMRI was confirmed. Limitations were encountered a)
                   when the focus was too close to air cavities; b) if an
                   active epileptogenic focus was absent; and c) if only
                   reduced cooperation with respect to body movements was
                   provided by the patient. We conclude that EEG-triggered
                   fMRI is a safe and powerful noninvasive tool that
                   improves the diagnostic value of MRI by localizing the
                   epileptic focus precisely.},
  authoraddress = {Department of Radiology, University Hospitals of
                   Geneva, Switzerland. francois.lazeyras@hcuge.ch},
  keywords = {Adolescent ; Adult ; Anticonvulsants/therapeutic use ;
                   Brain Mapping/methods ; Drug Resistance ;
                   Electroencephalography/*methods ;
                   Epilepsy/*diagnosis/drug therapy/surgery ; Female ;
                   Human ; Magnetic Resonance Imaging/*methods ; Male ;
                   Preoperative Care ; Sensitivity and Specificity ;
                   Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1002/1522-2586(200007)12:1<177::AID-JMRI20>3.0.CO;2-3
                   [pii]},
  medline-da = {20001205},
  medline-dcom = {20001205},
  medline-edat = {2000/08/10 11:00},
  medline-fau = {Lazeyras, F ; Blanke, O ; Perrig, S ; Zimine, I ;
                   Golay, X ; Delavelle, J ; Michel, C M ; de Tribolet, N
                   ; Villemure, J G ; Seeck, M},
  medline-is = {1053-1807},
  medline-jid = {9105850},
  medline-lr = {20021101},
  medline-mhda = {2001/02/28 10:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10931578},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-rn = {0 (Anticonvulsants)},
  medline-sb = {IM},
  medline-so = {J Magn Reson Imaging 2000 Jul;12(1):177-85.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10931578},
  year = 2000
}
@ARTICLE{LDB02,
  author = {Liu, A. K. and Dale, A. M. and Belliveau, J. W.},
  title = {Monte {C}arlo simulation studies of {EEG} and {MEG}
                   localization accuracy},
  journal = {Hum Brain Mapp},
  volume = {16},
  number = {1},
  pages = {47-62},
  abstract = {Both electroencephalography (EEG) and
                   magnetoencephalography (MEG) are currently used to
                   localize brain activity. The accuracy of source
                   localization depends on numerous factors, including the
                   specific inverse approach and source model, fundamental
                   differences in EEG and MEG data, and the accuracy of
                   the volume conductor model of the head (i.e., the
                   forward model). Using Monte Carlo simulations, this
                   study removes the effect of forward model errors and
                   theoretically compares the use of EEG alone, MEG alone,
                   and combined EEG/MEG data sets for source localization.
                   Here, we use a linear estimation inverse approach with
                   a distributed source model and a realistic forward head
                   model. We evaluated its accuracy using the crosstalk
                   and point spread metrics. The crosstalk metric for a
                   specified location on the cortex describes the amount
                   of activity incorrectly localized onto that location
                   from other locations. The point spread metric provides
                   the complementary measure: for that same location, the
                   point spread describes the mis-localization of activity
                   from that specified location to other locations in the
                   brain. We also propose and examine the utility of a
                   "noise sensitivity normalized" inverse operator. Given
                   our particular forward and inverse models, our results
                   show that 1) surprisingly, EEG localization is more
                   accurate than MEG localization for the same number of
                   sensors averaged over many source locations and
                   orientations; 2) as expected, combining EEG with MEG
                   produces the best accuracy for the same total number of
                   sensors; 3) the noise sensitivity normalized inverse
                   operator improves the spatial resolution relative to
                   the standard linear estimation operator; and 4) use of
                   an a priori fMRI constraint universally reduces both
                   crosstalk and point spread.},
  authoraddress = {Massachusetts General Hospital, NMR Center, Building
                   149, 13th Street, Charlestown, MA 02129, USA.},
  keywords = {*Algorithms ; *Artifacts ; Bayes Theorem ;
                   Brain/anatomy & histology/physiology ; Brain
                   Mapping/*methods ; Electrodes/standards ;
                   Electroencephalography/*methods ; Human ; Image
                   Processing, Computer-Assisted/*methods ;
                   Magnetoencephalography/*methods ; Models, Neurological
                   ; *Monte Carlo Method ; Reproducibility of Results ;
                   Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {10.1002/hbm.10024 [pii]},
  medline-ci = {Copyright 2002 Wiley-Liss, Inc.},
  medline-da = {20020228},
  medline-dcom = {20020621},
  medline-edat = {2002/03/01 10:00},
  medline-fau = {Liu, Arthur K ; Dale, Anders M ; Belliveau, John W},
  medline-gr = {P41-RR 14075/RR/NCRR ; R01-NS 37462/NS/NINDS ; R01-NS
                   39581/NS/NINDS ; R01-RR 13609/RR/NCRR},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-mhda = {2002/06/22 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11870926},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 2002 May;16(1):47-62.},
  medline-stat = {completed},
  year = 2002
}
@ARTICLE{LDM+06,
  author = {Liston, A. D. and De Munck, J. C. and Hamandi, K. and
                   Laufs, H. and Ossenblok, P. and Duncan, J. S. and
                   Lemieux, L.},
  title = {Analysis of {EEG}-f{MRI} data in focal epilepsy based
                   on automated spike classification and {S}ignal {S}pace
                   {P}rojection.},
  journal = {Neuroimage},
  abstract = {Simultaneous acquisition of EEG and fMRI data enables
                   the investigation of the hemodynamic correlates of
                   interictal epileptiform discharges (IEDs) during the
                   resting state in patients with epilepsy. This paper
                   addresses two issues: (1) the semi-automation of IED
                   classification in statistical modelling for fMRI
                   analysis and (2) the improvement of IED detection to
                   increase experimental fMRI efficiency. For patients
                   with multiple IED generators, sensitivity to
                   IED-correlated BOLD signal changes can be improved when
                   the fMRI analysis model distinguishes between IEDs of
                   differing morphology and field. In an attempt to reduce
                   the subjectivity of visual IED classification, we
                   implemented a semi-automated system, based on the
                   spatio-temporal clustering of EEG events. We illustrate
                   the technique's usefulness using EEG-fMRI data from a
                   subject with focal epilepsy in whom 202 IEDs were
                   visually identified and then clustered
                   semi-automatically into four clusters. Each cluster of
                   IEDs was modelled separately for the purpose of fMRI
                   analysis. This revealed IED-correlated BOLD activations
                   in distinct regions corresponding to three different
                   IED categories. In a second step, Signal Space
                   Projection (SSP) was used to project the scalp EEG onto
                   the dipoles corresponding to each IED cluster. This
                   resulted in 123 previously unrecognised IEDs, the
                   inclusion of which, in the General Linear Model (GLM),
                   increased the experimental efficiency as reflected by
                   significant BOLD activations. We have also shown that
                   the detection of extra IEDs is robust in the face of
                   fluctuations in the set of visually detected IEDs. We
                   conclude that automated IED classification can result
                   in more objective fMRI models of IEDs and significantly
                   increased sensitivity.},
  authoraddress = {Clinical and Experimental Epilepsy, Institute of
                   Neurology, UC, MRI Unit, NSE, Chesham Lane, Chalfont
                   St. Peter, Buckinghamshire SL9 0RJ, UK.},
  language = {ENG},
  medline-aid = {S1053-8119(06)00093-0 [pii] ;
                   10.1016/j.neuroimage.2006.01.040 [doi]},
  medline-da = {20060320},
  medline-dep = {20060315},
  medline-edat = {2006/03/21 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2006/03/21 09:00},
  medline-own = {NLM},
  medline-phst = {2005/09/23 [received] ; 2005/12/19 [revised] ;
                   2006/01/29 [accepted]},
  medline-pmid = {16545967},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2006 Mar 15;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16545967},
  year = 2006
}
@ARTICLE{LES+03,
  author = {Liebenthal, E. and Ellingson, M. L. and Spanaki, M. V.
                   and Prieto, T. E. and Ropella, K. M. and Binder, J. R.},
  title = {Simultaneous {ERP} and f{MRI} of the auditory cortex
                   in a passive oddball paradigm},
  journal = {NeuroImage},
  volume = {19},
  number = {4},
  pages = {1395-1404},
  abstract = {Infrequent occurrences of a deviant sound within a
                   sequence of repetitive standard sounds elicit the
                   automatic mismatch negativity (MMN) event-related
                   potential (ERP). The main MMN generators are located in
                   the superior temporal cortex, but their number, precise
                   location, and temporal sequence of activation remain
                   unclear. In this study, ERP and functional magnetic
                   resonance imaging (fMRI) data were obtained
                   simultaneously during a passive frequency oddball
                   paradigm. There were three conditions, a STANDARD, a
                   SMALL deviant, and a LARGE deviant. A clustered image
                   acquisition technique was applied to prevent
                   contamination of the fMRI data by the acoustic noise of
                   the scanner and to limit contamination of the
                   electroencephalogram (EEG) by the gradient-switching
                   artifact. The ERP data were used to identify areas in
                   which the blood oxygenation (BOLD) signal varied with
                   the magnitude of the negativity in each condition. A
                   significant ERP MMN was obtained, with larger peaks to
                   LARGE deviants and with frontocentral scalp
                   distribution, consistent with the MMN reported outside
                   the magnetic field. This result validates the
                   experimental procedures for simultaneous ERP/fMRI of
                   the auditory cortex. Main foci of increased BOLD signal
                   were observed in the right superior temporal gyrus
                   [STG; Brodmann area (BA) 22] and right superior
                   temporal plane (STP; BA 41 and 42). The imaging results
                   provide new information supporting the idea that
                   generators in the right lateral aspect of the STG are
                   implicated in processes of frequency deviant detection,
                   in addition to generators in the right and left STP.},
  authoraddress = {Department of Neurology, Medical College of Wisconsin,
                   8701 Watertown Plank Road, Milwaukee, WI 53226, USA.
                   einatl@mcw.edu},
  keywords = {Adult ; Arousal/physiology ; Attention/*physiology ;
                   Auditory Cortex/*physiology ; Brain Mapping ;
                   Contingent Negative Variation/*physiology ;
                   *Electroencephalography ; Evoked Potentials,
                   Auditory/*physiology ; Female ; Human ; *Image
                   Processing, Computer-Assisted ; *Magnetic Resonance
                   Imaging ; Male ; Middle Aged ; Nerve Net/physiology ;
                   Oxygen Consumption/physiology ; Pitch
                   Discrimination/*physiology ; Support, U.S. Gov't,
                   P.H.S. ; Temporal Lobe/physiology},
  language = {eng},
  medline-aid = {S1053811903002283 [pii]},
  medline-da = {20030901},
  medline-dcom = {20031023},
  medline-edat = {2003/09/02 05:00},
  medline-fau = {Liebenthal, Einat ; Ellingson, Michael L ; Spanaki,
                   Marianna V ; Prieto, Thomas E ; Ropella, Kristina M ;
                   Binder, Jeffrey R},
  medline-gr = {R01 NS 33576/NS/NINDS ; R21 DC 04880/DC/NIDCD},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {2003/10/24 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12948697},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2003 Aug;19(4):1395-404.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12948697},
  year = 2003
}
@ARTICLE{LGK+07,
  author = {Lu, Y. and Grova, C. and Kobayashi, E. and Dubeau, F.
                   and Gotman, J.},
  title = {Using voxel-specific hemodynamic response function in
                   {EEG}-f{MRI} data analysis: {A}n estimation and
                   detection model.},
  journal = {Neuroimage},
  volume = {34},
  number = {1},
  pages = {195-203},
  abstract = {Research groups who study epileptic spikes with
                   simultaneous EEG-fMRI have used mostly the general
                   linear model (GLM). A shortcoming of the GLM is that
                   the specification of a simple hemodynamic response
                   function (HRF) may lead to biased results. Other
                   methods, which predict the hemodynamic response from
                   the measured data, have been termed "recognition
                   models". The merit of recognition models lies in the
                   power of estimating the region-specific or
                   voxel-specific HRF. We propose an approach that merges
                   these two models in a general framework: estimate the
                   HRF on the training data sets, and applying the
                   estimated HRF on the other part of the data sets. The
                   merit of this framework is that it can utilize the
                   advantages of both models. A comparison of performance
                   is made between the GLM with three fixed HRFs and the
                   new model with voxel-specific HRFs. The main results
                   are as follows: (1) in 18 of the 21 patients, the new
                   model has a higher adjusted coefficient of multiple
                   determination than the GLM with fixed HRF; (2) in some
                   subjects, with the new model, we found areas of
                   activation that had not been detected with the three
                   fixed HRFs at our threshold of significance. The
                   results suggest that the new model can do better than
                   the fixed HRF GLM for the analysis of epileptic
                   activity with EEG-fMRI.},
  authoraddress = {Montreal Neurological Institute, McGill University,
                   3801 University Street, Montreal, Quebec, Canada H3A
                   2B4.},
  keywords = {*Electroencephalography ; Epilepsy/*physiopathology ;
                   Humans ; *Magnetic Resonance Imaging ; Models,
                   Statistical ; Sensitivity and Specificity},
  language = {eng},
  medline-aid = {S1053-8119(06)00891-3 [pii] ;
                   10.1016/j.neuroimage.2006.08.023 [doi]},
  medline-da = {20061124},
  medline-dcom = {20070709},
  medline-dep = {20061011},
  medline-edat = {2006/10/19 09:00},
  medline-fau = {Lu, Yingli ; Grova, Christophe ; Kobayashi, Eliane ;
                   Dubeau, Francois ; Gotman, Jean},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage},
  medline-mhda = {2007/07/10 09:00},
  medline-own = {NLM},
  medline-phst = {2006/06/06 [received] ; 2006/08/18 [revised] ;
                   2006/08/22 [accepted] ; 2006/10/11 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {17045491},
  medline-pst = {ppublish},
  medline-pt = {Comparative Study ; Journal Article ; Research
                   Support, Non-U.S. Gov't},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2007 Jan 1;34(1):195-203. Epub 2006 Oct
                   11.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17045491},
  year = 2007
}
@ARTICLE{LKB+03,
  author = {Laufs, H. and Kleinschmidt, A. and Beyerle, A. and
                   Eger, E. and Salek-Haddadi, A. and Preibisch, C. and
                   Krakow, K.},
  title = {E{EG}-correlated f{MRI} of human alpha activity},
  journal = {NeuroImage},
  volume = {19},
  number = {4},
  pages = {1463-1476},
  abstract = {Electroencephalography-correlated functional magnetic
                   resonance imaging (EEG/fMRI) can be used to identify
                   blood oxygen level-dependent (BOLD) signal changes
                   associated with both physiological and pathological EEG
                   events. Here, we implemented continuous and
                   simultaneous EEG/fMRI to identify BOLD signal changes
                   related to spontaneous power fluctuations in the alpha
                   rhythm (8-12 Hz), the dominant EEG pattern during
                   relaxed wakefulness. Thirty-two channels of EEG were
                   recorded in 10 subjects during eyes-closed rest inside
                   a 1.5-T magnet resonance (MR) scanner using an
                   MR-compatible EEG recording system. Functional scanning
                   by echoplanar imaging covered almost the entire
                   cerebrum every 4 s. Off-line MRI artifact subtraction
                   software was applied to obtain continuous EEG data
                   during fMRI acquisition. The average alpha power over
                   1-s epochs was derived at several electrode positions
                   using a Fast Fourier Transform. The power time course
                   was then convolved with a canonical hemodynamic
                   response function, down-sampled, and used for
                   statistical parametric mapping of associated signal
                   changes in the image time series. At all electrode
                   positions studied, a strong negative correlation of
                   parietal and frontal cortical activity with alpha power
                   was found. Conversely, only sparse and nonsystematic
                   positive correlation was detected. The relevance of
                   these findings is discussed in view of the current
                   theories on the generation and significance of the
                   alpha rhythm and the related functional neuroimaging
                   findings.},
  authoraddress = {Department of Neurology, Johann Wolfgang
                   Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt
                   am Main, Germany. helmut@laufs.com},
  keywords = {Adult ; *Alpha Rhythm ; Brain Mapping/*methods ;
                   Cerebral Cortex/*physiology ;
                   Electroencephalography/*methods ; Female ; Fourier
                   Analysis ; Frontal Lobe/physiology ; Human ; *Image
                   Processing, Computer-Assisted ; Imaging,
                   Three-Dimensional/*methods ; Magnetic Resonance
                   Imaging/*methods ; Male ; Mathematical Computing ;
                   Oxygen Consumption/physiology ; Parietal
                   Lobe/physiology ; Reference Values ; *Signal
                   Processing, Computer-Assisted ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1053811903002866 [pii]},
  medline-da = {20030901},
  medline-dcom = {20031023},
  medline-edat = {2003/09/02 05:00},
  medline-fau = {Laufs, H ; Kleinschmidt, A ; Beyerle, A ; Eger, E ;
                   Salek-Haddadi, A ; Preibisch, C ; Krakow, K},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2003/10/24 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12948703},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2003 Aug;19(4):1463-76.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12948703},
  year = 2003
}
@ARTICLE{LKF01,
  author = {Lemieux, L. and Krakow, K. and Fish, D. R.},
  title = {Comparison of spike-triggered functional {MRI} {BOLD}
                   activation and {EEG} dipole model localization},
  journal = {NeuroImage},
  volume = {14},
  number = {5},
  pages = {1097-1104},
  abstract = {We studied six patients with localization-related
                   epilepsy, frequent interictal epileptiform discharges,
                   and positive spike-triggered blood oxygen
                   level-dependent functional MRI (BOLD-fMRI) findings.
                   EEG source analysis solutions based on 64-channel EEG
                   recorded in a separate session outside the scanner were
                   obtained using dipole models and compared to the BOLD
                   localization. The BOLD and structural images were
                   coregistered, allowing the measurement of distances
                   between the generator models and BOLD activation(s) and
                   structural lesion when present. In all cases dipole
                   models could be found that explained a sufficient
                   amount of the data and that were anatomically
                   concordant with the BOLD localization. In the five
                   cases with structural abnormality visible on T1 scans,
                   the BOLD activation overlapped or was in close
                   proximity to the abnormality. The overall mean distance
                   between the main moving dipole and the center of the
                   nearest BOLD activation was 3.5 and 2.2 cm for the
                   negative and positive peaks, respectively, including
                   one case of a deep BOLD activation, in which the
                   distance was 5 cm. In conclusion, the degree of
                   agreement between the BOLD and EEG source localization
                   indicates that the combination of these two noninvasive
                   techniques offers the possibility of advancing the
                   study of the generators of epileptiform electrical
                   activity.},
  authoraddress = {Epilepsy Research Group, University College London
                   Institute of Neurology, Chalfont St. Peter, United
                   Kingdom.},
  keywords = {Adult ; Brain Mapping ; Cerebral
                   Cortex/*physiopathology ; Dominance,
                   Cerebral/physiology ; *Electroencephalography ;
                   Epilepsy, Frontal
                   Lobe/*diagnosis/etiology/physiopathology ; Epilepsy,
                   Temporal Lobe/*diagnosis/etiology/physiopathology ;
                   Evoked Potentials ; Female ; Human ; *Imaging,
                   Three-Dimensional ; *Magnetic Resonance Imaging ; Male
                   ; Middle Aged ; Oxygen/*blood ; Sensitivity and
                   Specificity ; Support, Non-U.S. Gov't ; Temporal
                   Lobe/physiopathology},
  language = {eng},
  medline-aid = {10.1006/nimg.2001.0896 [doi] ; S1053811901908961 [pii]},
  medline-ci = {Copyright 2001 Academic Press.},
  medline-da = {20011107},
  medline-dcom = {20020102},
  medline-edat = {2001/11/08 10:00},
  medline-fau = {Lemieux, L ; Krakow, K ; Fish, D R},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {2002/01/05 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11697941},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {NeuroImage 2001 Nov;14(5):1097-104.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11697941},
  year = 2001
}
@ARTICLE{LKS+03,
  author = {Laufs, H. and Krakow, K. and Sterzer, P. and Eger, E.
                   and Beyerle, A. and Salek-Haddadi, A. and Kleinschmidt,
                   A.},
  title = {Electroencephalographic signatures of attentional and
                   cognitive default modes in spontaneous brain activity
                   fluctuations at rest},
  journal = {Proc Natl Acad Sci U S A},
  volume = {100},
  number = {19},
  pages = {11053-11058},
  abstract = {We assessed the relation between hemodynamic and
                   electrical indices of brain function by performing
                   simultaneous functional MRI (fMRI) and
                   electroencephalography (EEG) in awake subjects at rest
                   with eyes closed. Spontaneous power fluctuations of
                   electrical rhythms were determined for multiple
                   discrete frequency bands, and associated fMRI signal
                   modulations were mapped on a voxel-by-voxel basis.
                   There was little positive correlation of localized
                   brain activity with alpha power (8-12 Hz), but strong
                   and widespread negative correlation in lateral frontal
                   and parietal cortices that are known to support
                   attentional processes. Power in a 17-23 Hz range of
                   beta activity was positively correlated with activity
                   in retrosplenial, temporo-parietal, and dorsomedial
                   prefrontal cortices. This set of areas has previously
                   been characterized by high but coupled metabolism and
                   blood flow at rest that decrease whenever subjects
                   engage in explicit perception or action. The
                   distributed patterns of fMRI activity that were
                   correlated with power in different EEG bands overlapped
                   strongly with those of functional connectivity, i.e.,
                   intrinsic covariations of regional activity at rest.
                   This result indicates that, during resting wakefulness,
                   and hence the absence of a task, these areas constitute
                   separable and dynamic functional networks, and that
                   activity in these networks is associated with distinct
                   EEG signatures. Taken together with studies that have
                   explicitly characterized the response properties of
                   these distributed cortical systems, our findings may
                   suggest that alpha oscillations signal a neural
                   baseline with "inattention" whereas beta rhythms index
                   spontaneous cognitive operations during conscious rest.},
  authoraddress = {Cognitive Neurology Unit, Department of Neurology, J.
                   W. Goethe University, Theodor-Stern-Kai 7, D-60590
                   Frankfurt am Main, Germany.},
  keywords = {*Attention ; Brain/*physiology ; *Cognition ;
                   Electroencephalography ; Human ; Magnetic Resonance
                   Imaging ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1073/pnas.1831638100 [doi] ; 1831638100 [pii]},
  medline-da = {20030917},
  medline-dcom = {20031029},
  medline-dep = {20030904},
  medline-edat = {2003/09/06 05:00},
  medline-fau = {Laufs, H ; Krakow, K ; Sterzer, P ; Eger, E ; Beyerle,
                   A ; Salek-Haddadi, A ; Kleinschmidt, A},
  medline-is = {0027-8424},
  medline-jid = {7505876},
  medline-mhda = {2003/10/30 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Sep/04 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {12958209},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Proc Natl Acad Sci U S A 2003 Sep 16;100(19):11053-8.
                   Epub 2003 Sep 4.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12958209},
  year = 2003
}
@ARTICLE{LP04,
  author = {Logothetis, N.K. and Pfeuffer, J.},
  title = {On the nature of the {BOLD} f{MRI} contrast mechanism.},
  journal = {Magn Reson Imaging},
  volume = {22},
  number = {10},
  pages = {1517-1531},
  abstract = {Since its development about 15 years ago, functional
                   magnetic resonance imaging (fMRI) has become the
                   leading research tool for mapping brain activity. The
                   technique works by detecting the levels of oxygen in
                   the blood, point by point, throughout the brain. In
                   other words, it relies on a surrogate signal, resulting
                   from changes in oxygenation, blood volume and flow, and
                   does not directly measure neural activity. Although a
                   relationship between changes in brain activity and
                   blood flow has long been speculated, indirectly
                   examined and suggested and surely anticipated and
                   expected, the neural basis of the fMRI signal was only
                   recently demonstrated directly in experiments using
                   combined imaging and intracortical recordings. In the
                   present paper, we discuss the results obtained from
                   such combined experiments. We also discuss our current
                   knowledge of the extracellularly measured signals of
                   the neural processes that they represent and of the
                   structural and functional neurovascular coupling, which
                   links such processes with the hemodynamic changes that
                   offer the surrogate signal that we use to map brain
                   activity. We conclude by considering applications of
                   invasive MRI, including injections of paramagnetic
                   tracers for the study of connectivity in the living
                   animal and simultaneous imaging and electrical
                   microstimulation.},
  authoraddress = {Department Physiology of Cognitive Processes, Max
                   Planck Institute for Biological Cybernetics,
                   Spemannstrasse 38, 72076 Tubingen, Germany.
                   nikos.logothetis@tuebingen.mpg.de},
  language = {eng},
  medline-aid = {S0730-725X(04)00301-7 [pii] ;
                   10.1016/j.mri.2004.10.018 [doi]},
  medline-da = {20050214},
  medline-edat = {2005/02/15 09:00},
  medline-fau = {Logothetis, Nikos K ; Pfeuffer, Josef},
  medline-is = {0730-725X},
  medline-jid = {8214883},
  medline-mhda = {2005/02/15 09:00},
  medline-own = {NLM},
  medline-phst = {2004/09/17 [received] ; 2004/10/15 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15707801},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Magn Reson Imaging 2004 Dec;22(10):1517-31.},
  medline-stat = {In-Process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15707801},
  year = 2004
}
@ARTICLE{LPA+01,
  author = {Logothetis, N. K. and Pauls, J. and Augath, M. and
                   Trinath, T. and Oeltermann, A.},
  title = {Neurophysiological investigation of the basis of the
                   f{MRI} signal},
  journal = {Nature},
  volume = {412},
  number = {6843},
  pages = {150-157},
  abstract = {Functional magnetic resonance imaging (fMRI) is widely
                   used to study the operational organization of the human
                   brain, but the exact relationship between the measured
                   fMRI signal and the underlying neural activity is
                   unclear. Here we present simultaneous intracortical
                   recordings of neural signals and fMRI responses. We
                   compared local field potentials (LFPs), single- and
                   multi-unit spiking activity with highly
                   spatio-temporally resolved blood-oxygen-level-dependent
                   (BOLD) fMRI responses from the visual cortex of
                   monkeys. The largest magnitude changes were observed in
                   LFPs, which at recording sites characterized by
                   transient responses were the only signal that
                   significantly correlated with the haemodynamic
                   response. Linear systems analysis on a trial-by-trial
                   basis showed that the impulse response of the
                   neurovascular system is both animal- and site-specific,
                   and that LFPs yield a better estimate of BOLD responses
                   than the multi-unit responses. These findings suggest
                   that the BOLD contrast mechanism reflects the input and
                   intracortical processing of a given area rather than
                   its spiking output.},
  authoraddress = {Max Planck Institute for Biological Cybernetics,
                   Tuebingen, Germany. nikos.logothetis@tuebingen.mpg.de},
  keywords = {Action Potentials ; Animals ; Contrast Sensitivity ;
                   Electrodes ; Electrophysiology ; Hemodynamic Processes
                   ; Macaca mulatta ; *Magnetic Resonance Imaging ;
                   Neurons/*physiology ; Oxygen/blood ; Photic Stimulation
                   ; Signal Processing, Computer-Assisted ; Support,
                   Non-U.S. Gov't ; Synaptic Transmission ; Visual
                   Cortex/*physiology},
  language = {eng},
  medline-aid = {10.1038/35084005 [doi] ; 35084005 [pii]},
  medline-cin = {Nature. 2001 Jul 12;412(6843):128-30. PMID: 11449247},
  medline-da = {20010712},
  medline-dcom = {20010802},
  medline-edat = {2001/07/13 10:00},
  medline-fau = {Logothetis, N K ; Pauls, J ; Augath, M ; Trinath, T ;
                   Oeltermann, A},
  medline-is = {0028-0836},
  medline-jid = {0410462},
  medline-lr = {20031114},
  medline-mhda = {2001/08/03 10:01},
  medline-own = {NLM},
  medline-pl = {England},
  medline-pmid = {11449264},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Nature 2001 Jul 12;412(6843):150-7.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11449264},
  year = 2001
}
@ARTICLE{LSJ+93,
  author = {Lagerlund, T. D. and Sharbrough, F. W. and Jack, Jr,
                   C. R. and Erickson, B. J. and Strelow, D. C. and
                   Cicora, K. M. and Busacker, N. E.},
  title = {Determination of 10-20 system electrode locations
                   using magnetic resonance image scanning with markers},
  journal = {Electroencephalogr Clin Neurophysiol},
  volume = {86},
  number = {1},
  pages = {7-14},
  abstract = {We determined locations of 33 scalp electrodes used
                   for electroencephalographic (EEG) recording by placing
                   markers in the positions determined by the 10-20 system
                   and performing magnetic resonance image (MRI) scanning
                   on volunteer subjects. Small Vaseline-filled capsules
                   glued on the scalp with collodion produced easily
                   delineated regions of increased signal on standard MRI
                   head images. Measurements of each capsule's coordinates
                   in 3 dimensions were made from MRI scans. A spherical
                   surface was fitted through the marker positions, giving
                   an average radius and an origin (center of sphere). The
                   coordinate axes were rotated to ensure that electrode
                   Cz was on the z-axis and that the y-axis was oriented
                   in the posterior-anterior direction. Two spherical
                   (angular) coordinates were determined for each
                   electrode. Spherical electrode coordinates for
                   different subjects differed by less than 20 degrees in
                   all cases. An average and standard deviation of the
                   spherical coordinates were calculated for each
                   electrode. Standard deviations of several degrees were
                   obtained. The average spherical coordinates obtained
                   were close to those expected on the basis of applying
                   the 10-20 system of placement to an ideal sphere. These
                   measurements provide data necessary for various
                   analyses of EEG performed to help localize epileptic
                   foci.},
  authoraddress = {Department of Neurology, Mayo Clinic and Mayo
                   Foundation, Rochester, MN 55905.},
  keywords = {Brain/anatomy & histology/*physiology ; Brain Mapping
                   ; Electrodes ; Electroencephalography/*instrumentation
                   ; Female ; Human ; *Magnetic Resonance Imaging ; Male},
  language = {eng},
  medline-da = {19930218},
  medline-dcom = {19930218},
  medline-edat = {1993/01/01},
  medline-fau = {Lagerlund, T D ; Sharbrough, F W ; Jack, C R Jr ;
                   Erickson, B J ; Strelow, D C ; Cicora, K M ; Busacker,
                   N E},
  medline-is = {0013-4694},
  medline-jid = {0375035},
  medline-lr = {20010323},
  medline-mhda = {2001/03/28 10:01},
  medline-own = {NLM},
  medline-pl = {IRELAND},
  medline-pmid = {7678393},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Electroencephalogr Clin Neurophysiol 1993
                   Jan;86(1):7-14.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=7678393},
  year = 1993
}
@ARTICLE{LSM+01,
  author = {Lantz, G. and Spinelli, L. and Menendez, R. G. and
                   Seeck, M. and Michel, C. M.},
  title = {Localization of distributed sources and comparison
                   with functional {MRI}},
  journal = {Epileptic Disord},
  volume = {Special Issue},
  pages = {45-58},
  abstract = {Functional mapping of the human brain has made
                   tremendous progress in the past years thanks to new
                   technical developments. Imaging methods are now
                   available; they allow to study brain functions with
                   high spatial and temporal resolution. Single photon
                   emission computer tomography (SPECT), positron emission
                   tomography (PET), functional magnetic resonance imaging
                   (fMRI) and high resolution electro- and
                   magnetoencephalography (EEG and MEG) are currently
                   intensively applied techniques to functional studies,
                   each one having specific properties concerning spatial
                   and temporal resolution. The success of these methods
                   in basic neuroscience research has led to the demand
                   for applying them to clinical questions. Diseases of
                   the central nervous system that lead to brain
                   dysfunction can be ideally explored using these
                   techniques. Of particular importance are those diseases
                   in which a focal neuronal dysfunction is the primary
                   cause and where surgical resection of this focus might
                   be the cure. This is often the case for epilepsy, where
                   a discrete primary focus might exist from which
                   pathological rhythms evolve and propagate throughout
                   the brain, leading to seizures that severely handicap
                   the patient. Surgical resection of the primary focus is
                   only possible if the focus can be exactly localized and
                   adequately separated from functionally important areas.
                   This is where these new functional imaging tools become
                   important. The use of SPECT and PET for focus
                   localization has been most extensively studied and
                   their specificity and sensitivity are intensively
                   discussed. In the last few years functional MRI has
                   evolved as a new interesting tool in epileptic focus
                   localization. The most important limitation of these
                   techniques, however, is the temporal resolution. Since
                   epileptic activity can propagate very fast, several
                   hyper- or hypoactive regions are seen in the images and
                   primary areas cannot be distinguished from regions of
                   propagation. The only methods that have sufficient
                   temporal resolution to follow neuronal activity in real
                   time are the electrophysiological measures, i.e. the
                   EEG and the MEG. Localization of the sources in the
                   brain that produced a given surface electromagnetic
                   field has become possible through algorithms that solve
                   the so-called "inverse problem". Several different
                   algorithms exist and many groups begun to apply them to
                   epileptic data with the aim to localize the focus of
                   the pathological electrical discharges. This review
                   article discusses the use of distributed EEG source
                   localization procedures in the presurgical evaluation
                   of patients with intractable focal epilepsy. In
                   contrast to equivalent dipole models, distributed
                   localization methods do not localize one active point
                   in the brain but rather assume extended active areas,
                   which is generally the case in epileptic activity. The
                   methods shown here are based on linear numerical
                   methods and are therefore less prone to errors when
                   working with scattered solution spaces such as the one
                   defined by anatomical constraints. Solutions constraint
                   to the gray matter determined in the individual MRI are
                   shown here. We illustrate three methods to increase the
                   spatial resolution of the source localization
                   procedures: One is to increase the number of recording
                   channels to more than 100, the second to use linear
                   methods of high precision to detect focal sources
                   (EPIFOCUS), and the third to combine EEG source
                   localization with EEG-triggered functional magnetic
                   resonance imaging. The importance of EEG source
                   localization for the interpretation of fMRI data will
                   be particularly discussed in view of the important
                   difference of the temporal resolution by the two
                   methods. The localization methods can be applied to
                   interictal as well as to ictal activity. In case of
                   analysis of ictal EEG we propose to use full scalp
                   frequency analysis to determine the time period of
                   seizure onset and to localize the sources of the
                   initial dominant frequency.},
  authoraddress = {Laboratoire de Cartographie des Fonctions Cerebrales,
                   Clinique de Neurologie, Hopital Cantonal, 24, rue
                   Micheli-du-Crest, CH-1211 Geneve 14, Suisse.},
  language = {eng},
  medline-da = {20020108},
  medline-edat = {2002/01/10 10:00},
  medline-fau = {Lantz, G ; Spinelli, L ; Menendez, R G ; Seeck, M ;
                   Michel, C M},
  medline-is = {1294-9361},
  medline-jid = {100891853},
  medline-mhda = {2002/01/10 10:00},
  medline-own = {NLM},
  medline-pl = {France},
  medline-pmid = {11781200},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Epileptic Disord 2001 Jul;Special Issue:45-58.},
  medline-stat = {in-data-review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11781200},
  year = 2001
}
@ARTICLE{LW04,
  author = {Logothetis, N. K. and Wandell, B. A.},
  title = {Interpreting the {BOLD} signal},
  journal = {Annu Rev Physiol},
  volume = {66},
  pages = {735-769},
  abstract = {The development of functional magnetic resonance
                   imaging (fMRI) has brought together a broad community
                   of scientists interested in measuring the neural basis
                   of the human mind. Because fMRI signals are an indirect
                   measure of neural activity, interpreting these signals
                   to make deductions about the nervous system requires
                   some understanding of the signaling mechanisms. We
                   describe our current understanding of the causal
                   relationships between neural activity and the
                   blood-oxygen-level-dependent (BOLD) signal, and we
                   review how these analyses have challenged some basic
                   assumptions that have guided neuroscience. We conclude
                   with a discussion of how to use the BOLD signal to make
                   inferences about the neural signal.},
  authoraddress = {Max-Planck Institut fur Biologische Kybernetik,
                   Tubingen, Germany.},
  keywords = {Animals ; Brain/*physiology ; Brain Mapping ;
                   *Cerebrovascular Circulation ; Electrophysiology ;
                   Human ; *Magnetic Resonance Imaging ; Models,
                   Neurological ; Oxygen/*blood ; Support, Non-U.S. Gov't
                   ; Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {10.1146/annurev.physiol.66.082602.092845 [doi]},
  medline-da = {20040223},
  medline-dcom = {20040506},
  medline-edat = {2004/02/24 05:00},
  medline-fau = {Logothetis, Nikos K ; Wandell, Brian A},
  medline-gr = {R01 EY03164/EY/NEI},
  medline-is = {0066-4278},
  medline-jid = {0370600},
  medline-mhda = {2004/05/07 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {14977420},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {164},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Annu Rev Physiol 2004;66:735-69.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=14977420},
  year = 2004
}
@ARTICLE{LWA+06,
  author = {Lin, F. H. and Witzel, T. and Ahlfors, S. P. and
                   Stufflebeam, S. M. and Belliveau, J. W. and Hamalainen,
                   M. S.},
  title = {Assessing and improving the spatial accuracy in {MEG}
                   source localization by depth-weighted minimum-norm
                   estimates.},
  journal = {Neuroimage},
  volume = {31},
  number = {1},
  pages = {160-71},
  abstract = {Cerebral currents responsible for the extra-cranially
                   recorded magnetoencephalography (MEG) data can be
                   estimated by applying a suitable source model. A
                   popular choice is the distributed minimum-norm estimate
                   (MNE) which minimizes the l2-norm of the estimated
                   current. Under the l2-norm constraint, the current
                   estimate is related to the measurements by a linear
                   inverse operator. However, the MNE has a bias towards
                   superficial sources, which can be reduced by applying
                   depth weighting. We studied the effect of depth
                   weighting in MNE using a shift metric. We assessed the
                   localization performance of the depth-weighted MNE as
                   well as depth-weighted noise-normalized MNE solutions
                   under different cortical orientation constraints,
                   source space densities, and signal-to-noise ratios
                   (SNRs) in multiple subjects. We found that MNE with
                   depth weighting parameter between 0.6 and 0.8 showed
                   improved localization accuracy, reducing the mean
                   displacement error from 12 mm to 7 mm. The
                   noise-normalized MNE was insensitive to depth
                   weighting. A similar investigation of EEG data
                   indicated that depth weighting parameter between 2.0
                   and 5.0 resulted in an improved localization accuracy.
                   The application of depth weighting to auditory and
                   somatosensory experimental data illustrated the
                   beneficial effect of depth weighting on the accuracy of
                   spatiotemporal mapping of neuronal sources.},
  authoraddress = {MGH/MIT/HMS Athinoula A. Martinos Center for
                   Biomedical Imaging, Building 149 13th St. Charlestown,
                   MA 02129, USA. fhlin@nmr.mgh.harvard.edu},
  language = {eng},
  medline-aid = {S1053-8119(05)02497-3 [pii] ;
                   10.1016/j.neuroimage.2005.11.054 [doi]},
  medline-da = {20060523},
  medline-dep = {20060306},
  medline-edat = {2006/03/08 09:00},
  medline-fau = {Lin, Fa-Hsuan ; Witzel, Thomas ; Ahlfors, Seppo P ;
                   Stufflebeam, Steven M ; Belliveau, John W ; Hamalainen,
                   Matti S},
  medline-gr = {P41 RR14075/RR/NCRR ; R01 HD040712/HD/NICHD ; R01
                   NS037462/NS/NINDS},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2006/03/08 09:00},
  medline-own = {NLM},
  medline-phst = {2005/03/16 [received] ; 2005/11/21 [revised] ;
                   2005/11/29 [accepted] ; 2006/03/06 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16520063},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 May 15;31(1):160-71. Epub 2006 Mar 6.},
  medline-stat = {In-Process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16520063},
  year = 2006
}
@ARTICLE{LWL+01,
  author = {Lamm, C. and Windischberger, C. and Leodolter, U. and
                   Moser, E. and Bauer, H.},
  title = {Co-registration of {EEG} and {MRI} data using matching
                   of spline interpolated and {MRI}-segmented
                   reconstructions of the scalp surface.},
  journal = {Brain Topogr},
  volume = {14},
  number = {2},
  pages = {93-100},
  abstract = {Accurate co-registration of MRI and EEG data is
                   indispensable for the correct interpretation of EEG
                   maps or source localizations in relation to brain
                   anatomy derived from MRI. In this study, a method for
                   the co-registration of EEG and MRI data is presented.
                   The method consists of an iterative matching of
                   EEG-electrode based reconstructions of the scalp
                   surface to scalp-segmented MRIs. EEG-electrode based
                   surface reconstruction is achieved via spline
                   interpolation of individually digitized 3D-electrode
                   coordinates. In contrast to other approaches, neither
                   fiducial determination nor any additional provisions
                   (such as bite bars, other co-registration devices or
                   head shape digitization) are required, and
                   co-registration errors associated with inaccurate
                   fiducial determination are avoided. The accuracy of the
                   method was estimated by calculating the
                   root-mean-square (RMS) deviation of spline interpolated
                   and MRI-segmented surface reconstructions in 20
                   subjects. In addition, the distance between
                   co-registered and genuine electrode coordinates was
                   assessed via a simulation study, in which surface
                   reconstruction was based on virtual electrodes
                   determined on the scalp surface of a high-resolution
                   MRI data set. The mean RMS deviation of surface
                   reconstructions was 2.43 mm, and the maximal distance
                   between any two matched surface points was 5.06 mm. The
                   simulated co-registration revealed a mean deviation of
                   genuine and co-registered electrode coordinates of 0.61
                   mm. It is concluded that surface matching using spline
                   interpolated reconstructions of scalp surfaces is a
                   precise and highly practicable method to co-register
                   EEG and MRI data.},
  authoraddress = {Department of Psychology, University of Vienna,
                   Austria. claus.lamm@univie.ac.at},
  keywords = {Adult ; Brain/*anatomy & histology/*physiology ;
                   Brain Mapping/*methods ; *Electroencephalography ;
                   Human ; *Image Processing, Computer-Assisted ; Imaging,
                   Three-Dimensional ; *Magnetic Resonance Imaging ;
                   Scalp/*anatomy & histology/*physiology ; Skull/anatomy
                   & histology ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-da = {20020118},
  medline-dcom = {20020619},
  medline-edat = {2002/01/19 10:00},
  medline-fau = {Lamm, C ; Windischberger, C ; Leodolter, U ; Moser, E
                   ; Bauer, H},
  medline-is = {0896-0267},
  medline-jid = {8903034},
  medline-mhda = {2002/06/20 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11797814},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Brain Topogr 2001 Winter;14(2):93-100.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11797814},
  year = 2001
}
@ARTICLE{LZB+01,
  author = {Lazeyras, F. and Zimine, I. and Blanke, O. and Perrig,
                   S. H. and Seeck, M.},
  title = {Functional {MRI} with simultaneous {EEG} recording:
                   feasibility and application to motor and visual
                   activation},
  journal = {J Magn Reson Imaging},
  volume = {13},
  number = {6},
  pages = {943-948},
  abstract = {The possibility of combining the high spatial
                   resolution of functional magnetic resonance imaging
                   (fMRI) with the high temporal resolution of
                   electroencephalography (EEG) may provide a new tool in
                   cognitive neurophysiology, as well as in clinical
                   applications such as epilepsy. However, the
                   simultaneous recording of EEG and fMRI raises important
                   practical problems: 1) the patients' safety, in
                   particular the risk of skin burns due to electrodes
                   heating; 2) the impairment of the EEG recording by the
                   static magnetic field, as well as by RF and magnetic
                   field gradients used during MRI; and 3) the quality of
                   MR images, which may be affected by the presence of
                   conductors and electronic devices in the MRI bore. Here
                   we present our experiences on 19 normal volunteers who
                   underwent combined fMRI and 16-channel EEG examination.
                   Consistent with previous reports, safety could be
                   assured when performing EEG recordings during fMRI
                   acquisition. Electrophysiological signals recorded with
                   surface EEG were similar inside and outside the 1.5 T
                   magnet. Furthermore, fMRI using motor or visual tasks
                   revealed similar areas of activation when performed
                   with and without 16-channel EEG recording. J. Magn.
                   Reson. Imaging 2001;13:943-948.},
  authoraddress = {Department of Radiology, University Hospital of
                   Geneva, rue Micheli-du-Crest 24, 1211 Geneva 14,
                   Switzerland. francois.lazeyras@hcuge.ch},
  keywords = {Attention/physiology ; Brain Mapping/instrumentation ;
                   Cerebral Cortex/*physiology ; Echo-Planar
                   Imaging/*instrumentation ; Electrodes ;
                   Electroencephalography/*instrumentation ; Equipment
                   Safety ; Heat/adverse effects ; Human ; *Image
                   Enhancement ; *Image Processing, Computer-Assisted ;
                   Magnetic Resonance Imaging/*instrumentation ; Motion
                   Perception/physiology ; Motor Activity/physiology ;
                   Pattern Recognition, Visual/physiology ; Reference
                   Values ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1002/jmri.1135 [pii]},
  medline-ci = {Copyright 2001 Wiley-Liss, Inc.},
  medline-da = {20010530},
  medline-dcom = {20010726},
  medline-edat = {2001/05/31 10:00},
  medline-fau = {Lazeyras, F ; Zimine, I ; Blanke, O ; Perrig, S H ;
                   Seeck, M},
  medline-is = {1053-1807},
  medline-jid = {9105850},
  medline-lr = {20011119},
  medline-mhda = {2001/07/28 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11382957},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {J Magn Reson Imaging 2001 Jun;13(6):943-8.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11382957},
  year = 2001
}
@ARTICLE{Log03,
  author = {Logothetis, N. K.},
  title = {The underpinnings of the {BOLD} functional magnetic
                   resonance imaging signal},
  journal = {J Neurosci},
  volume = {23},
  number = {10},
  pages = {3963-3971},
  authoraddress = {Max Planck Institute for Biological Cybernetics, 72076
                   Tuebingen, Germany. nikos.logothetis@tuebingen.mpg.de},
  keywords = {Animals ; Brain/blood supply/physiology ; Carbon
                   Dioxide/blood ; Cerebrovascular Circulation/physiology
                   ; Echo-Planar Imaging/methods ; Human ; Magnetic
                   Resonance Imaging/*methods ; Magnetic Resonance
                   Spectroscopy/methods ; Oxygen/*blood ; Support,
                   Non-U.S. Gov't},
  language = {eng},
  medline-aid = {23/10/3963 [pii]},
  medline-da = {20030523},
  medline-dcom = {20030625},
  medline-edat = {2003/05/24 05:00},
  medline-fau = {Logothetis, Nikos K},
  medline-is = {1529-2401},
  medline-jid = {8102140},
  medline-lr = {20031114},
  medline-mhda = {2003/06/26 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12764080},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {125},
  medline-rn = {124-38-9 (Carbon Dioxide) ; 7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {J Neurosci 2003 May 15;23(10):3963-71.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12764080},
  year = 2003
}
@ARTICLE{MBC+03,
  author = {Marrelec, G. and Benali, H. and Ciuciu, P. and
                   Pelegrini-Issac, M. and Poline, J. B.},
  title = {Robust {B}ayesian estimation of the hemodynamic
                   response function in event-related {BOLD} f{MRI} using
                   basic physiological information},
  journal = {Hum Brain Mapp},
  volume = {19},
  number = {1},
  pages = {1-17},
  abstract = {In BOLD fMRI data analysis, robust and accurate
                   estimation of the Hemodynamic Response Function (HRF)
                   is still under investigation. Parametric methods assume
                   the shape of the HRF to be known and constant
                   throughout the brain, whereas non-parametric methods
                   mostly rely on artificially increasing the
                   signal-to-noise ratio. We extend and develop a
                   previously proposed method that makes use of basic yet
                   relevant temporal information about the underlying
                   physiological process of the brain BOLD response in
                   order to infer the HRF in a Bayesian framework. A
                   general hypothesis test is also proposed, allowing to
                   take advantage of the knowledge gained regarding the
                   HRF to perform activation detection. The performances
                   of the method are then evaluated by simulation. Great
                   improvement is shown compared to the Maximum-Likelihood
                   estimate in terms of estimation error, variance, and
                   bias. Robustness of the estimators with regard to the
                   actual noise structure or level, as well as the
                   stimulus sequence, is also proven. Lastly, fMRI data
                   with an event-related paradigm are analyzed. As
                   suspected, the regions selected from highly
                   discriminating activation maps resulting from the
                   method exhibit a certain inter-regional homogeneity in
                   term of HRF shape, as well as noticeable inter-regional
                   differences.},
  authoraddress = {Institut National de la Sante et de la Recherche
                   Medicale U494, Paris, France.
                   Guillaume.marrelec@imed.jussieu.fr},
  keywords = {Adult ; Bayes Theorem ; Hemodynamic
                   Processes/*physiology ; Human ; Magnetic Resonance
                   Imaging/*methods/statistics & numerical data ;
                   *Models, Biological ; Psychomotor
                   Performance/*physiology ; Statistics ; Support,
                   Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1002/hbm.10100 [doi]},
  medline-ci = {Copyright 2003 Wiley-Liss, Inc.},
  medline-da = {20030505},
  medline-dcom = {20030605},
  medline-edat = {2003/05/06 05:00},
  medline-fau = {Marrelec, Guillaume ; Benali, Habib ; Ciuciu, Philippe
                   ; Pelegrini-Issac, Melanie ; Poline, Jean-Baptiste},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-lr = {20031114},
  medline-mhda = {2003/06/06 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12731100},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 2003 May;19(1):1-17.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12731100},
  year = 2003
}
@ARTICLE{MBW+06,
  author = {Mazaheri, Y. and Biswal, B. B. and Ward, B. D. and
                   Hyde, J. S.},
  title = {Measurements of tissue {T}(1) spin-lattice relaxation
                   time and discrimination of large draining veins using
                   transient {EPI} data sets in {BOLD}-weighted f{MRI}
                   acquisitions.},
  journal = {Neuroimage},
  volume = {32},
  number = {2},
  pages = {603-15},
  abstract = {The signal intensity during the dynamic approach to
                   the equilibrium state of longitudinal magnetization is
                   a function of sequence parameters, such as repetition
                   time and flip angle, and depends on tissue
                   characteristics, including longitudinal relaxation time
                   of stationary tissue and the rate of blood inflow. A
                   method is presented to extract information from data
                   acquired during the transient state prior to T(1)
                   equilibrium using echo-planar acquisitions in
                   T(2)*-weighted functional magnetic resonance imaging
                   (fMRI) experiments. A voxel in a single slice
                   acquisition is assumed to contain either stationary
                   tissue or large vessels with flowing blood. Models are
                   presented to characterize longitudinal magnetization
                   relaxation of heterogeneous stationary tissue and blood
                   inflow. The data were fitted to theoretical models for
                   longitudinal relaxation of stationary tissue and
                   inflowing blood assuming no residual signal prior to
                   each RF excitation. Parameters were estimated at 3 T
                   for each model using least squares estimation. A
                   goodness-of-fit criterion was applied to exclude voxels
                   that have transient data that does not fit the selected
                   (best fit) model. Voxels that best fit the inflow
                   model, measured at various TR and flip angles, were
                   assumed to contain large draining veins and were
                   excluded from functional maps. Histogram analysis of
                   T(1) distributions for activated voxels in a visual
                   paradigm demonstrated the distributions are centered at
                   T(1) values of gray matter with tails at both sides of
                   the center due to partial voluming of gray matter with
                   white matter and CSF respectively. The mean gray matter
                   volume fraction in activated voxels was about 0.9. The
                   results indicate that transient data sets can provide
                   additional information that is useful for both
                   localization and characterization of the functionally
                   relevant BOLD response.},
  authoraddress = {Department of Medical Physics and Radiology, Memorial
                   Sloan Kettering Cancer Center, 1275 York Avenue, New
                   York, NY 10021, USA.},
  language = {eng},
  medline-aid = {S1053-8119(06)00238-2 [pii] ;
                   10.1016/j.neuroimage.2006.03.051 [doi]},
  medline-da = {20060807},
  medline-dep = {20060519},
  medline-edat = {2006/05/23 09:00},
  medline-fau = {Mazaheri, Yousef ; Biswal, Bharat B ; Ward, B Douglas
                   ; Hyde, James S},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2006/05/23 09:00},
  medline-own = {NLM},
  medline-phst = {2005/09/16 [received] ; 2006/02/26 [revised] ;
                   2006/03/23 [accepted] ; 2006/05/19 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16713305},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 Aug 15;32(2):603-15. Epub 2006 May
                   19.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16713305},
  year = 2006
}
@ARTICLE{MC05,
  author = {Menon, V. and Crottaz-Herbette, S.},
  title = {Combined {EEG} and f{MRI} studies of human brain
                   function.},
  journal = {Int Rev Neurobiol},
  volume = {66},
  pages = {291-321},
  authoraddress = {Department of Psychiatry & Behavioral Sciences,
                   Stanford University School of Medicine Stanford,
                   California 94305, USA.},
  keywords = {Artifacts ; Brain/*physiology ;
                   *Electroencephalography ; Epilepsy/diagnosis ; Evoked
                   Potentials ; Humans ; *Magnetic Resonance Imaging ;
                   Models, Neurological},
  language = {eng},
  medline-aid = {S0074-7742(05)66010-2 [pii] ;
                   10.1016/S0074-7742(05)66010-2 [doi]},
  medline-da = {20060102},
  medline-dcom = {20060118},
  medline-edat = {2006/01/03 09:00},
  medline-fau = {Menon, V ; Crottaz-Herbette, S},
  medline-is = {0074-7742 (Print)},
  medline-jid = {0374740},
  medline-jt = {International review of neurobiology.},
  medline-mhda = {2006/01/19 09:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {16387208},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review},
  medline-pubm = {Print},
  medline-rf = {88},
  medline-sb = {IM},
  medline-so = {Int Rev Neurobiol. 2005;66:291-321.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16387208},
  year = 2005
}
@ARTICLE{MF05,
  author = {Mathiak, K. and Fallgatter, A.J.},
  title = {Combining magnetoencephalography and functional
                   magnetic resonance imaging.},
  journal = {Int Rev Neurobiol},
  volume = {68},
  pages = {121-48},
  authoraddress = {Department of Psychiatry, RWTH Aachen University
                   D-52074 Aachen, Germany.},
  language = {eng},
  medline-aid = {S0074-7742(05)68005-1 [pii] ;
                   10.1016/S0074-7742(05)68005-1 [doi]},
  medline-da = {20060130},
  medline-edat = {2006/01/31 09:00},
  medline-fau = {Mathiak, Klaus ; Fallgatter, Andreas J},
  medline-is = {0074-7742 (Print)},
  medline-jid = {0374740},
  medline-jt = {International review of neurobiology.},
  medline-mhda = {2006/01/31 09:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {16443012},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Int Rev Neurobiol. 2005;68:121-48.},
  medline-stat = {In-Process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16443012},
  year = 2005
}
@ARTICLE{MFL+97,
  author = {Menon, V. and Ford, J. M. and Lim, K. O. and Glover,
                   G. H. and Pfefferbaum, A.},
  title = {Combined event-related f{MRI} and {EEG} evidence for
                   temporal-parietal cortex activation during target
                   detection},
  journal = {Neuroreport},
  volume = {8},
  number = {14},
  pages = {3029-3037},
  abstract = {Target detection is the process of bringing a salient
                   stimulus into conscious awareness. Target detection
                   evokes a prominent event-related potential (ERP)
                   component (P3) in the electroencephalogram (EEG). We
                   combined the high spatial resolution of functional
                   magnetic resonance imaging (fMRI) with the high
                   temporal resolution of EEG to investigate the neural
                   generators of the P3. Event-related brain activation
                   (ERBA) and ERPs were computed by time-locked averaging
                   of fMRI and EEG, respectively, recorded using the same
                   paradigm in the same subjects. Target detection
                   elicited significantly greater ERBAs bilaterally in the
                   temporal-parietal cortex, thalamus and anterior
                   cingulate. Spatio-temporal modelling of ERPs based on
                   dipole locations derived from the ERBAs indicated that
                   bilateral sources in the temporal-parietal cortex are
                   the main generators of the P3. The findings provide
                   convergent fMRI and EEG evidence for significant
                   activation of the temporal-parietal cortex 285-610 ms
                   after stimulus onset during target detection. The
                   methods developed here provide a novel multimodal
                   neuroimaging technique to investigate the
                   spatio-temporal aspects of processes underlying brain
                   function.},
  authoraddress = {Department of Psychiatry and Behavioral Sciences,
                   Stanford University School of Medicine, CA 94305, USA.},
  keywords = {Adult ; Brain Mapping/*methods ;
                   *Electroencephalography ; Evoked Potentials/physiology
                   ; Female ; Human ; Magnetic Resonance Imaging/*methods
                   ; Male ; Parietal Lobe/*physiology ; Support, Non-U.S.
                   Gov't ; Support, U.S. Gov't, Non-P.H.S. ; Support, U.S.
                   Gov't, P.H.S. ; Temporal Lobe/*physiology},
  language = {eng},
  medline-da = {19971126},
  medline-dcom = {19971126},
  medline-edat = {1997/10/23},
  medline-fau = {Menon, V ; Ford, J M ; Lim, K O ; Glover, G H ;
                   Pfefferbaum, A},
  medline-gr = {AA05965/AA/NIAAA ; MH30854/MH/NIMH ; RR09784/RR/NCRR},
  medline-is = {0959-4965},
  medline-jid = {9100935},
  medline-lr = {20001218},
  medline-mhda = {1997/10/23 00:01},
  medline-own = {NLM},
  medline-pl = {ENGLAND},
  medline-pmid = {9331910},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article ; Randomized
                   Controlled Trial},
  medline-sb = {IM},
  medline-so = {Neuroreport 1997 Sep 29;8(14):3029-37.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9331910},
  year = 1997
}
@ARTICLE{MH90,
  author = {Miller, C. E. and Henriquez, C. S.},
  title = {Finite element analysis of bioelectric phenomena},
  journal = {Crit Rev Biomed Eng},
  volume = {18},
  number = {3},
  pages = {207-233},
  abstract = {This article reviews the application of finite element
                   methods to models of bioelectric phenomena. The models
                   represent the electrical fields created in the body as
                   a result of membrane current sources or external
                   current applied for diagnostic or therapeutic purposes.
                   We formulate the governing equations for these models
                   and then derive the finite element equations for the
                   generalized bioelectric problem. The 32 papers reviewed
                   here, all those appearing in the literature to date,
                   cover the areas of electrocardiology, therapeutic and
                   functional electrical stimulation in the cerebellum,
                   cochlea, spinal cord, and peripheral nerves, cardiac
                   defibrillation, electrical impedance tomography,
                   bidomain cardiac models, electroporation, and
                   therapeutic electrical stimulation of bone. For each,
                   we summarize the purpose of the study, the model
                   details and assumptions, the major results, and the
                   applicability of the study. The models are then
                   considered as a group to critique the appropriateness
                   of the finite element method, the means of
                   implementation, and the factors affecting accuracy,
                   thus providing an overview of the state of finite
                   element modeling of bioelectric phenomena.},
  authoraddress = {Center for Computer-Aided Engineering and Design,
                   Bucknell University, Lewisburg, PA 17837.},
  keywords = {Central Nervous System Diseases/therapy ; Cochlear
                   Implants ; Electric Countershock ; Electric Stimulation
                   Therapy ; *Electrophysiology ; Human ; *Models,
                   Biological ; Tomography, X-Ray/methods ; Ventricular
                   Fibrillation/therapy},
  language = {eng},
  medline-da = {19910322},
  medline-dcom = {19910322},
  medline-edat = {1990/01/01},
  medline-fau = {Miller, C E ; Henriquez, C S},
  medline-is = {0278-940X},
  medline-jid = {8208627},
  medline-lr = {20001218},
  medline-mhda = {1990/01/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {2286094},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {73},
  medline-sb = {IM},
  medline-so = {Crit Rev Biomed Eng 1990;18(3):207-33.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=2286094},
  year = 1990
}
@ARTICLE{MHB+06,
  author = {Mandelkow, H. and Halder, P. and Boesiger, P. and
                   Brandeis, D.},
  title = {Synchronization facilitates removal of {MRI} artefacts
                   from concurrent {EEG} recordings and increases usable
                   bandwidth.},
  journal = {Neuroimage},
  volume = {32},
  number = {3},
  pages = {1120-6},
  abstract = {Investigating human brain function non-invasively by
                   simultaneous EEG and fMRI measurements is gaining in
                   popularity as more and better solutions to the inherent
                   technical challenges emerge. We demonstrate the use of
                   a commercially available frequency divider and
                   phase-locking device for the purpose of synchronizing
                   an MRI acquisition with a simultaneous recording of the
                   EEG. Synchronization hugely improves the effectiveness
                   of MRI artefact removal from the EEG signal by the
                   common mean template subtraction method. It complements
                   or substitutes post-processing techniques like
                   filtering, thereby increasing the usable bandwidth of
                   the EEG signal to about 150 Hz. This is important for
                   covering the full range of human Gamma band activity.
                   Similarly, synchronization eliminates the necessity for
                   over-sampling of the EEG signal.},
  authoraddress = {Institute for Biomedical Engineering, University and
                   ETH Zurich, Zurich, Switzerland.},
  language = {eng},
  medline-aid = {S1053-8119(06)00542-8 [pii] ;
                   10.1016/j.neuroimage.2006.04.231 [doi]},
  medline-da = {20060828},
  medline-dep = {20060724},
  medline-edat = {2006/07/25 09:00},
  medline-fau = {Mandelkow, H ; Halder, P ; Boesiger, P ; Brandeis, D},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2006/07/25 09:00},
  medline-own = {NLM},
  medline-phst = {2005/12/12 [received] ; 2006/04/16 [revised] ;
                   2006/04/28 [accepted] ; 2006/07/24 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16861010},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 Sep;32(3):1120-6. Epub 2006 Jul 24.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16861010},
  year = 2006
}
@ARTICLE{MJS+04,
  author = {Mulert, C. and Jager, L. and Schmitt, R. and Bussfeld,
                   P. and Pogarell, O. and Moller, H. J. and Juckel, G.
                   and Hegerl, U.},
  title = {Integration of f{MRI} and simultaneous {EEG}: towards
                   a comprehensive understanding of localization and
                   time-course of brain activity in target detection},
  journal = {NeuroImage},
  volume = {22},
  number = {1},
  pages = {83-94},
  abstract = {fMRI and EEG are complimentary methods for the
                   analysis of brain activity since each method has its
                   strength where the other one has limits: The spatial
                   resolution is thus in the range of millimeters with
                   fMRI and the time resolution is in the range of
                   milliseconds with EEG. For a comprehensive
                   understanding of brain activity in target detection,
                   nine healthy subjects (age 24.2 +/- 2.9) were
                   investigated with simultaneous EEG (27 electrodes) and
                   fMRI using an auditory oddball paradigm. As a first
                   step, event-related potentials, measured inside the
                   scanner, have been compared with the potentials
                   recorded in a directly preceding session in front of
                   the scanner. Attenuated amplitudes were found inside
                   the scanner for the earlier N1/P2 component but not for
                   the late P300 component. Second, an independent
                   analysis of the localizations of the fMRI activations
                   and the current source density as revealed by low
                   resolution electromagnetic tomography (LORETA) has been
                   done. Concordant activations were found in most
                   regions, including the temporoparietal junction (TPJ),
                   the supplementary motor area (SMA)/anterior cingulate
                   cortex (ACC), the insula, and the middle frontal gyrus,
                   with a mean Euclidean distance of 16.0 +/- 6.6 mm
                   between the BOLD centers of gravity and the
                   LORETA-maxima. Finally, a time-course analysis based on
                   the current source density maxima was done. It revealed
                   different time-course patterns in the left and right
                   hemisphere with earlier activations in frontal and
                   parietal regions in the right hemisphere. The results
                   suggest that the combination of EEG and fMRI permits an
                   improved understanding of the spatiotemporal dynamics
                   of brain activity.},
  authoraddress = {Department of Psychiatry, LMU, Nussbaumstrasse 7,
                   80336 Munich, Germany. cmulert@psy.med.uni-muenchen.de},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.10.051 [doi] ;
                   S1053811904000084 [pii]},
  medline-da = {20040427},
  medline-edat = {2004/04/28 05:00},
  medline-fau = {Mulert, Christoph ; Jager, Lorenz ; Schmitt, Robert ;
                   Bussfeld, Patrick ; Pogarell, Oliver ; Moller,
                   Hans-Jurgen ; Juckel, Georg ; Hegerl, Ulrich},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/04/28 05:00},
  medline-own = {NLM},
  medline-phst = {2003/May/06 [received] ; 2003/Oct/29 [revised] ;
                   2003/Oct/29 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15109999},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 May;22(1):83-94.},
  medline-stat = {in-process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15109999},
  year = 2004
}
@ARTICLE{MKV+06,
  author = {Musso, F. and Konrad, A. and Vucurevic, G. and
                   Schaffner, C. and Friedrich, B. and Frech, P. and
                   Stoeter, P. and Winterer, G.},
  title = {Distributed {BOLD}-response in association cortex
                   vector state space predicts reaction time during
                   selective attention.},
  journal = {Neuroimage},
  volume = {29},
  number = {4},
  pages = {1311-8},
  abstract = {Human cortical information processing is thought to be
                   dominated by distributed activity in vector state space
                   (Churchland, P.S., Sejnowski, T.J., 1992. The
                   Computational Brain. MIT Press, Cambridge.). In
                   principle, it should be possible to quantify
                   distributed brain activation with independent component
                   analysis (ICA) through vector-based decomposition,
                   i.e., through a separation of a mixture of sources.
                   Using event-related functional magnetic resonance
                   imaging (fMRI) during a selective attention-requiring
                   task (visual oddball), we explored how the number of
                   independent components within activated cortical areas
                   is related to reaction time. Prior to ICA, the
                   activated cortical areas were determined on the basis
                   of a General linear model (GLM) voxel-by-voxel analysis
                   of the target stimuli (checkerboard reversal). Two
                   activated cortical areas (temporoparietal cortex,
                   medial prefrontal cortex) were further investigated as
                   these cortical regions are known to be the sites of
                   simultaneously active electromagnetic generators which
                   give rise to the compound event-related potential P300
                   during oddball task conditions. We found that the
                   number of independent components more strongly
                   predicted reaction time than the overall level of
                   "activation" (GLM BOLD-response) in the left
                   temporoparietal area whereas in the medial prefrontal
                   cortex both ICA and GLM predicted reaction time equally
                   well. Comparable correlations were not seen when
                   principle components were used instead of independent
                   components. These results indicate that the number of
                   independently activated components, i.e., a high level
                   of cortical activation complexity in cortical vector
                   state space, may index particularly efficient
                   information processing during selective
                   attention-requiring tasks. To our best knowledge, this
                   is the first report describing a potential relationship
                   between neuronal generators of cognitive processes, the
                   associated electrophysiological evidence for the
                   existence of distributed networks and BOLD fMRI signals
                   using information from model order selection
                   techniques.},
  authoraddress = {Laboratory of Molecular Neuroimaging and
                   Electrophysiology, Department of Psychiatry, Johannes
                   Gutenberg-University Hospital, Untere Zahlbacherstr. 8,
                   55131 Mainz, Germany.},
  keywords = {Adult ; Attention/*physiology ; Brain Mapping ;
                   Cerebral Cortex/*physiology ; Dominance,
                   Cerebral/physiology ; Event-Related Potentials,
                   P300/physiology ; Female ; Humans ; *Image Enhancement
                   ; *Image Processing, Computer-Assisted ; *Imaging,
                   Three-Dimensional ; Linear Models ; *Magnetic Resonance
                   Imaging ; Male ; Nerve Net/physiology ;
                   Neurons/physiology ; Oxygen/*blood ; Pattern
                   Recognition, Visual/*physiology ; Principal Component
                   Analysis ; Reaction Time/*physiology},
  language = {eng},
  medline-aid = {S1053-8119(05)00557-4 [pii] ;
                   10.1016/j.neuroimage.2005.07.059 [doi]},
  medline-da = {20060206},
  medline-dcom = {20060517},
  medline-dep = {20060109},
  medline-edat = {2006/01/13 09:00},
  medline-fau = {Musso, Francesco ; Konrad, Andreas ; Vucurevic, Goran
                   ; Schaffner, Cornelius ; Friedrich, Britta ; Frech,
                   Peter ; Stoeter, Peter ; Winterer, Georg},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2006/05/18 09:00},
  medline-own = {NLM},
  medline-phst = {2005/03/08 [received] ; 2005/07/22 [revised] ;
                   2005/07/26 [accepted] ; 2006/01/09 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16406256},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 Feb 15;29(4):1311-8. Epub 2006 Jan 9.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16406256},
  year = 2006
}
@ARTICLE{MML+04,
  author = {Michel, C. M. and Murray, M. M. and Lantz, G. and
                   Gonzalez, S. and Spinelli, L. and Grave De Peralta, R.},
  title = {E{EG} source imaging},
  journal = {Clin Neurophysiol},
  volume = {115},
  number = {10},
  pages = {2195-2222},
  abstract = {Objective: Electroencephalography (EEG) is an
                   important tool for studying the temporal dynamics of
                   the human brain's large-scale neuronal circuits.
                   However, most EEG applications fail to capitalize on
                   all of the data's available information, particularly
                   that concerning the location of active sources in the
                   brain. Localizing the sources of a given scalp
                   measurement is only achieved by solving the so-called
                   inverse problem. By introducing reasonable a priori
                   constraints, the inverse problem can be solved and the
                   most probable sources in the brain at every moment in
                   time can be accurately localized. Methods and Results:
                   Here, we review the different EEG source localization
                   procedures applied during the last two decades.
                   Additionally, we detail the importance of those
                   procedures preceding and following source estimation
                   that are intimately linked to a successful, reliable
                   result. We discuss (1) the number and positioning of
                   electrodes, (2) the varieties of inverse solution
                   models and algorithms, (3) the integration of EEG
                   source estimations with MRI data, (4) the integration
                   of time and frequency in source imaging, and (5) the
                   statistical analysis of inverse solution results.
                   Conclusions and Significance: We show that modern EEG
                   source imaging simultaneously details the temporal and
                   spatial dimensions of brain activity, making it an
                   important and affordable tool to study the properties
                   of cerebral, neural networks in cognitive and clinical
                   neurosciences.},
  authoraddress = {Functional Brain Mapping Laboratory, Neurology Clinic,
                   University Hospital of Geneva, 24 rue Micheli-du-Crest,
                   1211 Geneva, Switzerland.},
  language = {eng},
  medline-aid = {10.1016/j.clinph.2004.06.001 [doi] ; S1388245704002135
                   [pii]},
  medline-da = {20040907},
  medline-edat = {2004/09/08 05:00},
  medline-fau = {Michel, Christoph M ; Murray, Micah M ; Lantz, Goran ;
                   Gonzalez, Sara ; Spinelli, Laurent ; Grave De Peralta,
                   Rolando},
  medline-is = {1388-2457},
  medline-jid = {100883319},
  medline-mhda = {2004/09/08 05:00},
  medline-own = {NLM},
  medline-pl = {Netherlands},
  medline-pmid = {15351361},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Clin Neurophysiol 2004 Oct;115(10):2195-222.},
  medline-stat = {in-data-review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15351361},
  year = 2004
}
@ARTICLE{MO06,
  author = {Murakami, S. and Okada, Y.},
  title = {Contributions of principal neocortical neurons to
                   magnetoencephalography and electroencephalography
                   signals.},
  journal = {J Physiol},
  volume = {575},
  number = {Pt 3},
  pages = {925-36},
  abstract = {A realistically shaped three-dimensional single-neuron
                   model was constructed for each of four principal cell
                   types in the neocortex in order to infer their
                   contributions to magnetoencephalography (MEG) and
                   electroencephalography (EEG) signals. For each cell,
                   the soma was stimulated and the resulting intracellular
                   current was used to compute the current dipole Q for
                   the whole cell or separately for the apical and basal
                   dendrites. The magnitude of Q is proportional to the
                   magnetic field and electrical potential far from the
                   neuron. A train of spikes and depolarization shift in
                   an intracellular burst discharge were seen as spikes
                   and an envelope in Q for the layer V and layer II/III
                   pyramidal cells. The stellate cells lacked the
                   envelope. As expected, the pyramidal cells produced a
                   stronger Q than the stellate cells. The spikes produced
                   by the layer V pyramidal cells (n = 4) varied between
                   -0.78 and 2.97 pA m with the majority of the cells
                   showing a current toward the pia (defined as positive).
                   The basal dendrites, however, produced considerable
                   spike currents. The magnitude and direction of dipole
                   moment are in agreement with the distribution of the
                   dendrites. The spikes in Q for the layer V pyramidal
                   cells were produced by the transient sodium conductance
                   and potassium conductance of delayed rectifier type;
                   the conductances distributed along the dendrites were
                   capable of generating spike propagation, which was seen
                   in Q as the tail of a triphasic wave lasting several
                   milliseconds. The envelope was similar in magnitude
                   (-0.41 to -0.90 pA m) across the four layer V pyramidal
                   cells. The spike and envelope for the layer II/III
                   pyramidal cell were 0.47 and -0.29 pA m, respectively;
                   these values agreed well with empirical and theoretical
                   estimates for guinea pig CA3 pyramidal cells. Spikes
                   were stronger for the layer IV spiny stellate (0.27 pA
                   m) than the layer III aspiny stellate cell (0.06 pA m)
                   along their best orientations. The spikes may thus be
                   stronger than has been previously thought. The Q for a
                   population of stellate cells may be weaker than a
                   linear sum of their individual Q values due to their
                   variable dendritic geometry. The burst discharge by
                   pyramidal cells may be detectable with MEG and EEG when
                   10 000-50 000 cells are synchronously active.},
  authoraddress = {Division of Molecular and Cellular Pharmacology,
                   Department of Pharmacology, Graduate School of
                   Medicine, Osaka University, 2-2 Yamada-oka, Suita,
                   Osaka 565-0871 Japan.
                   murakami@pharma2.med.osaka-u.ac.jp},
  language = {eng},
  medline-aid = {jphysiol.2006.105379 [pii] ;
                   10.1113/jphysiol.2006.105379 [doi]},
  medline-da = {20060915},
  medline-dep = {20060413},
  medline-edat = {2006/04/15 09:00},
  medline-fau = {Murakami, Shingo ; Okada, Yoshio},
  medline-gr = {R01-NS21149/NS/NINDS ; R03-NS50544/NS/NINDS},
  medline-is = {0022-3751 (Print)},
  medline-jid = {0266262},
  medline-jt = {The Journal of physiology.},
  medline-mhda = {2006/04/15 09:00},
  medline-own = {NLM},
  medline-phst = {2006/04/13 [aheadofprint]},
  medline-pl = {England},
  medline-pmid = {16613883},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {J Physiol. 2006 Sep 15;575(Pt 3):925-36. Epub 2006 Apr
                   13.},
  medline-stat = {In-Process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16613883},
  year = 2006
}
@ARTICLE{MPF01,
  author = {Mechelli, A. and Price, C. J. and Friston, K. J.},
  title = {Nonlinear coupling between evoked r{CBF} and {BOLD}
                   signals: a simulation study of hemodynamic responses},
  journal = {NeuroImage},
  volume = {14},
  number = {4},
  pages = {862-872},
  abstract = {The aim of this work was to investigate the dependence
                   of BOLD responses on different patterns of stimulus
                   input/neuronal changes. In an earlier report, we
                   described an input-state-output model that combined (i)
                   the Balloon/Windkessel model of nonlinear coupling
                   between rCBF and BOLD signals, and (ii) a linear model
                   of how regional flow changes with synaptic activity. In
                   the present investigation, the input-state-output model
                   was used to explore the dependence of simulated PET
                   (rCBF) and fMRI (BOLD) signals on various parameters
                   pertaining to experimental design. Biophysical
                   simulations were used to estimate rCBF and BOLD
                   responses as functions of (a) a prior stimulus, (b)
                   epoch length (for a fixed SOA), (c) SOA (for a fixed
                   number of events), and (d) stimulus amplitude. We also
                   addressed the notion that a single neuronal response
                   may differ, in terms of the relative contributions of
                   early and late neural components, and investigated the
                   effect of (e) the relative size of the late or
                   "endogenous" neural component. We were interested in
                   the estimated average rCBF and BOLD responses per
                   stimulus or event, not in the statistical efficiency
                   with which these responses are detected. The BOLD
                   response was underestimated relative to rCBF with a
                   preceding stimulus, increasing epoch length, and
                   increasing SOA. Furthermore, the BOLD response showed
                   some highly nonlinear behaviour when varying stimulus
                   amplitude, suggesting some form of hemodynamic
                   "rectification." Finally, the BOLD response was
                   underestimated in the context of large late neuronal
                   components. The difference between rCBF and BOLD is
                   attributed to the nonlinear transduction of rCBF to
                   BOLD signal. Our simulations support the idea that
                   varying parameters that specify the experimental design
                   may have differential effects in PET and fMRI.
                   Moreover, they show that fMRI can be asymmetric in its
                   ability to detect deactivations relative to activations
                   when an absolute baseline is stipulated. Finally, our
                   simulations suggest that relative insensitivity to BOLD
                   signal in specific regions, such as the temporal lobe,
                   may be partly explained by higher cognitive functions
                   eliciting a relatively large late endogenous neuronal
                   component.},
  authoraddress = {Wellcome Department of Cognitive Neurology, Institute
                   of Neurology, 12 Queen Square, London, WC1N 3BG, United
                   Kingdom.},
  keywords = {Arousal/*physiology ; Brain/*blood supply ;
                   Comparative Study ; Hemodynamic Processes/*physiology ;
                   Human ; *Image Enhancement ; Image Processing,
                   Computer-Assisted ; *Magnetic Resonance Imaging ;
                   Models, Neurological ; Neurons/physiology ; *Nonlinear
                   Dynamics ; Oxygen/*blood/physiology ; Regional Blood
                   Flow/physiology ; Sensitivity and Specificity ;
                   Support, Non-U.S. Gov't ; Tomography, Emission-Computed},
  language = {eng},
  medline-aid = {10.1006/nimg.2001.0876 [doi] ; S1053811901908766 [pii]},
  medline-ci = {Copyright 2001 Academic Press.},
  medline-da = {20010913},
  medline-dcom = {20011204},
  medline-edat = {2001/09/14 10:00},
  medline-fau = {Mechelli, A ; Price, C J ; Friston, K J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {2002/01/05 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11554805},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {NeuroImage 2001 Oct;14(4):862-72.},
  medline-stat = {completed},
  year = 2001
}
@ARTICLE{MPP+06,
  author = {Mattout, J. and Phillips, C. and Penny, W. D. and
                   Rugg, M. D. and Friston, K. J.},
  title = {M{EG} source localization under multiple constraints:
                   an extended {B}ayesian framework.},
  journal = {Neuroimage},
  volume = {30},
  number = {3},
  pages = {753-67},
  abstract = {To use Electroencephalography (EEG) and
                   Magnetoencephalography (MEG) as functional brain 3D
                   imaging techniques, identifiable distributed source
                   models are required. The reconstruction of EEG/MEG
                   sources rests on inverting these models and is
                   ill-posed because the solution does not depend
                   continuously on the data and there is no unique
                   solution in the absence of prior information or
                   constraints. We have described a general framework that
                   can account for several priors in a common inverse
                   solution. An empirical Bayesian framework based on
                   hierarchical linear models was proposed for the
                   analysis of functional neuroimaging data [Friston, K.,
                   Penny, W., Phillips, C., Kiebel, S., Hinton, G.,
                   Ashburner, J., 2002. Classical and Bayesian inference
                   in neuroimaging: theory. NeuroImage 16, 465-483] and
                   was evaluated recently in the context of EEG [Phillips,
                   C., Mattout, J., Rugg, M.D., Maquet, P., Friston, K.,
                   2005. An empirical Bayesian solution to the source
                   reconstruction problem in EEG. NeuroImage 24,
                   997-1011]. The approach consists of estimating the
                   expected source distribution and its conditional
                   variance that is constrained by an empirically
                   determined mixture of prior variance components.
                   Estimation uses Expectation-Maximization (EM) to give
                   the Restricted Maximum Likelihood (ReML) estimate of
                   the variance components (in terms of hyperparameters)
                   and the Maximum A Posteriori (MAP) estimate of the
                   source parameters. In this paper, we extend the
                   framework to compare different combinations of priors,
                   using a second level of inference based on Bayesian
                   model selection. Using Monte-Carlo simulations, ReML is
                   first compared to a classic Weighted Minimum Norm (WMN)
                   solution under a single constraint. Then, the ReML
                   estimates are evaluated using various combinations of
                   priors. Both standard criterion and ROC-based measures
                   were used to assess localization and detection
                   performance. The empirical Bayes approach proved useful
                   as: (1) ReML was significantly better than WMN for
                   single priors; (2) valid location priors improved ReML
                   source localization; (3) invalid location priors did
                   not significantly impair performance. Finally, we show
                   how model selection, using the log-evidence, can be
                   used to select the best combination of priors. This
                   enables a global strategy for multiple prior-based
                   regularization of the MEG/EEG source reconstruction.},
  authoraddress = {Wellcome Department of Imaging Neuroscience, 12 Queen
                   Square, WC1N 3BG London, UK. jmattout@fil.ion.ucl.ac.uk},
  language = {eng},
  medline-aid = {S1053-8119(05)02418-3 [pii] ;
                   10.1016/j.neuroimage.2005.10.037 [doi]},
  medline-da = {20060417},
  medline-dep = {20051220},
  medline-edat = {2005/12/22 09:00},
  medline-fau = {Mattout, Jeremie ; Phillips, Christophe ; Penny,
                   William D ; Rugg, Michael D ; Friston, Karl J},
  medline-gr = {Wellcome Trust},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2005/12/22 09:00},
  medline-own = {NLM},
  medline-phst = {2005/04/07 [received] ; 2005/10/19 [revised] ;
                   2005/10/31 [accepted] ; 2005/12/20 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16368248},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 Apr 15;30(3):753-67. Epub 2005 Dec
                   20.},
  medline-stat = {In-Process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16368248},
  year = 2006
}
@ARTICLE{MRK+03,
  author = {Moosmann, M. and Ritter, P. and Krastel, I. and Brink,
                   A. and Thees, S. and Blankenburg, F. and Taskin, B. and
                   Obrig, H. and Villringer, A.},
  title = {Correlates of alpha rhythm in functional magnetic
                   resonance imaging and near infrared spectroscopy},
  journal = {NeuroImage},
  volume = {20},
  number = {1},
  pages = {145-158},
  abstract = {We used simultaneous electroencephalogram-functional
                   magnetic resonance imaging (EEG-fMRI) and EEG-near
                   infrared spectroscopy (NIRS) to investigate whether
                   changes of the posterior EEG alpha rhythm are
                   correlated with changes in local cerebral blood
                   oxygenation. Cross-correlation analysis of slowly
                   fluctuating, spontaneous rhythms in the EEG and the
                   fMRI signal revealed an inverse relationship between
                   alpha activity and the fMRI-blood oxygen level
                   dependent signal in the occipital cortex. The NIRS-EEG
                   measurements demonstrated a positive cross-correlation
                   in occipital cortex between alpha activity and
                   concentration changes of deoxygenated hemoglobin, which
                   peaked at a relative shift of about 8 s. Our data
                   suggest that alpha activity in the occipital cortex is
                   associated with metabolic deactivation. Mapping of
                   spontaneously synchronizing distributed neuronal
                   networks is thus shown to be feasible.},
  authoraddress = {Department of Neurology, Charite, Humboldt University,
                   Berlin, Germany. moosmann@charite.de},
  keywords = {Adult ; *Alpha Rhythm ; Brain Chemistry/*physiology ;
                   Electroencephalography ; Energy Metabolism/physiology ;
                   Female ; Hemoglobins/metabolism ; Human ; *Magnetic
                   Resonance Imaging ; Male ; Oxygen/*blood ; Photic
                   Stimulation ; *Spectroscopy, Near-Infrared ; Support,
                   Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1053811903003446 [pii]},
  medline-da = {20031006},
  medline-dcom = {20031121},
  medline-edat = {2003/10/07 05:00},
  medline-fau = {Moosmann, Matthias ; Ritter, Petra ; Krastel, Ina ;
                   Brink, Andrea ; Thees, Sebastian ; Blankenburg, Felix ;
                   Taskin, Birol ; Obrig, Hellmuth ; Villringer, Arno},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2003/12/03 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {14527577},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-rn = {0 (Hemoglobins) ; 7782-44-7 (Oxygen) ; 9008-02-0
                   (deoxyhemoglobin)},
  medline-sb = {IM},
  medline-so = {NeuroImage 2003 Sep;20(1):145-58.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=14527577},
  year = 2003
}
@ARTICLE{MRS+04,
  author = {Makiranta, M. J. and Ruohonen, J. and Suominen, K. and
                   Sonkajarvi, E. and Salomaki, T. and Kiviniemi, V. and
                   Seppanen, T. and Alahuhta, S. and Jantti, V. and
                   Tervonen, O.},
  title = {B{OLD}-contrast functional {MRI} signal changes
                   related to intermittent rhythmic delta activity in
                   {EEG} during voluntary hyperventilation-simultaneous
                   {EEG} and f{MRI} study},
  journal = {NeuroImage},
  volume = {22},
  number = {1},
  pages = {222-231},
  abstract = {Differences in the blood oxygen level dependent (BOLD)
                   signal changes were studied during voluntary
                   hyperventilation (HV) between young healthy volunteer
                   groups, (1) with intermittent rhythmic delta activity
                   (IRDA) (N = 4) and (2) controls (N = 4) with only
                   diffuse arrhythmic slowing in EEG (normal response).
                   Subjects hyperventilated (3 min) during an 8-min
                   functional MRI in a 1.5-T scanner, with simultaneous
                   recording of EEG (successful with N = 3 in both groups)
                   and physiological parameters. IRDA power and average
                   BOLD signal intensities (of selected brain regions)
                   were calculated. Hypocapnia showed a tendency to be
                   slightly lighter in the controls than in the IRDA
                   group. IRDA power increased during the last minute of
                   HV and ended 10-15 s after HV. The BOLD signal
                   decreased in white and gray matter after the onset of
                   HV and returned to the baseline within 2 min after HV.
                   The BOLD signal in gray matter decreased approximately
                   30\% more in subjects with IRDA than in controls,
                   during the first 2 min of HV. This difference
                   disappeared (in three subjects out of four) during IRDA
                   in EEG. BOLD signal changes seem to depict changes,
                   which precede IRDA. IRDA due to HV in healthy
                   volunteers represent a model with a clearly defined EEG
                   pattern and an observable BOLD signal change.},
  authoraddress = {Department of Clinical Neurophysiology, Oulu
                   University Hospital, University of Oulu, Kajaanintie
                   50, 90220 Oulu, Finland. Minna.Makiranta@oulu.fi},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2004.01.004 [doi] ;
                   S1053811904000266 [pii]},
  medline-da = {20040427},
  medline-edat = {2004/04/28 05:00},
  medline-fau = {Makiranta, Minna J ; Ruohonen, Jyrki ; Suominen,
                   Kalervo ; Sonkajarvi, Eila ; Salomaki, Timo ;
                   Kiviniemi, Vesa ; Seppanen, Tapio ; Alahuhta, Seppo ;
                   Jantti, Ville ; Tervonen, Osmo},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/04/28 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Jul/28 [received] ; 2003/Dec/24 [revised] ;
                   2004/Jan/05 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15110012},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 May;22(1):222-31.},
  medline-stat = {in-process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15110012},
  year = 2004
}
@ARTICLE{MS04,
  author = {Malmivuo, J.A. and Suihko, V.E.},
  title = {Effect of skull resistivity on the spatial resolutions
                   of {EEG} and {MEG}.},
  journal = {IEEE Trans Biomed Eng},
  volume = {51},
  number = {7},
  pages = {1276-1280},
  abstract = {The resistivity values of the different tissues of the
                   head affect the lead fields of electroencephalography
                   (EEG). When the head is modeled with a concentric
                   spherical model, the different resistivity values have
                   no effect on the lead fields of the
                   magnetoencephalography (MEG). Recent publications
                   indicate that the resistivity of the skull is much
                   lower than what was estimated by Rush and Driscoll. At
                   the moment, this information on skull resistivity is,
                   however, slightly controversial. We have compared the
                   spatial resolution of EEG and MEG for cortical sources
                   by calculating the half-sensitivity volumes (HSVs) of
                   EEG and MEG as a function of electrode and magnetometer
                   distance, respectively, with the relative skull
                   resistivity as a parameter. Because the spatial
                   resolution is related to the HSV, these data give an
                   overview of the effect of these parameters on the
                   spatial resolution of both techniques. Our calculations
                   show that, with the new information on the resistivity
                   of the skull, in the spherical model for cortical
                   sources the spatial resolution of the EEG is better
                   than that of the MEG.},
  authoraddress = {Ragnar Granit Institute, Tampere University of
                   Technology, FIN-33101 Tampere, Finland.
                   jaakko.malmivuo@tut.fi},
  keywords = {Brain/*physiology ; Comparative Study ; Computer
                   Simulation ; Electric Impedance ; Electrodes ;
                   Electroencephalography/*methods ; Head/physiology ;
                   Human ; Magnetoencephalography/*methods ; *Models,
                   Neurological ; Reproducibility of Results ; Sensitivity
                   and Specificity ; Skull/*physiology ; Support, Non-U.S.
                   Gov't},
  language = {eng},
  medline-da = {20040713},
  medline-dcom = {20040810},
  medline-edat = {2004/07/14 05:00},
  medline-ein = {IEEE Trans Biomed Eng. 2004 Jul;51(7):1295},
  medline-fau = {Malmivuo, Jaakko A ; Suihko, Veikko E},
  medline-is = {0018-9294},
  medline-jid = {0012737},
  medline-lr = {20040811},
  medline-mhda = {2004/08/11 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {15248545},
  medline-pst = {ppublish},
  medline-pt = {Evaluation Studies ; Journal Article},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng 2004 Jul;51(7):1276-80.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15248545},
  year = 2004
}
@ARTICLE{MVH+02,
  author = {McKeown, M. J. and Varadarajan, V. and Huettel, S. and
                   McCarthy, G.},
  title = {Deterministic and stochastic features of f{MRI} data:
                   implications for analysis of event-related experiments.},
  journal = {J Neurosci Methods},
  volume = {118},
  number = {2},
  pages = {103-113},
  abstract = {As the limits of stimuli presentation rates are
                   explored in event-related fMRI design, there is a
                   greater need to assess the implications of averaging
                   raw fMRI data. Selective averaging assumes that the
                   fMRI signal consists of task-dependent signal, random
                   noise, and non-task dependent brain signal that can be
                   modeled as random noise so that it tends to zero when
                   averaged over a practical number of trials. We recorded
                   a total of four fMRI data series from two normal
                   subjects (subject 1, axially acquired; subject 2,
                   coronally acquired) performing a simple visual
                   event-related task and a water phantom with the same
                   fMRI scanner imaging parameters. To determine which
                   fraction of the fMRI data was deterministic as opposed
                   to random, we created different data subsets by taking
                   the odd or even time points of the full data sets. All
                   data sets were first dimension-reduced with principal
                   component analysis (PCA) and separated into 100
                   spatially independent components with independent
                   component analysis (ICA). The mutual information
                   between best-matching pairs of components selected from
                   full data set-subset comparisons was plotted for each
                   data set. Visual inspection suggested that 45-85
                   components were reproducible, and hence deterministic,
                   accounting for 79-97\% of the variance, respectively,
                   in the raw data. The reproducible components exhibited
                   much less trial-to-trial variability than the raw data
                   from even the most activated voxel. Many (22-47) of
                   reproducible components were significantly affected by
                   stimulus presentation (P < 0.001). The most
                   significantly-stimulus-correlated component was
                   strongly time-locked to stimulus presentation and was
                   directly stimulus correlated, corresponding to
                   occipital brain regions. However, other spatially
                   distinct task-related components demonstrated variable
                   temporal relationships with the most
                   significantly-stimulus-correlated component. Our
                   results suggest that the majority of the variance in
                   fMRI data is in fact deterministic, and support the
                   notion that the data consist of differing components
                   with differing temporal relationships to visual
                   stimulation. They further suggest roles for restricting
                   interpretations of the spatial extent of activation
                   from event-related designs to a specific region of
                   interest (ROI) and/or first separating the data into
                   spatially independent components. Averaging the time
                   courses of spatially independent components time-locked
                   to stimulus presentation may prevent possible biases in
                   the estimates of the spatial and temporal extent of
                   stimulus-correlated activation and of trial-to-trial
                   variability.},
  authoraddress = {Brain Imaging and Analysis Center, Center for
                   Cognitive Neuroscience, 254E Bell Research Building,
                   Box 3918, Duke University Medical Center, Durham, NC
                   27710, USA. martin.mckeown@duke.edu},
  keywords = {Analysis of Variance ; Brain/physiology ; Data
                   Interpretation, Statistical ; *Evoked Potentials ;
                   Human ; Magnetic Resonance Imaging/*statistics &
                   numerical data ; Phantoms, Imaging ; Principal
                   Component Analysis},
  language = {eng},
  medline-aid = {S0165027002001206 [pii]},
  medline-ci = {Copyright 2002 Elsevier Science B.V.},
  medline-da = {20020902},
  medline-dcom = {20021016},
  medline-edat = {2002/09/03 10:00},
  medline-fau = {McKeown, Martin J ; Varadarajan, Vijay ; Huettel,
                   Scott ; McCarthy, Gregory},
  medline-is = {0165-0270},
  medline-jid = {7905558},
  medline-mhda = {2002/10/17 04:00},
  medline-own = {NLM},
  medline-pl = {Netherlands},
  medline-pmid = {12204302},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {J Neurosci Methods 2002 Aug 30;118(2):103-13.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12204302},
  year = 2002
}
@ARTICLE{MVM+04,
  author = {Martinez-Montes, E. and Valdes-Sosa, P. A. and
                   Miwakeichi, F. and Goldman, R. I. and Cohen, M. S.},
  title = {Concurrent {EEG}/f{MRI} analysis by multiway {P}artial
                   {L}east {S}quares},
  journal = {NeuroImage},
  volume = {22},
  number = {3},
  pages = {1023-1034},
  abstract = {Data may now be recorded concurrently from EEG and
                   functional MRI, using the Simultaneous Imaging for
                   Tomographic Electrophysiology (SITE) method. As yet,
                   there is no established means to integrate the analysis
                   of the combined data set. Recognizing that the
                   hemodynamically convolved time-varying EEG spectrum, S,
                   is intrinsically multidimensional in space, frequency,
                   and time motivated us to use multiway Partial
                   Least-Squares (N-PLS) analysis to decompose EEG
                   (independent variable) and fMRI (dependent variable)
                   data uniquely as a sum of "atoms". Each EEG atom is the
                   outer product of spatial, spectral, and temporal
                   signatures and each fMRI atom the product of spatial
                   and temporal signatures. The decomposition was
                   constrained to maximize the covariance between
                   corresponding temporal signatures of the EEG and fMRI.
                   On all data sets, three components whose spectral peaks
                   were in the theta, alpha, and gamma bands appeared;
                   only the alpha atom had a significant temporal
                   correlation with the fMRI signal. The spatial
                   distribution of the alpha-band atom included
                   parieto-occipital cortex, thalamus, and insula, and
                   corresponded closely to that reported by Goldman et al.
                   [NeuroReport 13(18) (2002) 2487] using a more
                   conventional analysis. The source reconstruction from
                   EEG spatial signature showed only the parieto-occipital
                   sources. We interpret these results to indicate that
                   some electrical sources may be intrinsically invisible
                   to scalp EEG, yet may be revealed through conjoint
                   analysis of EEG and fMRI data. These results may also
                   expose brain regions that participate in the control of
                   brain rhythms but may not themselves be generators. As
                   of yet, no single neuroimaging method offers the
                   optimal combination of spatial and temporal resolution;
                   fusing fMRI and EEG meaningfully extends the
                   spatio-temporal resolution and sensitivity of each
                   method.},
  authoraddress = {Neurophysics Department, Cuban Neuroscience Center,
                   Havana, Cuba. eduardo@cneuro.edu.cu},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2004.03.038 [doi] ;
                   S1053811904001946 [pii]},
  medline-ci = {Copyright 2004 Elsevier Inc.},
  medline-da = {20040628},
  medline-edat = {2004/06/29 05:00},
  medline-fau = {Martinez-Montes, Eduardo ; Valdes-Sosa, Pedro A ;
                   Miwakeichi, Fumikazu ; Goldman, Robin I ; Cohen, Mark S},
  medline-gr = {DA13054/DA/NIDA ; DA15549/DA/NIDA},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/06/29 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Jul/17 [received] ; 2004/Mar/12 [revised] ;
                   2004/Mar/17 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15219575},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Jul;22(3):1023-34.},
  medline-stat = {in-process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15219575},
  year = 2004
}
@ARTICLE{MWI+06,
  author = {Mirsattari, S. M. and Wang, Z. and Ives, J. R. and
                   Bihari, F. and Leung, L. S. and Bartha, R. and Menon,
                   R. S.},
  title = {Linear aspects of transformation from interictal
                   epileptic discharges to {BOLD} f{MRI} signals in an
                   animal model of occipital epilepsy.},
  journal = {Neuroimage},
  volume = {30},
  number = {4},
  pages = {1133-1148},
  abstract = {Epileptic disorders manifest with seizures and
                   interictal epileptic discharges (IEDs). The hemodynamic
                   changes that accompany IEDs are poorly understood and
                   may be critical for understanding epileptogenesis.
                   Despite a known linear coupling of the neurovascular
                   elements in normal brain tissues, previous simultaneous
                   electroencephalography (EEG)-functional magnetic
                   resonance imaging (fMRI) studies have shown variable
                   correlations between epileptic discharges and blood
                   oxygenation level-dependent (BOLD) response, partly
                   because most previous studies assumed particular
                   hemodynamic properties in normal brain tissue. The
                   occurrence of IEDs in human subjects is unpredictable.
                   Therefore, an animal model with reproducible
                   stereotyped IEDs was developed by the focal injection
                   of penicillin into the right occipital cortex of rats
                   anesthetized with isoflurane. Simultaneous EEG-fMRI was
                   used to study the hemodynamic changes during IEDs. A
                   hybrid of temporal independent component analysis (ICA)
                   of EEG and spatial ICA of fMRI data was used to
                   correlate BOLD fMRI signals with IEDs. A linear
                   autoregression with exogenous input (ARX) model was
                   used to estimate the hemodynamic impulse response
                   function (HIRF) based on the data from simultaneous
                   EEG-fMRI measurement. Changes in the measured BOLD
                   signal from the right primary visual cortex and
                   bilateral visual association cortices were consistently
                   coupled to IEDs. The linear ARX model was applied here
                   to confirm that a linear transform can be used to study
                   the correlation between BOLD signal and its
                   corresponding neural activity in this animal model of
                   occipital epilepsy.},
  authoraddress = {Faculty of Graduate Studies, The University of Western
                   Ontario, London, Canada; Department of Clinical
                   Neurological Sciences, The University of Western
                   Ontario, London, Canada; Laboratory for Functional
                   Magnetic Resonance Research, Robarts Research
                   Institute, PO Box 5015, 100 Perth Drive, London,
                   Ontario, Canada.},
  language = {ENG},
  medline-aid = {S1053-8119(05)02445-6 [pii] ;
                   10.1016/j.neuroimage.2005.11.006 [doi]},
  medline-da = {20060508},
  medline-dep = {20060118},
  medline-edat = {2006/01/18 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2006/01/18 09:00},
  medline-own = {NLM},
  medline-phst = {2005/01/17 [received] ; 2005/10/29 [revised] ;
                   2005/11/02 [accepted] ; 2006/01/18 [aheadofprint]},
  medline-pmid = {16414283},
  medline-pst = {ppublish},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2006 May 1;30(4):1133-1148. Epub 2006 Jan
                   18.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16414283},
  year = 2006
}
@ARTICLE{NAN+04,
  author = {Negishi, M. and Abildgaard, M. and Nixon, T. and Todd
                   Constable, R.},
  title = {Removal of time-varying gradient artifacts from {EEG}
                   data acquired during continuous f{MRI}},
  journal = {Clin Neurophysiol},
  volume = {115},
  number = {9},
  pages = {2181-2192},
  abstract = {Objective: Recording low amplitude
                   electroencephalography (EEG) signals in the face of
                   large gradient artifacts generated by changing
                   functional magnetic resonance imaging (fMRI) magnetic
                   fields continues to be a challenge. We present a new
                   method of removing gradient artifacts with time-varying
                   waveforms, and evaluate it in continuous
                   (non-interleaved) simultaneous EEG-fMRI experiments.
                   Methods: The current method consists of an analog
                   filter, an EEG-fMRI timing error correction algorithm,
                   and a temporal principal component analysis based
                   gradient noise removal algorithm. We conducted a
                   phantom experiment and a visual oddball experiment to
                   evaluate the method. Results: The results from the
                   phantom experiment showed that the current method
                   reduced the number of averaged samples required to
                   obtain high correlation between injected and recovered
                   signals, compared to a conventional average waveform
                   subtraction method with adaptive noise canceling. For
                   the oddball experiment, the results obtained from the
                   two methods were very similar, except that the current
                   method resulted in a higher P300 amplitude when the
                   number of averaged trials was small. Conclusions: The
                   current method enabled us to obtain high quality EEGs
                   in continuous simultaneous EEG-fMRI experiments.
                   Significance: Continuous simultaneous EEG-fMRI
                   acquisition enables efficient use of data acquisition
                   time and better monitoring of rare EEG events.},
  authoraddress = {Department of Diagnostic Radiology, Yale University
                   School of Medicine, P.O. Box 208043, TAC Building MRRC
                   Rm. N128, New Haven, CT 06520-8043, USA.},
  language = {eng},
  medline-aid = {10.1016/j.clinph.2004.04.005 [doi] ; S1388245704001476
                   [pii]},
  medline-da = {20040805},
  medline-edat = {2004/08/06 05:00},
  medline-fau = {Negishi, Michiro ; Abildgaard, Mark ; Nixon, Terry ;
                   Todd Constable, Robert},
  medline-is = {1388-2457},
  medline-jid = {100883319},
  medline-mhda = {2004/08/06 05:00},
  medline-own = {NLM},
  medline-phst = {2004/Apr/08 [accepted]},
  medline-pl = {Netherlands},
  medline-pmid = {15294222},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Clin Neurophysiol 2004 Sep;115(9):2181-92.},
  medline-stat = {in-data-review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15294222},
  year = 2004
}
@ARTICLE{NBI+05,
  author = {Niazy, R. K. and Beckmann, C. F. and Iannetti, G. D.
                   and Brady, J. M. and Smith, S. M.},
  title = {Removal of {FMRI} environment artifacts from {EEG}
                   data using optimal basis sets.},
  journal = {Neuroimage},
  volume = {28},
  number = {3},
  pages = {720-37},
  abstract = {The combination of functional magnetic resonance
                   imaging (FMRI) and electroencephalography (EEG) has
                   received much recent attention, since it potentially
                   offers a new tool for neuroscientists that makes
                   simultaneous use of the strengths of the two
                   modalities. However, EEG data collected in such
                   experiments suffer from two kinds of artifact. First,
                   gradient artifacts are caused by the switching of
                   magnetic gradients during FMRI. Second,
                   ballistocardiographic (BCG) artifacts related to
                   cardiac activities further contaminate the EEG data.
                   Here we present new methods to remove both kinds of
                   artifact. The methods are based primarily on the idea
                   that temporal variations in the artifacts can be
                   captured by performing temporal principal component
                   analysis (PCA), which leads to the identification of a
                   set of basis functions which describe the temporal
                   variations in the artifacts. These basis functions are
                   then fitted to, and subtracted from, EEG data to
                   produce artifact-free results. In addition, we also
                   describe a robust algorithm for the accurate detection
                   of heart beat peaks from poor quality
                   electrocardiographic (ECG) data that are collected for
                   the purpose of BCG artifact removal. The methods are
                   tested and are shown to give superior results to
                   existing methods. The methods also demonstrate the
                   feasibility of simultaneous EEG/FMRI experiments using
                   the relatively low EEG sampling frequency of 2048 Hz.},
  authoraddress = {University of Oxford, Centre for Functional MRI of the
                   Brain (FMRIB), John Radcliffe Hospital, Headington,
                   Oxford OX3 9DU, UK. rami@fmrib.ox.ac.uk},
  keywords = {Algorithms ; *Artifacts ; Electrocardiography ;
                   Electroencephalography/*statistics & numerical data ;
                   Evoked Potentials/physiology ; Heart Rate/physiology ;
                   Humans ; Image Processing, Computer-Assisted/*methods ;
                   Lasers ; Magnetic Resonance Imaging/*statistics &
                   numerical data ; Principal Component Analysis ;
                   Reproducibility of Results ; Research Support, Non-U.S.
                   Gov't},
  language = {eng},
  medline-aid = {S1053-8119(05)00472-6 [pii] ;
                   10.1016/j.neuroimage.2005.06.067 [doi]},
  medline-da = {20051031},
  medline-dcom = {20060117},
  medline-dep = {20050916},
  medline-edat = {2005/09/10 09:00},
  medline-fau = {Niazy, R K ; Beckmann, C F ; Iannetti, G D ; Brady, J
                   M ; Smith, S M},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2006/01/18 09:00},
  medline-own = {NLM},
  medline-phst = {2005/04/09 [received] ; 2005/06/08 [revised] ;
                   2005/06/23 [accepted] ; 2005/09/16 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16150610},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2005 Nov 15;28(3):720-37. Epub 2005 Sep
                   16.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16150610},
  year = 2005
}
@ARTICLE{NCF+04,
  author = {Nagai, Y. and Critchley, H. D. and Featherstone, E.
                   and Fenwick, P. B. and Trimble, M. R. and Dolan, R. J.},
  title = {Brain activity relating to the contingent negative
                   variation: an f{MRI} investigation.},
  journal = {Neuroimage},
  volume = {21},
  number = {4},
  pages = {1232-41},
  abstract = {The contingent negative variation (CNV) is a
                   long-latency electroencephalography (EEG) surface
                   negative potential with cognitive and motor components,
                   observed during response anticipation. CNV is an index
                   of cortical arousal during orienting and attention, yet
                   its functional neuroanatomical basis is poorly
                   understood. We used functional magnetic resonance
                   imaging (fMRI) with simultaneous EEG and recording of
                   galvanic skin response (GSR) to investigate CNV-related
                   central neural activity and its relationship to
                   peripheral autonomic arousal. In a group analysis,
                   blood oxygenation level dependent (BOLD) activity
                   during the period of CNV generation was enhanced in
                   thalamus, somatomotor cortex, bilateral midcingulate,
                   supplementary motor, and insular cortices. Enhancement
                   of CNV-related activity in anterior and midcingulate,
                   SMA, and insular cortices was associated with decreases
                   in peripheral sympathetic arousal. In a subset of
                   subjects in whom we acquired simultaneous EEG and fMRI
                   data, we observed activity in bilateral thalamus,
                   anterior cingulate, and supplementary motor cortex that
                   was modulated by trial-by-trial amplitude of CNV. These
                   findings provide a likely functional neuroanatomical
                   substrate for the CNV and demonstrate modulation of
                   components of this neural circuitry by peripheral
                   autonomic arousal. Moreover, these data suggest a
                   mechanistic model whereby thalamocortical interactions
                   regulate CNV amplitude.},
  authoraddress = {Institute of Neurology, Department of Clinical and
                   Experimental Epilepsy, London WC1N 3BG, UK.
                   y.nagai@ion.ucl.ac.uk},
  keywords = {Adult ; Arousal/*physiology ; Brain/*physiology ;
                   Brain Mapping ; Cerebral Cortex/*physiology ;
                   Contingent Negative Variation/*physiology ; Dominance,
                   Cerebral/physiology ; *Electroencephalography ; Female
                   ; Galvanic Skin Response/physiology ; Gyrus
                   Cinguli/physiology ; Humans ; *Image Enhancement ;
                   *Image Processing, Computer-Assisted ; *Magnetic
                   Resonance Imaging ; Male ; Neural Pathways/physiology ;
                   Oxygen/*blood ; Peripheral Nervous System/physiology ;
                   Psychomotor Performance/physiology ; Reaction
                   Time/physiology ; Research Support, Non-U.S. Gov't ;
                   Sympathetic Nervous System/physiology ;
                   Thalamus/physiology},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.10.036 [doi] ;
                   S1053811903007067 [pii]},
  medline-da = {20040330},
  medline-dcom = {20040806},
  medline-edat = {2004/03/31 05:00},
  medline-fau = {Nagai, Y ; Critchley, H D ; Featherstone, E ; Fenwick,
                   P B C ; Trimble, M R ; Dolan, R J},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-lr = {20041117},
  medline-mhda = {2004/08/07 05:00},
  medline-own = {NLM},
  medline-phst = {2003/05/06 [received] ; 2003/10/30 [revised] ;
                   2003/10/31 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15050551},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2004 Apr;21(4):1232-41.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15050551},
  year = 2004
}
@ARTICLE{NPP+07,
  author = {Negishi, M. and Pinus, B. I. and Pinus, A. B. and
                   Constable, R. T.},
  title = {Origin of the radio frequency pulse artifact in
                   simultaneous {EEG}-f{MRI} recording: rectification at
                   the carbon-metal interface.},
  journal = {IEEE Trans Biomed Eng},
  volume = {54},
  number = {9},
  pages = {1725-7},
  abstract = {Simultaneous electroencephalograph-functional magnetic
                   resonance imaging (EEG-fMRI) recording has become an
                   important tool for investigating spatiotemporal
                   properties of brain events, such as epilepsy, evoked
                   brain responses, and changes in brain rhythms.
                   Reduction of noise in EEG signals during fMRI recording
                   is crucial for acquiring high-quality EEG-fMRI data.
                   The main source of the noise includes the gradient
                   artifact, the radio frequency (RF) pulse artifact, and
                   the cardiac pulse artifact. Since the RF pulse artifact
                   is relatively small in amplitude, little attention has
                   been paid to this artifact, and its origin is not well
                   understood. However, the amplitude of the RF pulse
                   artifact fluctuates randomly even if a very high EEG
                   sampling rate is used, making it more salient than the
                   gradient artifact after postprocessing for noise
                   removal. In this paper, we investigate the cause of the
                   RF pulse artifact in EEG systems that use carbon wires.},
  authoraddress = {Department of Diagnostic Radiology, School of
                   Medicine, Yale University, New Haven, CT 06520-8043,
                   USA. michiro.negishi@yale.edu},
  language = {eng},
  medline-da = {20070917},
  medline-edat = {2007/09/18 09:00},
  medline-fau = {Negishi, Michiro ; Pinus, Boris I ; Pinus, Alexander B
                   ; Constable, R Todd},
  medline-gr = {R01-NS47605/NS/NINDS},
  medline-is = {0018-9294 (Print)},
  medline-jid = {0012737},
  medline-jt = {IEEE transactions on bio-medical engineering},
  medline-mhda = {2007/09/18 09:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {17867368},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Research Support, N.I.H., Extramural
                   ; Research Support, Non-U.S. Gov't},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng. 2007 Sep;54(9):1725-7.},
  medline-stat = {In-Process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17867368},
  year = 2007
}
@ARTICLE{NS00,
  author = {Nunez, P. L. and Silberstein, R. B.},
  title = {On the relationship of synaptic activity to
                   macroscopic measurements: does co-registration of {EEG}
                   with f{MRI} make sense?},
  journal = {Brain Topogr},
  volume = {13},
  number = {2},
  pages = {79-96},
  abstract = {A two-scale theoretical description outlines
                   relationships between brain current sources and the
                   resulting extracranial electric field, recorded as EEG.
                   Finding unknown sources of EEG, the so-called "inverse
                   problem", is discussed in general terms, with emphasis
                   on the fundamental non-uniqueness of inverse solutions.
                   Hemodynamic signatures, measured with fMRI, are
                   expressed as voxel integrals to facilitate comparisons
                   with EEG. Two generally distinct cell groups (1 and 2),
                   generating EEG and fMRI signals respectively, are
                   embedded within the much broader class of synaptic
                   action fields. Cell groups 1 and 2 may or may not
                   overlap in specific experiments. Implications of this
                   incomplete overlap for co-registration studies are
                   considered. Each experimental measure of brain function
                   is generally sensitive to a different kind of source
                   activity and to different spatial and temporal scales.
                   Failure to appreciate such distinctions can exacerbate
                   conflicting views of brain function that emphasize
                   either global integration or functional localization.},
  authoraddress = {The Brain Sciences Institute, Melbourne, Australia.},
  keywords = {Brain/*physiology/radionuclide imaging ;
                   *Electroencephalography ; Human ; *Magnetic Resonance
                   Imaging ; Magnetoencephalography ; Models, Neurological
                   ; Synapses/*physiology ; Tomography, Emission-Computed},
  language = {eng},
  medline-da = {20010110},
  medline-dcom = {20010308},
  medline-edat = {2001/01/12 11:00},
  medline-fau = {Nunez, P L ; Silberstein, R B},
  medline-is = {0896-0267},
  medline-jid = {8903034},
  medline-mhda = {2001/03/10 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11154104},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {67},
  medline-sb = {IM},
  medline-so = {Brain Topogr 2000 Winter;13(2):79-96.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11154104},
  year = 2000
}
@ARTICLE{Nai05,
  author = {Nair, D.G.},
  title = {About being {BOLD}.},
  journal = {Brain Res Brain Res Rev},
  abstract = {The last decade has seen an unprecedented increase in
                   the use of functional magnetic resonance imaging (fMRI)
                   to understand the neural basis of cognition and
                   behavior. Being non-invasive and relatively easy to
                   use, most studies relied on changes in the blood
                   oxygenation level dependent (BOLD) contrast as an
                   indirect marker of variations in brain activity.
                   However, the fact that BOLD fMRI is dependent on the
                   blood flow response that follows neural activity and
                   does not measure neural activity per se is seen as an
                   inherent cause for concern while interpreting data from
                   these studies. In order to characterize the BOLD signal
                   correctly, it is imperative that we have a better
                   understanding of neural events that lead to the BOLD
                   response. A review of recent studies that addressed
                   several aspects of BOLD fMRI including events at the
                   level of the synapse, the nature of the neurovascular
                   coupling, and some parameters of the BOLD signal is
                   provided. This is intended to serve as background
                   information for the interpretation of fMRI data in
                   normal subjects and in patients with compromised
                   neurovascular coupling. One of the aims is also to
                   encourage researchers to interpret the results of
                   functional imaging studies in light of the dynamic
                   interactions between different brain regions, something
                   that often is neglected.},
  authoraddress = {Palmer 127, Department of Neurology, Beth Israel
                   Deaconess Medical Center/Harvard Medical School,
                   Boston, MA 02215, USA.},
  language = {ENG},
  medline-aid = {S0165-0173(05)00111-6 [pii] ;
                   10.1016/j.brainresrev.2005.07.001 [doi]},
  medline-da = {20051010},
  medline-dep = {20051003},
  medline-edat = {2005/10/11 09:00},
  medline-is = {0165-0173},
  medline-jid = {8908638},
  medline-mhda = {2005/10/11 09:00},
  medline-own = {NLM},
  medline-phst = {2005/02/24 [received] ; 2005/06/16 [revised] ;
                   2005/07/13 [accepted]},
  medline-pmid = {16213027},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Brain Res Brain Res Rev 2005 Oct 3;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16213027},
  year = 2005
}
@ARTICLE{Nie97,
  author = {Niedermeyer, E.},
  title = {Alpha rhythms as physiological and abnormal phenomena},
  journal = {Int J Psychophysiol},
  volume = {26},
  number = {1-3},
  pages = {31-49},
  abstract = {There are three physiological alpha rhythms in mature
                   healthy humans: (a) the classical posterior alpha; (b)
                   the Rolandic mu rhythm and (c) the midtemporal 'third
                   rhythm'. The classical posterior alpha rhythm develops
                   out of a 4/s rhythm appearing at age 4 months and
                   gradually reaches the alpha frequency band around age 3
                   years. The mature frequency around 10/s is subject to
                   subtle physiological changes and grossly decelerates in
                   the face of pathology. No posterior alpha rhythm may be
                   detectable in a minority of healthy adults with an
                   inherited low voltage fast EEG. One is tempted to
                   speculate that these individuals may have a hidden
                   alpha rhythm in neuronal level and defective mechanisms
                   of synchronization. Alpha blocking with visual stimuli
                   (eye opening) is a classical response; responses to
                   mental stimuli (mental arithmetic) are inconsistent,
                   presumably due to the involvement of higher cognitive
                   functions. The Rolandic my rhythm is found with scalp
                   EEG in a minority of subjects but there is good reason
                   to presume that all healthy adults have this rhythm. A
                   particularly powerful mu rhythm reaches the scalp but
                   this could be also an indicator of a mild CNS
                   dysfunction. There is even a relationship between mu
                   rhythm and the central spike activity in children with
                   benign Rolandic epilepsy. The midtemporal third rhythm
                   is not detectable in the scalp EEG unless there are
                   local bone defects. Its functional significance is
                   debatable; its blocking responses encompass various
                   higher cognitive tasks and are inconsistent; responses
                   to auditory stimuli do occur but appear to be of
                   secondary significance. This rhythm arises from
                   midtemporal structures which by far exceed the borders
                   of the auditory cortex. Abnormal rhythmical alpha
                   activity-above all the alpha coma in life-threatening
                   cerebral anoxia -is discussed in order to deepen our
                   understanding of the physiological alpha rhythms.
                   Severe cortical de-afferentation may give rise to
                   cortical autorhythmicity-either in alpha frequency or
                   in other frequency bands. Physiological alpha rhythms
                   are likely to have closer relationships to 'events'
                   than one might have thought earlier. The demonstration
                   of event-related desynchronization and synchronization
                   (in Pfurtscheller's work) clearly underscores this
                   view.},
  authoraddress = {Department of Neurology, John Hopkins University
                   School of Medicine and Hospital, Baltimore, MD
                   21287-7247, USA.},
  keywords = {*Alpha Rhythm ; Animals ; Brain/*physiology ;
                   *Electroencephalography ; Human},
  language = {eng},
  medline-da = {19970904},
  medline-dcom = {19970904},
  medline-edat = {1997/06/01},
  medline-fau = {Niedermeyer, E},
  medline-is = {0167-8760},
  medline-jid = {8406214},
  medline-lr = {20031114},
  medline-mhda = {1997/06/01 00:01},
  medline-own = {NLM},
  medline-pl = {NETHERLANDS},
  medline-pmid = {9202993},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {84},
  medline-sb = {IM},
  medline-so = {Int J Psychophysiol 1997 Jun;26(1-3):31-49.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9202993},
  year = 1997
}
@ARTICLE{Nolte-2003a,
  author = {Nolte, G.},
  title = {The magnetic lead field theorem in the quasi-static
                  approximation and its use for magnetoencephalography
                  forward calculation in realistic volume conductors},
  year = 2003,
  journal = {Phys. Med. Biol.},
  volume = 48,
  pages = {3637-3652},
  url = {http://stacks.iop.org/PMB/48/3637},
  month = NOV
}
@ARTICLE{OGF07,
  author = {Otzenberger, H. and Gounot, D. and Foucher, J. R.},
  title = {Optimisation of a post-processing method to remove the
                   pulse artifact from {EEG} data recorded during f{MRI}:
                   an application to {P}300 recordings during e-f{MRI}.},
  journal = {Neurosci Res},
  volume = {57},
  number = {2},
  pages = {230-9},
  abstract = {In functional cerebral studies, it has been
                   established that co-registered electroencephalography
                   (EEG) measurements and functional magnetic resonance
                   imaging (fMRI) were complementary. However, EEG data
                   recorded inside an MRI scanner are heavily distorted,
                   mainly by the most prominent artifact, the cardiac
                   pulse artifact (PA). We describe an original algorithm
                   which yields a high-quality PA filter and demonstrates
                   how this tool can be used to improve the quality of
                   P300 ERP measurements during event-related fMRI
                   (e-fMRI) experiments. EEG data were acquired in
                   interleaved mode during e-fMRI while six healthy
                   volunteers performed a visual odd-ball task, involving
                   Distractors, Target and Novel stimuli, to elicit P300
                   components. The PA was corrected with the original
                   algorithm. The temporal variations in the PA were
                   evidenced using a principal component analysis (PCA),
                   on each EEG channel. The procedure yielded several PA
                   templates, which were regressed from the EEG data. The
                   PA removal procedure was optimised, and then
                   implemented to improve the measured P300 components.
                   Regressing the most adequate PA template resulted in a
                   high-quality reduction in spectral power at frequencies
                   associated with the cardiac PA. More reliable P300
                   component measurements were obtained, evidencing higher
                   amplitudes for Novels (9.76-11.20 microV) than for to
                   Targets (6.3-9.09 microV) in centro-parietal and
                   prefrontal areas. The improvement of the processing of
                   EEG data acquired simultaneously with fMRI data
                   provides a new tool and casts perspectives to study the
                   functional organisation of the brain.},
  authoraddress = {UMR 7004 Laboratoire de Neuroimagerie in vivo,
                   Universite Louis Pasteur, Centre National de Recherche
                   Scientifique, IFR 37 de Neurosciences, 4 rue
                   Kirschleger, 67085 Strasbourg Cedex, France.
                   otzenber@ipb.u-strasbg.fr},
  keywords = {Adult ; *Artifacts ; Brain Mapping ; Cerebral
                   Cortex/blood supply/physiology ; *Diagnostic
                   Techniques, Neurological ; *Electroencephalography ;
                   Event-Related Potentials, P300/*physiology ; Female ;
                   Humans ; Image Processing, Computer-Assisted ;
                   *Magnetic Resonance Imaging ; Male ; *Subtraction
                   Technique},
  language = {eng},
  medline-aid = {S0168-0102(06)00282-3 [pii] ;
                   10.1016/j.neures.2006.10.014 [doi]},
  medline-da = {20070205},
  medline-dcom = {20070417},
  medline-dep = {20061206},
  medline-edat = {2006/12/13 09:00},
  medline-fau = {Otzenberger, H ; Gounot, D ; Foucher, J R},
  medline-is = {0168-0102 (Print)},
  medline-jid = {8500749},
  medline-jt = {Neuroscience research},
  medline-mhda = {2007/04/18 09:00},
  medline-own = {NLM},
  medline-phst = {2006/04/27 [received] ; 2006/10/09 [revised] ;
                   2006/10/24 [accepted] ; 2006/12/06 [aheadofprint]},
  medline-pl = {Ireland},
  medline-pmid = {17157401},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Research Support, Non-U.S. Gov't},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neurosci Res. 2007 Feb;57(2):230-9. Epub 2006 Dec 6.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17157401},
  year = 2007
}
@ARTICLE{OLK+90,
  author = {Ogawa, S. and Lee, T. M. and Kay, A. R. and Tank, D.
                   W.},
  title = {Brain magnetic resonance imaging with contrast
                   dependent on blood oxygenation},
  journal = {Proc Natl Acad Sci U S A},
  volume = {87},
  number = {24},
  pages = {9868-9872},
  abstract = {Paramagnetic deoxyhemoglobin in venous blood is a
                   naturally occurring contrast agent for magnetic
                   resonance imaging (MRI). By accentuating the effects of
                   this agent through the use of gradient-echo techniques
                   in high fields, we demonstrate in vivo images of brain
                   microvasculature with image contrast reflecting the
                   blood oxygen level. This blood oxygenation
                   level-dependent (BOLD) contrast follows blood oxygen
                   changes induced by anesthetics, by insulin-induced
                   hypoglycemia, and by inhaled gas mixtures that alter
                   metabolic demand or blood flow. The results suggest
                   that BOLD contrast can be used to provide in vivo
                   real-time maps of blood oxygenation in the brain under
                   normal physiological conditions. BOLD contrast adds an
                   additional feature to magnetic resonance imaging and
                   complements other techniques that are attempting to
                   provide positron emission tomography-like measurements
                   related to regional neural activity.},
  authoraddress = {Biophysics Research Department, AT&T Bell
                   Laboratories, Murray Hill, NJ 07974.},
  keywords = {Animals ; *Blood Flow Velocity ; Brain/*anatomy &
                   histology/physiology/physiopathology ; Carbon
                   Dioxide/blood ; *Cerebrovascular Circulation ; Female ;
                   Hemoglobins/*metabolism ; Hypoglycemia/physiopathology
                   ; Kinetics ; Magnetic Resonance Imaging/methods ;
                   Models, Neurological ; Oxygen/*blood ; Rats ; Rats,
                   Inbred Strains},
  language = {eng},
  medline-da = {19910207},
  medline-dcom = {19910207},
  medline-edat = {1990/12/01},
  medline-fau = {Ogawa, S ; Lee, T M ; Kay, A R ; Tank, D W},
  medline-is = {0027-8424},
  medline-jid = {7505876},
  medline-lr = {20031114},
  medline-mhda = {1990/12/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {2124706},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {0 (Hemoglobins) ; 124-38-9 (Carbon Dioxide) ;
                   7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Proc Natl Acad Sci U S A 1990 Dec;87(24):9868-72.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=2124706},
  year = 1990
}
@ARTICLE{OLM+04,
  author = {Obata, T. and Liu, T.T. and Miller, K.L. and Luh, W.M.
                   and Wong, E.C. and Frank, L.R. and Buxton, R.B.},
  title = {Discrepancies between {BOLD} and flow dynamics in
                   primary and supplementary motor areas: application of
                   the balloon model to the interpretation of {BOLD}
                   transients.},
  journal = {Neuroimage},
  volume = {21},
  number = {1},
  pages = {144-53},
  abstract = {The blood-oxygen-level-dependent (BOLD) signal
                   measured in the brain with functional magnetic
                   resonance imaging (fMRI) during an activation
                   experiment often exhibits pronounced transients at the
                   beginning and end of the stimulus. Such transients
                   could be a reflection of transients in the underlying
                   neural activity, or they could result from transients
                   in cerebral blood flow (CBF), cerebral metabolic rate
                   of oxygen (CMRO2), or cerebral blood volume (CBV).
                   These transients were investigated using an arterial
                   spin labeling (ASL) method that allows simultaneous
                   measurements of BOLD and CBF responses. Responses to a
                   finger-tapping task (40-s stimulus, 80-s rest) were
                   measured in primary motor area (M1) and supplementary
                   motor area (SMA) in five healthy volunteers. In SMA,
                   the average BOLD response was pronounced near the
                   beginning and end of the stimulus, while in M1, the
                   BOLD response was nearly flat. However, CBF responses
                   in the two regions were rather similar, and did not
                   exhibit the same transient features as the BOLD
                   response in SMA. Because this suggests a hemodynamic
                   rather than a neural origin for the transients of the
                   BOLD response in SMA, we used a generalization of the
                   balloon model to test the degree of hemodynamic
                   transients required to produce the measured curves.
                   Both data sets could be approximated with modest
                   differences in the shapes of the CMRO2 and CBV
                   responses. This study illustrates the utility and the
                   limitations of using theoretical models combined with
                   ASL techniques to understand the dynamics of the BOLD
                   response.},
  authoraddress = {Department of Radiology, University of California at
                   San Diego, 92039-0677, La Jolla, CA, USA.
                   t\_obata@nirs.go.jp},
  keywords = {Adult ; Blood Volume/physiology ; Brain Mapping ;
                   Energy Metabolism/physiology ; Hemoglobins/metabolism ;
                   Humans ; Image Enhancement/*methods ; *Image
                   Processing, Computer-Assisted ; Magnetic Resonance
                   Imaging/*methods ; *Models, Neurological ; Models,
                   Theoretical ; Motor Activity/*physiology ; Motor
                   Cortex/*blood supply/physiology ; Oxygen/*blood ;
                   Oxygen Consumption/physiology ; Reference Values ;
                   Regional Blood Flow/physiology ; Reproducibility of
                   Results ; Research Support, Non-U.S. Gov't ; Research
                   Support, U.S. Gov't, P.H.S. ; Spin Labels},
  language = {eng},
  medline-aid = {S1053811903005494 [pii]},
  medline-da = {20040126},
  medline-dcom = {20040326},
  medline-edat = {2004/01/27 05:00},
  medline-fau = {Obata, Takayuki ; Liu, Thomas T ; Miller, Karla L ;
                   Luh, Wen Ming ; Wong, Eric C ; Frank, Lawrence R ;
                   Buxton, Richard B},
  medline-gr = {NS36722/NS/NINDS},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-lr = {20041117},
  medline-mhda = {2004/03/27 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {14741651},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {0 (Hemoglobins) ; 0 (Spin Labels) ; 7782-44-7 (Oxygen)
                   ; 9008-02-0 (deoxyhemoglobin)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2004 Jan;21(1):144-53.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=14741651},
  year = 2004
}
@ARTICLE{OLN+90,
  author = {Ogawa, S. and Lee, T.M. and Nayak, A.S. and Glynn, P.},
  title = {Oxygenation-sensitive contrast in magnetic resonance
                   image of rodent brain at high magnetic fields.},
  journal = {Magn Reson Med},
  volume = {14},
  number = {1},
  pages = {68-78},
  abstract = {At high magnetic fields (7 and 8.4 T), water proton
                   magnetic resonance images of brains of live mice and
                   rats under pentobarbital anesthetization have been
                   measured by a gradient echo pulse sequence with a
                   spatial resolution of 65 x 65-microns pixel size and
                   700-microns slice thickness. The contrast in these
                   images depicts anatomical details of the brain by
                   numerous dark lines of various sizes. These lines are
                   absent in the image taken by the usual spin echo
                   sequence. They represent the blood vessels in the image
                   slice and appear when the deoxyhemoglobin content in
                   the red cells increases. This contrast is most
                   pronounced in an anoxy brain but not present in a brain
                   with diamagnetic oxy or carbon monoxide hemoglobin. The
                   local field induced by the magnetic susceptibility
                   change in the blood due to the paramagnetic
                   deoxyhemoglobin causes the intra voxel dephasing of the
                   water signals of the blood and the surrounding tissue.
                   This oxygenation-dependent contrast is appreciable in
                   high field images with high spatial resolution.},
  authoraddress = {AT&T Bell Laboratories, Murray Hill, New Jersey
                   07974.},
  keywords = {Animals ; Brain/anatomy & histology/blood
                   supply/*metabolism ; Magnetic Resonance Imaging ;
                   *Magnetic Resonance Spectroscopy/methods ; Mice ;
                   *Oxygen Consumption ; Protons ; Rats ; Rats, Inbred
                   Strains},
  language = {eng},
  medline-da = {19900716},
  medline-dcom = {19900716},
  medline-edat = {1990/04/01},
  medline-fau = {Ogawa, S ; Lee, T M ; Nayak, A S ; Glynn, P},
  medline-is = {0740-3194},
  medline-jid = {8505245},
  medline-lr = {20031114},
  medline-mhda = {1990/04/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {2161986},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {0 (Protons)},
  medline-sb = {IM},
  medline-so = {Magn Reson Med 1990 Apr;14(1):68-78.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=2161986},
  year = 1990
}
@ARTICLE{OMT+93,
  author = {Ogawa, S. and Menon, R. S. and Tank, D. W. and Kim, S.
                   -. G. and Merkle, H. and Ellermann, J. M. and Ugurbil,
                   K.},
  title = {Functional brain mapping by blood oxygenation
                   level-dependent contrast magnetic resonance imaging. A
                   comparison of signal characteristics with a biophysical
                   model},
  journal = {Biophysical Journal},
  authoraddress = {Biolog. Computation Research Dept., AT and T Bell
                   Laboratories, Murray Hill, NJ 07974, United States AB -
                   It recently has been demonstrated that magnetic
                   resonance imaging can be used to map changes in brain
                   hemodynamics produced by human mental operations. One
                   method under development relies on blood oxygenation
                   level-dependent (BOLD) contrast: a change in the signal
                   strength of brain water protons produced by the
                   paramagnetic effects of venous blood deoxyhemoglobin.
                   Here we discuss the basic quantitative features of the
                   observed BOLD-based signal changes, including the
                   signal amplitude and its magnetic field dependence and
                   dynamic effects such as a pronounced oscillatory
                   pattern that is induced in the signal from primary
                   visual cortex during photic stimulation experiments.
                   The observed features are compared with the results of
                   Monte Carlo simulations of water proton intravoxel
                   phase dispersion produced by local field gradients
                   generated by paramagnetic deoxyhemoglobin in nearby
                   venous blood vessels. The simulations suggest that the
                   effect of water molecule diffusion is strong for the
                   case of blood capillaries, but, for larger venous blood
                   vessels, water diffusion is not an important
                   determinant of deoxyhemoglobin-induced signal
                   dephasing. We provide an expressicn for the apparent
                   in-plane relaxation rate constant (R2*) in terms of the
                   main magnetic field strength, the degree of the
                   oxygenation of the venous blood, the venous blood
                   volume fraction in the tissue, and the size of the
                   blood vessel.},
  medline-ep = {812},
  medline-is = {3},
  medline-n1 = {Cited By: 0; Export Date: 21 June 2006; Source: Scopus},
  medline-sp = {803},
  medline-ty = {JOUR},
  url = {http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-0027263961&partner=40&rel=R4.5.0},
  medline-vl = {64},
  year = 1993
}
@ARTICLE{OPH+04,
  author = {Oakes, T. R. and Pizzagalli, D. A. and Hendrick, A. M.
                   and Horras, K. A. and Larson, C. L. and Abercrombie, H.
                   C. and Schaefer, S. M. and Koger, J. V. and Davidson,
                   R. J.},
  title = {Functional coupling of simultaneous electrical and
                   metabolic activity in the human brain},
  journal = {Hum Brain Mapp},
  volume = {21},
  number = {4},
  pages = {257-270},
  abstract = {The relationships between brain electrical and
                   metabolic activity are being uncovered currently in
                   animal models using invasive methods; however, in the
                   human brain this relationship remains not well
                   understood. In particular, the relationship between
                   noninvasive measurements of electrical activity and
                   metabolism remains largely undefined. To understand
                   better these relations, cerebral activity was measured
                   simultaneously with electroencephalography (EEG) and
                   positron emission tomography using
                   [(18)f]-fluoro-2-deoxy-D-glucose (PET-FDG) in 12 normal
                   human subjects during rest. Intracerebral distributions
                   of current density were estimated, yielding tomographic
                   maps for seven standard EEG frequency bands. The PET
                   and EEG data were registered to the same space and
                   voxel dimensions, and correlational maps were created
                   on a voxel-by-voxel basis across all subjects. For each
                   band, significant positive and negative correlations
                   were found that are generally consistent with extant
                   understanding of EEG band power function. With
                   increasing EEG frequency, there was an increase in the
                   number of positively correlated voxels, whereas the
                   lower alpha band (8.5-10.0 Hz) was associated with the
                   highest number of negative correlations. This work
                   presents a method for comparing EEG signals with other
                   more traditionally tomographic functional imaging data
                   on a 3-D basis. This method will be useful in the
                   future when it is applied to functional imaging methods
                   with faster time resolution, such as short half-life
                   PET blood flow tracers and functional magnetic
                   resonance imaging.},
  authoraddress = {W M Keck Laboratory for Functional Brain Imaging and
                   Behavior, University of Wisconsin-Madison, Madison,
                   Wisconsin 53705, USA. oakes@falstaff.wisc.edu},
  keywords = {Adult ; Brain/*metabolism/radionuclide imaging ; Brain
                   Mapping/*methods ; Electroencephalography/*methods ;
                   Energy Metabolism/physiology ; Female ; Fludeoxyglucose
                   F 18/diagnostic use ; Glucose/metabolism ; Human ; Male
                   ; Middle Aged ; Support, Non-U.S. Gov't ; Support, U.S.
                   Gov't, P.H.S. ; *Tomography, Emission-Computed},
  language = {eng},
  medline-aid = {10.1002/hbm.20004 [doi]},
  medline-ci = {Copyright 2004 Wiley-Liss, Inc.},
  medline-da = {20040323},
  medline-dcom = {20040528},
  medline-edat = {2004/03/24 05:00},
  medline-fau = {Oakes, Terrence R ; Pizzagalli, Diego A ; Hendrick,
                   Andrew M ; Horras, Katherine A ; Larson, Christine L ;
                   Abercrombie, Heather C ; Schaefer, Stacey M ; Koger,
                   John V ; Davidson, Richard J},
  medline-gr = {F31-MH12085/MH/NIMH ; K05-MH00875/MH/NIMH ;
                   MH40747/MH/NIMH ; MH43454/MH/NIMH ; P50-MH52354/MH/NIMH},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-mhda = {2004/05/29 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {15038007},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {50-99-7 (Glucose) ; 63503-12-8 (Fludeoxyglucose F 18)},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 2004 Apr;21(4):257-70.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15038007},
  year = 2004
}
@ARTICLE{PGP93,
  author = {Pruis, G. W. and Gilding, B. H. and Peters, M. J.},
  title = {A comparison of different numerical methods for
                   solving the forward problem in {EEG} and {MEG}},
  journal = {Physiol Meas},
  volume = {14 Suppl 4A},
  pages = {A1-9},
  abstract = {In view of the complexity of the conductivity and the
                   geometry of the human head, a numerical method would
                   appear to be necessary for the adequate calculation of
                   the electric potential and the magnetic induction
                   generated by electric sources within the brain. Four
                   numerical methods that could be used for solving this
                   problem are the finite-difference method, the
                   finite-element method, the boundary-element method, and
                   the finite-volume method. These methods could be used
                   to calculate the electric potential and the magnetic
                   induction directly. Alternatively, they could be
                   applied to the electric potential or the electric field
                   and the magnetic induction could then be determined by
                   numerical integration of the Biot-Savart law. In this
                   paper the four numerical methods are briefly reviewed.
                   Thereafter the relative merits of the methods and the
                   various options for using them to solve the EEG and MEG
                   problem are evaluated.},
  authoraddress = {Faculty of Applied Physics, University of Twente,
                   Enschede, The Netherlands.},
  keywords = {Brain Mapping/*methods ; Comparative Study ;
                   *Electroencephalography ; Human ;
                   *Magnetoencephalography ; Mathematics},
  language = {eng},
  medline-da = {19940210},
  medline-dcom = {19940210},
  medline-edat = {1993/11/01},
  medline-fau = {Pruis, G W ; Gilding, B H ; Peters, M J},
  medline-is = {0967-3334},
  medline-jid = {9306921},
  medline-lr = {20001218},
  medline-mhda = {1993/11/01 00:01},
  medline-own = {NLM},
  medline-pl = {ENGLAND},
  medline-pmid = {8274975},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Physiol Meas 1993 Nov;14 Suppl 4A:A1-9.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=8274975},
  year = 1993
}
@ARTICLE{PHL+90,
  author = {Pantev, C. and Hoke, M. and Lehnertz, K. and
                   Lutkenhoner, B. and Fahrendorf, G. and Stober, U.},
  title = {Identification of sources of brain neuronal activity
                   with high spatiotemporal resolution through combination
                   of neuromagnetic source localization ({NMSL}) and
                   magnetic resonance imaging ({MRI})},
  journal = {Electroencephalogr Clin Neurophysiol},
  volume = {75},
  number = {3},
  pages = {173-184},
  abstract = {The locations of the origin of wave M100 of the
                   auditory evoked magnetic field in response to tone
                   bursts of different carrier frequencies, obtained
                   through dipole localization methods (DLM), were related
                   to cerebral structures, displayed by coronal MRI
                   (magnetic resonance imaging) tomograms of the
                   respective subjects. This was done by displaying the
                   landmarks which served as reference for the
                   neuromagnetic measurements in MRI tomogram (reference
                   plane). All calculated source locations project exactly
                   onto the transverse temporal gyri (Heschl) in which the
                   primary auditory cortex, the supposed origin of wave
                   M100, is located. The results highlight the exceptional
                   capabilities of a combination of these 2 non-invasive,
                   high-resolution techniques for functional diagnosis.},
  authoraddress = {Institute of Experimental Audiology, University of
                   Munster, F.R.G.},
  keywords = {Auditory Cortex/anatomy & histology/*physiology ;
                   Brain Mapping ; *Electromagnetic Fields ;
                   *Electromagnetics/*methods ; Evoked Potentials ; Human
                   ; *Magnetic Resonance Imaging ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-da = {19900406},
  medline-dcom = {19900406},
  medline-edat = {1990/03/01},
  medline-fau = {Pantev, C ; Hoke, M ; Lehnertz, K ; Lutkenhoner, B ;
                   Fahrendorf, G ; Stober, U},
  medline-is = {0013-4694},
  medline-jid = {0375035},
  medline-lr = {20001218},
  medline-mhda = {1990/03/01 00:01},
  medline-own = {NLM},
  medline-pl = {IRELAND},
  medline-pmid = {1689641},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Electroencephalogr Clin Neurophysiol 1990
                   Mar;75(3):173-84.},
  medline-stat = {completed},
  year = 1990
}
@ARTICLE{PKdS04,
  author = {Parra, J. and Kalitzin, S. N. and da Silva, F. H.},
  title = {Magnetoencephalography: an investigational tool or a
                   routine clinical technique?},
  journal = {Epilepsy Behav},
  volume = {5},
  number = {3},
  pages = {277-85},
  abstract = {Magnetoencephalography (MEG) is a relatively novel
                   noninvasive technique, with a much shorter history than
                   EEG, that conveys neurophysiological information
                   complementary to that provided by EEG, with high
                   temporal and spatial resolution. Despite its a priori,
                   highly competitive profile, the role of MEG in the
                   clinical setting is still controversial. We briefly
                   review the major obstacles MEG faces in becoming a
                   routine clinical test and the different strategies
                   needed to bypass them. The high cost and complexity
                   associated with MEG equipment are powerful hindrances
                   to wide acceptance of this relatively new technique in
                   clinical practice. The most straightforward advantage
                   is based on the relative facility of MEG recordings in
                   the process of source localization, which also carries
                   some degree of uncertainty, thus partly explaining why
                   the development of clinical applications of MEG has
                   been so slow. Obviously, a decrease in the cost and the
                   elaboration of semiautomatic protocols that could
                   reduce the complexity of the studies and favor the
                   development of consensual strategies, as well as a
                   major effort on the part of clinicians to identify
                   clinical issues where MEG could be decisive, would be
                   most welcome.},
  authoraddress = {Dutch Epilepsy Clinics Foundation, "Meer en Bosch,"
                   Heemstede, The Netherlands. jparra@sein.nl},
  keywords = {*Behavior ; Brain/*pathology/physiopathology ; Brain
                   Mapping ; Electroencephalography/methods ;
                   Electromagnetic Fields ;
                   Epilepsy/*diagnosis/physiopathology ; Evoked
                   Potentials/physiology ; Humans ;
                   Magnetoencephalography/economics/*methods},
  language = {eng},
  medline-aid = {10.1016/j.yebeh.2004.02.003 [doi] ; S1525505004000563
                   [pii]},
  medline-da = {20040517},
  medline-dcom = {20040706},
  medline-edat = {2004/05/18 05:00},
  medline-fau = {Parra, Jaime ; Kalitzin, Stiliyan N ; da Silva,
                   Fernando H Lopes},
  medline-is = {1525-5050 (Print)},
  medline-jid = {100892858},
  medline-jt = {Epilepsy & behavior : E&B.},
  medline-lr = {20051116},
  medline-mhda = {2004/07/09 05:00},
  medline-own = {NLM},
  medline-phst = {2004/02/09 [received] ; 2004/02/10 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15145295},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review},
  medline-pubm = {Print},
  medline-rf = {68},
  medline-sb = {IM},
  medline-so = {Epilepsy Behav. 2004 Jun;5(3):277-85.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15145295},
  year = 2004
}
@ARTICLE{PMR+05,
  author = {Phillips, C. and Mattout, J. and Rugg, M. D. and
                   Maquet, P. and Friston, K. J.},
  title = {An empirical {B}ayesian solution to the source
                   reconstruction problem in {EEG}.},
  journal = {Neuroimage},
  volume = {24},
  number = {4},
  pages = {997-1011},
  abstract = {Distributed linear solutions of the EEG source
                   localisation problem are used routinely. In contrast to
                   discrete dipole equivalent models, distributed linear
                   solutions do not assume a fixed number of active
                   sources and rest on a discretised fully 3D
                   representation of the electrical activity of the brain.
                   The ensuing inverse problem is underdetermined and
                   constraints or priors are required to ensure the
                   uniqueness of the solution. In a Bayesian framework,
                   the conditional expectation of the source distribution,
                   given the data, is attained by carefully balancing the
                   minimisation of the residuals induced by noise and the
                   improbability of the estimates as determined by their
                   priors. This balance is specified by hyperparameters
                   that control the relative importance of fitting and
                   conforming to various constraints. Here we formulate
                   the conventional "Weighted Minimum Norm" (WMN) solution
                   in terms of hierarchical linear models. An
                   "Expectation-Maximisation" (EM) algorithm is used to
                   obtain a "Restricted Maximum Likelihood" (ReML)
                   estimate of the hyperparameters, before estimating the
                   "Maximum a Posteriori" solution itself. This procedure
                   can be considered a generalisation of previous work
                   that encompasses multiple constraints. Our approach was
                   compared with the "classic" WMN and Maximum Smoothness
                   solutions, using a simplified 2D source model with
                   synthetic noisy data. The ReML solution was assessed
                   with four types of source location priors: no priors,
                   accurate priors, inaccurate priors, and both accurate
                   and inaccurate priors. The ReML approach proved useful
                   as: (1) The regularisation (or influence of the a
                   priori source covariance) increased as the noise level
                   increased. (2) The localisation error (LE) was
                   negligible when accurate location priors were used. (3)
                   When accurate and inaccurate location priors were used
                   simultaneously, the solution was not influenced by the
                   inaccurate priors. The ReML solution was then applied
                   to real somatosensory-evoked responses to illustrate
                   the application in an empirical setting.},
  authoraddress = {Centre de Recherches du Cyclotron, B30, Universite de
                   Liege, Liege 4000, Belgium. c.philips@ulg.ac.be},
  keywords = {Algorithms ; Artifacts ; *Bayes Theorem ;
                   Electroencephalography/*statistics & numerical data ;
                   Evoked Potentials, Somatosensory/physiology ; Humans ;
                   Image Processing, Computer-Assisted/*statistics &
                   numerical data ; Likelihood Functions ; Magnetic
                   Resonance Imaging},
  language = {eng},
  medline-aid = {S1053-8119(04)00623-8 [pii] ;
                   10.1016/j.neuroimage.2004.10.030 [doi]},
  medline-da = {20050126},
  medline-dcom = {20050419},
  medline-dep = {20050105},
  medline-edat = {2005/01/27 09:00},
  medline-fau = {Phillips, Christophe ; Mattout, Jeremie ; Rugg,
                   Michael D ; Maquet, Pierre ; Friston, Karl J},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2005/04/20 09:00},
  medline-own = {NLM},
  medline-phst = {2004/04/08 [received] ; 2004/09/23 [revised] ;
                   2004/10/21 [accepted] ; 2005/01/05 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {15670677},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2005 Feb 15;24(4):997-1011. Epub 2005 Jan
                   5.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15670677},
  year = 2005
}
@ARTICLE{PRF02a,
  author = {Phillips, C. and Rugg, M. D. and Friston, K. J.},
  title = {Anatomically informed basis functions for {EEG} source
                   localization: combining functional and anatomical
                   constraints},
  journal = {NeuroImage},
  volume = {16},
  number = {3.1},
  pages = {678-695},
  abstract = {Distributed linear solutions have frequently been used
                   to solve the source localization problem in EEG. Here
                   we introduce an approach based on the weighted minimum
                   norm (WMN) method that imposes constraints using
                   anatomical and physiological information derived from
                   other imaging modalities. The anatomical constraints
                   are used to reduce the solution space a priori by
                   modeling the spatial source distribution with a set of
                   basis functions. These spatial basis functions are
                   chosen in a principled way using information theory.
                   The reduced problem is then solved with a classical WMN
                   method. Further (functional) constraints can be
                   introduced in the weighting of the solution using fMRI
                   brain responses to augment spatial priors. We used
                   simulated data to explore the behavior of the approach
                   over a range of the model's hyperparameters. To assess
                   the construct validity of our method we compared it
                   with two established approaches to the source
                   localization problem, a simple weighted minimum norm
                   and a maximum smoothness (Loreta-like) solution. This
                   involved simulations, using single and multiple sources
                   that were analyzed under different levels of confidence
                   in the priors.},
  authoraddress = {Institute of Cognitive Neuroscience, Wellcome
                   Department of Cognitive Neurology, Institute of
                   Neurology, University College London, London, United
                   Kingdom.},
  keywords = {Brain/*anatomy & histology/*physiology ; Brain
                   Mapping/methods ; *Electroencephalography/methods ;
                   Human ; Magnetic Resonance Imaging/methods ; Models,
                   Neurological ; Reproducibility of Results},
  language = {eng},
  medline-aid = {S1053811902911432 [pii]},
  medline-da = {20020809},
  medline-dcom = {20020911},
  medline-edat = {2002/08/10 10:00},
  medline-fau = {Phillips, Christophe ; Rugg, Michael D ; Friston, Karl
                   J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2002/09/12 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12169252},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2002 Jul;16(3 Pt 1):678-95.},
  medline-stat = {completed},
  year = 2002
}
@ARTICLE{PRF02b,
  author = {Phillips, C. and Rugg, M. D. and Friston, K. J.},
  title = {Systematic regularization of linear inverse solutions
                   of the {EEG} source localization problem},
  journal = {NeuroImage},
  volume = {17},
  number = {1},
  pages = {287-301},
  abstract = {Distributed linear solutions of the EEG source
                   localization problem are used routinely. Here we
                   describe an approach based on the weighted minimum norm
                   method that imposes constraints using anatomical and
                   physiological information derived from other imaging
                   modalities to regularize the solution. In this approach
                   the hyperparameters controlling the degree of
                   regularization are estimated using restricted maximum
                   likelihood (ReML). EEG data are always contaminated by
                   noise, e.g., exogenous noise and background brain
                   activity. The conditional expectation of the source
                   distribution, given the data, is attained by carefully
                   balancing the minimization of the residuals induced by
                   noise and the improbability of the estimates as
                   determined by their priors. This balance is specified
                   by hyperparameters that control the relative importance
                   of fitting and conforming to prior constraints. Here we
                   introduce a systematic approach to this regularization
                   problem, in the context of a linear observation model
                   we have described previously. In this model, basis
                   functions are extracted to reduce the solution space a
                   priori in the spatial and temporal domains. The basis
                   sets are motivated by knowledge of the evoked EEG
                   response and information theory. In this paper we focus
                   on an iterative "expectation-maximization" procedure to
                   jointly estimate the conditional expectation of the
                   source distribution and the ReML hyperparameters on
                   which this solution rests. We used simulated data mixed
                   with real EEG noise to explore the behavior of the
                   approach with various source locations, priors, and
                   noise levels. The results enabled us to conclude: (i)
                   Solutions in the space of informed basis functions have
                   a high face and construct validity, in relation to
                   conventional analyses. (ii) The hyperparameters
                   controlling the degree of regularization vary largely
                   with source geometry and noise. The second conclusion
                   speaks to the usefulness of using adaptative ReML
                   hyperparameter estimates.},
  authoraddress = {Institute of Cognitive Neuroscience University College
                   London, London, United Kingdom.},
  keywords = {*Algorithms ; Bayes Theorem ; Brain/anatomy &
                   histology/physiology ;
                   Electroencephalography/*statistics & numerical data ;
                   Electromagnetic Fields ; Head/anatomy & histology ;
                   Linear Models ; Models, Anatomic},
  language = {eng},
  medline-da = {20021216},
  medline-dcom = {20030114},
  medline-edat = {2002/12/17 04:00},
  medline-fau = {Phillips, Christophe ; Rugg, Michael D ; Fristont,
                   Karl J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2003/01/15 04:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12482084},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2002 Sep;17(1):287-301.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12482084},
  year = 2002
}
@PHDTHESIS{Poupon99b,
  author = {Poupon, F.},
  title = {Parcellisation syst{\'e}matique du cerveau en volumes
                  d'int{\'e}r{\^e}t. Le cas des structures profondes},
  school = {INSA Lyon},
  year = 1999,
  type = {PhD thesis},
  address = {Lyon, France},
  month = DEC,
  keywords = {Segmentation},
  url = {ftp://ftp.cea.fr/pub/dsv/anatomist/papers/fpoupon-thesis99.pdf}
}
@ARTICLE{RAI+05,
  author = {Riera, J. and Aubert, E. and Iwata, K. and Kawashima,
                   R. and Wan, X. and Ozaki, T.},
  title = {Fusing {EEG} and f{MRI} based on a bottom-up model:
                   inferring activation and effective connectivity in
                   neural masses.},
  journal = {Philos Trans R Soc Lond B Biol Sci},
  volume = {360},
  number = {1457},
  pages = {1025-41},
  abstract = {The elucidation of the complex machinery used by the
                   human brain to segregate and integrate information
                   while performing high cognitive functions is a subject
                   of imminent future consequences. The most significant
                   contributions to date in this field, known as cognitive
                   neuroscience, have been achieved by using innovative
                   neuroimaging techniques, such as electroencephalogram
                   (EEG) and functional magnetic resonance imaging (fMRI),
                   which measure variations in both the time and the space
                   of some interpretable physical magnitudes.
                   Extraordinary maps of cerebral activation involving
                   function-restricted brain areas, as well as graphs of
                   the functional connectivity between them, have been
                   obtained from EEG and fMRI data by solving some
                   spatio-temporal inverse problems, which constitutes a
                   top-down approach. However, in many cases, a natural
                   bridge between these maps/graphs and the causal
                   physiological processes is lacking, leading to some
                   misunderstandings in their interpretation. Recent
                   advances in the comprehension of the underlying
                   physiological mechanisms associated with different
                   cerebral scales have provided researchers with an
                   excellent scenario to develop sophisticated biophysical
                   models that permit an integration of these neuroimage
                   modalities, which must share a common aetiology. This
                   paper proposes a bottom-up approach, involving
                   physiological parameters in a specific mesoscopic
                   dynamic equations system. Further observation equations
                   encapsulating the relationship between the mesostates
                   and the EEG/fMRI data are obtained on the basis of the
                   physical foundations of these techniques. A methodology
                   for the estimation of parameters from fused EEG/fMRI
                   data is also presented. In this context, the concepts
                   of activation and effective connectivity are carefully
                   revised. This new approach permits us to examine and
                   discuss some future prospects for the integration of
                   multimodal neuroimages.},
  authoraddress = {Advanced Science and Technology of Materials, NICHe,
                   Tohoku University, Aoba 10, Aramaki, Aobaku, Sendai
                   980-8579, Japan. riera@idac.tohoku.ac.jp},
  keywords = {Brain/anatomy & histology/*physiology ; Brain
                   Mapping/*methods ; *Data Interpretation, Statistical ;
                   Electroencephalography/*methods ; Humans ; Magnetic
                   Resonance Imaging/*methods ; *Models, Neurological ;
                   Psychomotor Performance/physiology ; Regression
                   Analysis ; Time Factors},
  language = {eng},
  medline-aid = {LJDYNHGVDU9X77FL [pii] ; 10.1098/rstb.2005.1646 [doi]},
  medline-da = {20050809},
  medline-dcom = {20051004},
  medline-edat = {2005/08/10 09:00},
  medline-fau = {Riera, J ; Aubert, E ; Iwata, K ; Kawashima, R ; Wan,
                   X ; Ozaki, T},
  medline-is = {0962-8436 (Print)},
  medline-jid = {7503623},
  medline-jt = {Philosophical transactions of the Royal Society of
                   London. Series B, Biological sciences},
  medline-lr = {20061115},
  medline-mhda = {2005/10/05 09:00},
  medline-own = {NLM},
  medline-pl = {England},
  medline-pmid = {16087446},
  medline-pst = {ppublish},
  medline-pt = {Comparative Study ; Journal Article ; Research
                   Support, Non-U.S. Gov't},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Philos Trans R Soc Lond B Biol Sci. 2005 May
                   29;360(1457):1025-41.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16087446},
  year = 2005
}
@ARTICLE{RBA+91,
  author = {Rosen, B.R. and Belliveau, J.W. and Aronen, H.J. and
                   Kennedy, D. and Buchbinder, B.R. and Fischman, A. and
                   Gruber, M. and Glas, J. and Weisskoff, R.M. and Cohen,
                   M.S. and {et al.}},
  title = {Susceptibility contrast imaging of cerebral blood
                   volume: human experience.},
  journal = {Magn Reson Med},
  volume = {22},
  number = {2},
  pages = {293-9; discussion 300-3},
  abstract = {Magnetic resonance (MR) can offer a unique window on
                   the structure/function relationships in the brain, by
                   utilizing the established link between tissue function,
                   metabolism, and hemodynamics. This report focuses on
                   recent applications of MR-based cerebral blood volume
                   (CBV) imaging in humans. Our methodology uses
                   high-speed "single-shot" or echo planar imaging
                   techniques, which provide the necessary temporal
                   resolution for mapping the rapid cerebral transit of
                   contrast agents. These MR CBV mapping techniques have
                   been used to study normal human brain task activation
                   and in the clinical study of patients with brain
                   tumors. In the latter, positron emission tomography
                   imaging was used for functional metabolic and CBV
                   correlation. Susceptibility contrast CBV imaging should
                   allow us to improve our understanding of the
                   relationship between the detailed physiology and
                   morphology of the microvascular bed and functional
                   attributes of the brain. These techniques can be
                   applied to understanding fundamental questions of
                   cognitive neuroscience and can aid in improving
                   diagnostic sensitivity and specificity in various
                   neuropathologies.},
  authoraddress = {Department of Radiology, Massachusetts General
                   Hospital, Boston 02129.},
  keywords = {Brain/*anatomy & histology ; Brain
                   Neoplasms/*diagnosis ; Cerebrovascular
                   Circulation/*physiology ; *Contrast Media ;
                   Gadolinium/*diagnostic use ; Gadolinium DTPA ; Humans ;
                   *Magnetic Resonance Imaging ; Organometallic
                   Compounds/*diagnostic use ; Pentetic Acid/*diagnostic
                   use ; Tomography, Emission-Computed ; Visual
                   Cortex/anatomy & histology},
  language = {eng},
  medline-da = {19920611},
  medline-dcom = {19920611},
  medline-edat = {1991/12/01},
  medline-fau = {Rosen, B R ; Belliveau, J W ; Aronen, H J ; Kennedy, D
                   ; Buchbinder, B R ; Fischman, A ; Gruber, M ; Glas, J ;
                   Weisskoff, R M ; Cohen, M S},
  medline-is = {0740-3194},
  medline-jid = {8505245},
  medline-lr = {20041117},
  medline-mhda = {1991/12/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {1812360},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {0 (Contrast Media) ; 0 (Organometallic Compounds) ;
                   67-43-6 (Pentetic Acid) ; 7440-54-2 (Gadolinium) ;
                   80529-93-7 (Gadolinium DTPA)},
  medline-sb = {IM},
  medline-so = {Magn Reson Med 1991 Dec;22(2):293-9; discussion 300-3.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=1812360},
  year = 1991
}
@ARTICLE{RBD98,
  author = {Rosen, B. R. and Buckner, R. L. and Dale, A. M.},
  title = {Event-related functional {MRI}: past, present, and
                   future},
  journal = {Proc Natl Acad Sci U S A},
  volume = {95},
  number = {3},
  pages = {773-780},
  abstract = {The past two decades have seen an enormous growth in
                   the field of human brain mapping. Investigators have
                   extensively exploited techniques such as positron
                   emission tomography and MRI to map patterns of brain
                   activity based on changes in cerebral hemodynamics.
                   However, until recently, most studies have investigated
                   equilibrium changes in blood flow measured over time
                   periods upward of 1 min. The advent of high-speed MRI
                   methods, capable of imaging the entire brain with a
                   temporal resolution of a few seconds, allows for brain
                   mapping based on more transient aspects of the
                   hemodynamic response. Today it is now possible to map
                   changes in cerebrovascular parameters essentially in
                   real time, conferring the ability to observe changes in
                   brain state that occur over time periods of seconds.
                   Furthermore, because robust hemodynamic alterations are
                   detectable after neuronal stimuli lasting only a few
                   tens of milliseconds, a new class of task paradigms
                   designed to measure regional responses to single
                   sensory or cognitive events can now be studied. Such
                   "event related" functional MRI should provide for
                   fundamentally new ways to interrogate brain function,
                   and allow for the direct comparison and ultimately
                   integration of data acquired by using more traditional
                   behavioral and electrophysiological methods.},
  authoraddress = {Nuclear Magnetic Resonance Center, Massachusetts
                   General Hospital, Charlestown, MA 02129, USA.},
  keywords = {Brain/*anatomy & histology/*physiology ; Brain
                   Mapping ; Cerebrovascular Circulation/physiology ;
                   Computer Systems ; Human ; *Magnetic Resonance
                   Imaging/instrumentation/methods ; Support, Non-U.S.
                   Gov't ; Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-da = {19980311},
  medline-dcom = {19980311},
  medline-edat = {1998/03/14},
  medline-fau = {Rosen, B R ; Buckner, R L ; Dale, A M},
  medline-gr = {DC03245-01/DC/NIDCD},
  medline-is = {0027-8424},
  medline-jid = {7505876},
  medline-lr = {20001218},
  medline-mhda = {1998/03/14 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9448240},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {54},
  medline-sb = {IM},
  medline-so = {Proc Natl Acad Sci U S A 1998 Feb 3;95(3):773-80.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9448240},
  year = 1998
}
@ARTICLE{RBG+07,
  author = {Ritter, P. and Becker, R. and Graefe, C. and
                   Villringer, A.},
  title = {Evaluating gradient artifact correction of {EEG} data
                   acquired simultaneously with f{MRI}.},
  journal = {Magn Reson Imaging},
  volume = {25},
  number = {6},
  pages = {923-32},
  abstract = {Simultaneous electroencephalography (EEG) and
                   functional magnetic resonance imaging (fMRI) has become
                   a widely used application in spite of EEG perturbations
                   due to electromagnetic interference in the MR
                   environment. The most prominent and disturbing
                   artifacts in the EEG are caused by the alternating
                   magnetic fields (gradients) of the MR scanner.
                   Different methods for gradient artifact correction have
                   been developed. Here we propose an approach for the
                   systematic evaluation and comparison of these gradient
                   artifact correction methods. Exemplarily, we evaluate
                   different algorithms all based on artifact template
                   subtraction--the currently most established means of
                   gradient artifact removal. We introduce indices for the
                   degree of gradient artifact reduction and physiological
                   signal preservation. The combination of both indices
                   was used as a measure for the overall performance of
                   gradient artifact removal and was shown to be useful in
                   identifying problems during artifact removal. We
                   demonstrate that the evaluation as proposed here allows
                   to reveal frequency-band specific performance
                   differences among the algorithms. This emphasizes the
                   importance of carefully selecting the artifact
                   correction method appropriate for the respective case.},
  authoraddress = {Berlin NeuroImaging Center and Charite,
                   Universitatsmedizin Berlin, Berlin, Germany.
                   petra.ritter@charite.de},
  language = {eng},
  medline-aid = {S0730-725X(07)00215-9 [pii] ;
                   10.1016/j.mri.2007.03.005 [doi]},
  medline-da = {20070727},
  medline-dep = {20070426},
  medline-edat = {2007/04/28 09:00},
  medline-fau = {Ritter, Petra ; Becker, Robert ; Graefe, Christine ;
                   Villringer, Arno},
  medline-is = {0730-725X (Print)},
  medline-jid = {8214883},
  medline-jt = {Magnetic resonance imaging},
  medline-mhda = {2007/04/28 09:00},
  medline-own = {NLM},
  medline-phst = {2007/01/11 [accepted] ; 2007/04/26 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {17462844},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Magn Reson Imaging. 2007 Jul;25(6):923-32. Epub 2007
                   Apr 26.},
  medline-stat = {In-Process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17462844},
  year = 2007
}
@ARTICLE{RBY+04,
  author = {Riera, J. and Bosch, J. and Yamashita, O. and
                   Kawashima, R. and Sadato, N. and Okada, T. and Ozaki,
                   T.},
  title = {{f}{MRI} activation maps based on the {NN}-{AR}x
                   model.},
  journal = {Neuroimage},
  volume = {23},
  number = {2},
  pages = {680-97},
  abstract = {The most significant progresses in the understanding
                   of human brain functions have been possible due to the
                   use of functional magnetic resonance imaging (fMRI),
                   which when used in combination with other standard
                   neuroimaging techniques (i.e., EEG) provides
                   researchers with a potential tool to elucidate many
                   biophysical principles, established previously by
                   animal comparative studies. However, to date, most of
                   the methods proposed in the literature seeking fMRI
                   signs have been limited to the use of a top-down data
                   analysis approach, thus ignoring a pool of
                   physiological facts. In spite of the important
                   contributions achieved by applying these methods to
                   actual data, there is a disproportionate gap between
                   theoretical models and data-analysis strategies while
                   trying to focus on several new prospects, like for
                   example fMRI/EEG data fusion, causality/connectivity
                   patterns, and nonlinear BOLD signal dynamics. In this
                   paper, we propose a new approach which will allow many
                   of the abovementioned hot topics to be addressed in the
                   near future with an underlying interpretability based
                   on bottom-up modeling. In particular, the theta-MAP
                   presented in the paper to test brain activation
                   corresponds very well with the standardized t test of
                   the SPM99 toolbox. Additionally, a new Impulse Response
                   Function (IRF) has been formulated, directly related to
                   the well-established concept of the hemodynamics
                   response function (HRF). The model uses not only the
                   information contained in the signal but also that in
                   the structure of the background noise to simultaneously
                   estimate the IRF and the autocorrelation function (ACF)
                   by using an autoregressive (AR) model with a filtered
                   Poisson process driving the dynamics. The short-range
                   contributions of voxels within the near-neighborhood
                   are also included, and the potential drift was
                   characterized by a polynomial series. Since our model
                   originated from an immediate extension of the
                   hemodynamics approach [Friston, K.J., Mechelli, A.,
                   Turner, R., Price C.J. (2000a). Nonlinear responses in
                   fMRI: the balloon model, volterra kernels, and other
                   hemodynamics. NeuroImage 12, 466-477.], a natural
                   interpretability of the results is feasible.},
  authoraddress = {Advanced Science and Technology of Materials NICHe,
                   Tohoku University, Aoba 10, Aramaki, Aobaku, Sendai
                   980-8579, Japan. riera@idac.tohoku.ac.jp},
  keywords = {Algorithms ; Brain Mapping/*methods ; Cerebrovascular
                   Circulation/physiology ; Cluster Analysis ; Computer
                   Simulation ; Electroencephalography ; Humans ; Linear
                   Models ; Magnetic Resonance Imaging/*methods ; Models,
                   Neurological ; Movement/physiology ; Oxygen/blood ;
                   Photic Stimulation ; Reproducibility of Results},
  language = {eng},
  medline-aid = {S1053-8119(04)00363-5 [pii] ;
                   10.1016/j.neuroimage.2004.06.039 [doi]},
  medline-da = {20041018},
  medline-dcom = {20050105},
  medline-edat = {2004/10/19 09:00},
  medline-fau = {Riera, J ; Bosch, J ; Yamashita, O ; Kawashima, R ;
                   Sadato, N ; Okada, T ; Ozaki, T},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage},
  medline-lr = {20061115},
  medline-mhda = {2005/01/06 09:00},
  medline-own = {NLM},
  medline-phst = {2004/03/12 [received] ; 2004/06/23 [revised] ;
                   2004/06/25 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15488418},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Research Support, Non-U.S. Gov't},
  medline-pubm = {Print},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2004 Oct;23(2):680-97.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15488418},
  year = 2004
}
@ARTICLE{RDM+07,
  author = {Rodionov, R. and De Martino, F. and Laufs, H. and
                   Carmichael, D. W. and Formisano, E. and Walker, M. and
                   Duncan, J. S. and Lemieux, L.},
  title = {Independent component analysis of interictal f{MRI} in
                   focal epilepsy: {C}omparison with general linear
                   model-based {EEG}-correlated f{MRI}.},
  journal = {Neuroimage},
  abstract = {The general linear model (GLM) has been used to
                   analyze simultaneous EEG-fMRI to reveal BOLD changes
                   linked to interictal epileptic discharges (IED)
                   identified on scalp EEG. This approach is ineffective
                   when IED are not evident in the EEG. Data-driven fMRI
                   analysis techniques that do not require an EEG derived
                   model may offer a solution in these circumstances. We
                   compared the findings of independent components
                   analysis (ICA) and EEG-based GLM analyses of fMRI data
                   from eight patients with focal epilepsy. Spatial ICA
                   was used to extract independent components (IC) which
                   were automatically classified as either BOLD-related,
                   motion artefacts, EPI-susceptibility artefacts, large
                   blood vessels, noise at high spatial or temporal
                   frequency. The classifier reduced the number of
                   candidate IC by 78%, with an average of 16 BOLD-related
                   IC. Concordance between the ICA and GLM-derived results
                   was assessed based on spatio-temporal criteria. In each
                   patient, one of the IC satisfied the criteria to
                   correspond to IED-based GLM result. The remaining IC
                   were consistent with BOLD patterns of spontaneous brain
                   activity and may include epileptic activity that was
                   not evident on the scalp EEG. In conclusion, ICA of
                   fMRI is capable of revealing areas of epileptic
                   activity in patients with focal epilepsy and may be
                   useful for the analysis of EEG-fMRI data in which
                   abnormalities are not apparent on scalp EEG.},
  authoraddress = {Department of Clinical and Experimental Epilepsy,
                   Institute of Neurology, University College of London
                   Queen Square, London WC1N 3BG, UK; MRI Unit, National
                   Society for Epilepsy, Chesham Lane, Chalfont St. Peter,
                   Buckinghamshire SL9 0RJ, UK.},
  language = {ENG},
  medline-aid = {S1053-8119(07)00703-3 [pii] ;
                   10.1016/j.neuroimage.2007.08.003 [doi]},
  medline-da = {20070924},
  medline-dep = {20070817},
  medline-edat = {2007/09/25 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2007/09/25 09:00},
  medline-own = {NLM},
  medline-phst = {2007/05/02 [received] ; 2007/06/27 [revised] ;
                   2007/08/06 [accepted]},
  medline-pmid = {17889566},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2007 Aug 17;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17889566},
  year = 2007
}
@ARTICLE{RDVdM+06,
  author = {Robinson, P. A. and Drysdale, P. M. and Van der Merwe,
                   H. and Kyriakou, E. and Rigozzi, M. K. and Germanoska,
                   B. and Rennie, C. J.},
  title = {B{OLD} responses to stimuli: dependence on frequency,
                   stimulus form, amplitude, and repetition rate.},
  journal = {Neuroimage},
  volume = {31},
  number = {2},
  pages = {585-99},
  abstract = {A quantitative theory is developed for the
                   relationship between stimulus and the resulting blood
                   oxygen level-dependent (BOLD) functional MRI signal.
                   The relationship of stimuli to neuronal activity during
                   evoked responses is inferred from recent
                   physiology-based quantitative modeling of evoked
                   response potentials (ERPs). A hemodynamic model is then
                   used to calculate the BOLD response to neuronal
                   activity having the form of an impulse, a sinusoid, or
                   an ERP-like damped sinusoid. Using the resulting
                   equations, the BOLD response is analyzed for different
                   forms, frequencies, and amplitudes of stimuli, in
                   contrast with previous research, which has mostly
                   concentrated on sustained stimuli. The BOLD frequency
                   response is found to be closely linear in the parameter
                   ranges of interest, with the form of a low-pass filter
                   with a weak resonance at approximately 0.07 Hz. An
                   improved BOLD impulse response is systematically
                   obtained which includes initial dip and post-stimulus
                   undershoot for some parameter ranges. It is found that
                   the BOLD response depends strongly on the precise
                   temporal course of the evoked neuronal activity, not
                   just its peak value or typical amplitude. Indeed, for
                   short stimuli, the linear BOLD response is closely
                   proportional to the time-integrated activity change
                   evoked by the stimulus, regardless of amplitude. It is
                   concluded that there can be widely differing
                   proportionalities between BOLD and peak activity, that
                   this is the likely reason for the low level of
                   correspondence seen experimentally between ERP sources
                   and BOLD measurements and that non-BOLD measurements,
                   such as ERPs, can be used to correct for this effect to
                   obtain improved activity estimates. Finally, stimulus
                   sequences that optimize the signal-to-noise ratio in
                   event-related BOLD fMRI (efMRI) experiments are derived
                   using the hemodynamic transfer function.},
  authoraddress = {School of Physics, University of Sydney, NSW, 2006,
                   Australia.},
  keywords = {Brain/*anatomy & histology/*physiology/radionuclide
                   imaging ; *Cerebrovascular Circulation ; Evoked
                   Potentials ; Hemodynamic Processes ; Humans ; Models,
                   Neurological ; Oxygen/*blood ; Positron-Emission
                   Tomography},
  language = {eng},
  medline-aid = {S1053-8119(05)02574-7 [pii] ;
                   10.1016/j.neuroimage.2005.12.026 [doi]},
  medline-da = {20060601},
  medline-dcom = {20060814},
  medline-dep = {20060208},
  medline-edat = {2006/02/10 09:00},
  medline-fau = {Robinson, P A ; Drysdale, P M ; Van der Merwe, H ;
                   Kyriakou, E ; Rigozzi, M K ; Germanoska, B ; Rennie, C
                   J},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage},
  medline-lr = {20061115},
  medline-mhda = {2006/08/15 09:00},
  medline-own = {NLM},
  medline-phst = {2005/03/10 [received] ; 2005/12/01 [revised] ;
                   2005/12/20 [accepted] ; 2006/02/08 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16466935},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Research Support, Non-U.S. Gov't},
  medline-pubm = {Print-Electronic},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 Jun;31(2):585-99. Epub 2006 Feb 8.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16466935},
  year = 2006
}
@ARTICLE{RJW+06,
  author = {Riera, J. J. and Jimenez, J. C. and Wan, X. and
                   Kawashima, R. and Ozaki, T.},
  title = {Nonlinear local electrovascular coupling. {II}: {F}rom
                   data to neuronal masses.},
  journal = {Hum Brain Mapp},
  abstract = {In the companion article a local electrovascular
                   coupling (LEVC) model was proposed to explain the
                   continuous dynamics of electrical and vascular states
                   within a cortical unit. These states produce certain
                   mesoscopic reflections whose discrete time series can
                   be reconstructed from electroencephalography (EEG) and
                   functional magnetic resonance imaging (fMRI). In this
                   article we develop a recursive optimization algorithm
                   based on the local linearization (LL) filter and an
                   innovation method to make statistical inferences about
                   the LEVC model from both EEG and fMRI data, i.e., to
                   estimate the unobserved states and the unknown
                   parameters of the model. For a better understanding,
                   the LL filter is described from a Bayesian point of
                   view, providing the particulars for the case of hybrid
                   data (e.g., EEG and fMRI), which could be sampled at
                   different rates. The dynamics of the exogenous synaptic
                   inputs going into the cortical unit are also estimated
                   by introducing a set of Gaussian radial basis
                   functions. In order to study the dynamics of the
                   electrical and vascular states in the striate cortex of
                   humans as well as their local interrelationships, we
                   applied this algorithm to EEG and fMRI recordings
                   obtained concurrently from two subjects while passively
                   observing a radial checkerboard with a white/black
                   pattern reversal. The EEG and fMRI data from the first
                   subject was used to estimate the electrical/vascular
                   states and parameters of the LEVC model in V1 for a 4.0
                   Hz reversion frequency. We used the EEG data from the
                   second subject to investigate the changes in the
                   dynamics of the electrical states when the frequency of
                   reversion is varied from 0.5-4.0 Hz. Then we made use
                   of the estimated electrical states to predict the
                   effects on the vasculature that such variations
                   produce. Hum Brain Mapp, 2006. (c) 2006 Wiley-Liss,
                   Inc.},
  authoraddress = {NICHe, Tohoku University, Sendai, Japan.},
  language = {ENG},
  medline-aid = {10.1002/hbm.20278 [doi]},
  medline-da = {20060825},
  medline-dep = {20060824},
  medline-edat = {2006/08/26 09:00},
  medline-is = {1065-9471 (Print)},
  medline-jid = {9419065},
  medline-mhda = {2006/08/26 09:00},
  medline-own = {NLM},
  medline-pmid = {16933303},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Hum Brain Mapp. 2006 Aug 24;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16933303},
  year = 2006
}
@ARTICLE{RKL+05,
  author = {Rostrup, E. and Knudsen, G.M. and Law, I. and Holm, S.
                   and Larsson, H.B. and Paulson, O.B.},
  title = {The relationship between cerebral blood flow and
                   volume in humans.},
  journal = {Neuroimage},
  volume = {24},
  number = {1},
  pages = {1-11},
  abstract = {The purpose of this study was to establish the
                   relationship between regional CBF and CBV at normal,
                   resting cerebral metabolic rates. Eleven healthy
                   volunteers were investigated with PET during baseline
                   conditions, and during hyper- and hypocapnia. Values
                   for rCBF and rCBV were obtained using (15)O-labelled
                   water and carbon monoxide, respectively. The mean value
                   of rCBF using PET was 62 +/- 18 ml.100 g(-1) min(-1)
                   during baseline conditions, with an average increase of
                   46\% during hypercapnia, and a decrease of 29\% during
                   hypocapnia; baseline rCBV was 7.7 ml/100 g, with 27\%
                   increase during hypercapnia and no significant decrease
                   during hypocapnia. A regionally uniform exponential
                   relationship was confirmed between P(a)CO(2) and rCBF
                   as well as rCBV. It is shown that the theoretical
                   implication of this is that the rCBV vs. rCBF
                   relationship should be modelled by a power function;
                   however, due to pronounced intersubject variability,
                   the goodness of fit for linear and nonlinear models
                   were not significantly different. The results of the
                   study are applied to a numerical estimation of regional
                   brain deoxy-haemoglobin content. Independently of the
                   choice of model for the rCBV vs. rCBF relationship, a
                   nonlinear deoxy-haemoglobin vs. rCBF relationship was
                   predicted, and the implications for the BOLD response
                   are discussed.},
  authoraddress = {Danish Research Center for Magnetic Resonance,
                   DK-2650, Copenhagen University Hospital, Hvidovre,
                   Denmark.},
  language = {eng},
  medline-aid = {S1053-8119(04)00566-X [pii] ;
                   10.1016/j.neuroimage.2004.09.043 [doi]},
  medline-da = {20041213},
  medline-edat = {2004/12/14 09:00},
  medline-fau = {Rostrup, Egill ; Knudsen, Gitte M ; Law, Ian ; Holm,
                   Soren ; Larsson, Henrik B W ; Paulson, Olaf B},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/12/14 09:00},
  medline-own = {NLM},
  medline-phst = {2003/09/25 [received] ; 2004/06/25 [revised] ;
                   2004/09/24 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15588591},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuroimage 2005 Jan 1;24(1):1-11.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15588591},
  year = 2005
}
@ARTICLE{RKM+98,
  author = {Rajapakse, J. C. and Kruggel, F. and Maisog, J. M. and
                   von Cramon, D. Y.},
  title = {Modeling hemodynamic response for analysis of
                   functional {MRI} time-series.},
  journal = {Hum Brain Mapp},
  volume = {6},
  number = {4},
  pages = {283-300},
  abstract = {The standard Gaussian function is proposed for the
                   hemodynamic modulation function (HDMF) of functional
                   magnetic resonance imaging (fMRI) time-series. Unlike
                   previously proposed parametric models, the Gaussian
                   model accounts independently for the delay and
                   dispersion of the hemodynamic responses and provides a
                   more flexible and mathematically convenient model. A
                   suboptimal noniterative scheme to estimate the
                   hemodynamic parameters is presented. The ability of the
                   Gaussian function to represent the HDMF of brain
                   activation is compared with Poisson and Gamma models.
                   The proposed model seems valid because the lag and
                   dispersion values of hemodynamic responses rendered by
                   the Gaussian model are in the ranges of their
                   previously reported values in recent optical and fMR
                   imaging studies. An extension of multiple regression
                   analysis to incorporate the HDMF is presented. The
                   detected activity patterns exhibit improvements with
                   hemodynamic correction. The proposed model and
                   efficient parameter estimation scheme facilitated the
                   investigation of variability of hemodynamic parameters
                   of human brain activation. The hemodynamic parameters
                   estimated over different brain regions and across
                   different stimuli showed significant differences.
                   Measurement of hemodynamic parameters over the brain
                   during sensory or cognitive stimulation may reveal
                   vital information on physiological events accompanying
                   neuronal activation and functional variability of the
                   human brain, and should lead to the investigation of
                   more accurate and complex models.},
  authoraddress = {Max-Planck-Institute of Cognitive Neuroscience,
                   Leipzig, Germany. raja@cns.mpg.de},
  keywords = {Brain/blood supply/*physiology ; *Brain Mapping ;
                   Cerebrovascular Circulation/*physiology ;
                   Discrimination (Psychology) ; Human ; Language ;
                   Magnetic Resonance Imaging/methods ; Mental
                   Processes/*physiology ; *Models, Cardiovascular ;
                   *Models, Neurological ; Models, Statistical ; Normal
                   Distribution ; Photic Stimulation ; Poisson
                   Distribution ; Reaction Time ; Speech
                   Perception/physiology ; Temporal Lobe/physiology ;
                   Visual Perception/physiology},
  language = {eng},
  medline-aid = {10.1002/(SICI)1097-0193(1998)6:4<283::AID-HBM7>3.0.CO;2-\#
                   [pii]},
  medline-da = {19981026},
  medline-dcom = {19981026},
  medline-edat = {1998/08/15 02:13},
  medline-fau = {Rajapakse, J C ; Kruggel, F ; Maisog, J M ; von
                   Cramon, D Y},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-lr = {20001218},
  medline-mhda = {2000/08/12 11:00},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9704266},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 1998;6(4):283-300.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9704266},
  year = 1998
}
@ARTICLE{RMS+01,
  author = {Raichle, M. E. and MacLeod, A. M. and Snyder, A. Z.
                   and Powers, W. J. and Gusnard, D. A. and Shulman, G. L.},
  title = {A default mode of brain function.},
  journal = {Proc Natl Acad Sci U S A},
  volume = {98},
  number = {2},
  pages = {676-82},
  abstract = {A baseline or control state is fundamental to the
                   understanding of most complex systems. Defining a
                   baseline state in the human brain, arguably our most
                   complex system, poses a particular challenge. Many
                   suspect that left unconstrained, its activity will vary
                   unpredictably. Despite this prediction we identify a
                   baseline state of the normal adult human brain in terms
                   of the brain oxygen extraction fraction or OEF. The OEF
                   is defined as the ratio of oxygen used by the brain to
                   oxygen delivered by flowing blood and is remarkably
                   uniform in the awake but resting state (e.g., lying
                   quietly with eyes closed). Local deviations in the OEF
                   represent the physiological basis of signals of changes
                   in neuronal activity obtained with functional MRI
                   during a wide variety of human behaviors. We used
                   quantitative metabolic and circulatory measurements
                   from positron-emission tomography to obtain the OEF
                   regionally throughout the brain. Areas of activation
                   were conspicuous by their absence. All significant
                   deviations from the mean hemisphere OEF were increases,
                   signifying deactivations, and resided almost
                   exclusively in the visual system. Defining the baseline
                   state of an area in this manner attaches meaning to a
                   group of areas that consistently exhibit decreases from
                   this baseline, during a wide variety of goal-directed
                   behaviors monitored with positron-emission tomography
                   and functional MRI. These decreases suggest the
                   existence of an organized, baseline default mode of
                   brain function that is suspended during specific
                   goal-directed behaviors.},
  authoraddress = {Mallinckrodt Institute of Radiology and Departments of
                   Neurology and Psychiatry, Washington University School
                   of Medicine, St. Louis, MO 63110, USA.
                   marc@npg.wustl.edu},
  keywords = {Adult ; Aged ; Aged, 80 and over ;
                   Attention/physiology ; Brain/*physiology/radionuclide
                   imaging ; Brain Chemistry ; *Brain Mapping ;
                   Cerebrovascular Circulation ; Female ; Humans ;
                   *Magnetic Resonance Imaging ; Male ; Middle Aged ;
                   *Models, Neurological ; Oxygen/blood ; Oxygen
                   Consumption ; Oxyhemoglobins/analysis ; Parietal
                   Lobe/physiology ; Research Support, Non-U.S. Gov't ;
                   Research Support, U.S. Gov't, P.H.S. ; Rest/*physiology
                   ; Supine Position ; Tomography, Emission-Computed ;
                   Wakefulness/physiology},
  language = {eng},
  medline-aid = {10.1073/pnas.98.2.676 [doi] ; 98/2/676 [pii]},
  medline-da = {20010314},
  medline-dcom = {20010426},
  medline-edat = {2001/02/24 11:00},
  medline-fau = {Raichle, M E ; MacLeod, A M ; Snyder, A Z ; Powers, W
                   J ; Gusnard, D A ; Shulman, G L},
  medline-gr = {DA07261/DA/NIDA ; NS06833/NS/NINDS ; NS10196/NS/NINDS},
  medline-is = {0027-8424 (Print)},
  medline-jid = {7505876},
  medline-jt = {Proceedings of the National Academy of Sciences of the
                   United States of America.},
  medline-lr = {20041117},
  medline-mhda = {2001/05/01 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11209064},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {0 (Oxyhemoglobins) ; 7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Proc Natl Acad Sci U S A. 2001 Jan 16;98(2):676-82.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11209064},
  year = 2001
}
@ARTICLE{RV06,
  author = {Ritter, P. and Villringer, A.},
  title = {Simultaneous {EEG}-f{MRI}.},
  journal = {Neurosci Biobehav Rev},
  volume = {30},
  number = {6},
  pages = {823-38},
  abstract = {Acquisition of electroencephalogram (EEG) during
                   functional magnetic resonance imaging (fMRI) provides
                   an additional monitoring tool for the analysis of brain
                   state fluctuations. The exploration of brain responses
                   following inputs or in the context of state changes is
                   crucial for a better understanding of the basic
                   principles governing large-scale neuronal dynamics.
                   State-of-the-art techniques allow EEG activity-from DC
                   (direct current) up to high frequencies in the gamma
                   range-to be acquired simultaneously with fMRI data. In
                   the interleaved mode, spiking activities can also be
                   assessed during concurrent fMRI. The utilization of
                   fMRI evidence to better constrain solutions of the
                   inverse problem of source localization of EEG activity
                   is an exciting possibility. Nonetheless, this approach
                   should be applied cautiously since the degree of
                   overlap between underlying neuronal activity sources is
                   variable and, for the most part, unknown. The ultimate
                   goal is to make joint inferences about the activity,
                   dynamics, and functions by exploiting complementary
                   information from multimodal data sets.},
  authoraddress = {Berlin Neuroimaging Center and Charite,
                   Universitatsmedizin, Berlin. petra.ritter@charite.de},
  keywords = {Animals ; Brain/*blood supply/*physiology ; *Brain
                   Mapping ; Electroencephalography/*methods ; Humans ;
                   Image Processing, Computer-Assisted/methods ; *Magnetic
                   Resonance Imaging ; Oxygen/blood},
  language = {eng},
  medline-aid = {S0149-7634(06)00053-4 [pii] ;
                   10.1016/j.neubiorev.2006.06.008 [doi]},
  medline-da = {20060904},
  medline-dcom = {20061114},
  medline-dep = {20060815},
  medline-edat = {2006/08/17 09:00},
  medline-fau = {Ritter, Petra ; Villringer, Arno},
  medline-is = {0149-7634 (Print)},
  medline-jid = {7806090},
  medline-jt = {Neuroscience and biobehavioral reviews},
  medline-lr = {20061115},
  medline-mhda = {2006/11/15 09:00},
  medline-own = {NLM},
  medline-phst = {2006/08/15 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16911826},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Research Support, Non-U.S. Gov't ;
                   Review},
  medline-pubm = {Print-Electronic},
  medline-rf = {158},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neurosci Biobehav Rev. 2006;30(6):823-38. Epub 2006
                   Aug 15.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16911826},
  year = 2006
}
@INPROCEEDINGS{RV99,
  author = {Robinson, S. E. and Vrba, J.},
  title = {Functional neuroimaging by syntheticaperture
                  magnetometry ({SAM})},
  booktitle = {Recent Advances in Biomagnetism},
  pages = {302-305},
  year = 1999,
  editor = {Yoshimoto, T. and Kotani, M. and Kuriki, S. and
                  Karibe, H. and Nakasato, N.},
  address = {Sendai, Japan},
  publisher = {Tohoku Univ. Press.}
}
@ARTICLE{RWJ+06,
  author = {Riera, J. J. and Wan, X. and Jimenez, J. C. and
                   Kawashima, R.},
  title = {Nonlinear local electrovascular coupling. {I}: {A}
                   theoretical model.},
  journal = {Hum Brain Mapp},
  volume = {27},
  number = {11},
  pages = {896-914},
  abstract = {Here we present a detailed biophysical model of how
                   brain electrical and vascular dynamics are generated
                   within a basic cortical unit. The model was obtained
                   from coupling a canonical neuronal mass and an
                   expandable vasculature. In this proposal, we address
                   several aspects related to electroencephalographic and
                   functional magnetic resonance imaging data fusion: (1)
                   the impact of the cerebral architecture (at different
                   physical levels) on the observations; (2) the
                   physiology involved in electrovascular coupling; and
                   (3) energetic considerations to gain a better
                   understanding of how the glucose budget is used during
                   neuronal activity. The model has three components. The
                   first is the canonical neural mass model of three
                   subpopulations of neurons that respond to incoming
                   excitatory synaptic inputs. The generation of the
                   membrane potentials in the somas of these neurons and
                   the electric currents flowing in the neuropil are
                   modeled by this component. The second and third
                   components model the electrovascular coupling and the
                   dynamics of vascular states in an extended balloon
                   approach, respectively. In the first part we describe,
                   in some detail, the biophysical model and establish its
                   face validity using simulations of visually evoked
                   responses under different flickering frequencies and
                   luminous contrasts. In a second part, a recursive
                   optimization algorithm is developed and used to make
                   statistical inferences about this forward/generative
                   model from actual data. Hum. Brain Mapping 2006. (c)
                   2006 Wiley-Liss, Inc.},
  authoraddress = {NICHe, Tohoku University, Sendai, Japan.},
  language = {ENG},
  medline-aid = {10.1002/hbm.20230 [doi]},
  medline-da = {20061020},
  medline-dep = {20060525},
  medline-edat = {2006/05/27 09:00},
  medline-is = {1065-9471 (Print)},
  medline-jid = {9419065},
  medline-mhda = {2006/05/27 09:00},
  medline-own = {NLM},
  medline-pmid = {16729288},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Hum Brain Mapp. 2006 May 25;27(11):896-914.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16729288},
  year = 2006
}
@ARTICLE{SBG+05,
  author = {Sammer, G. and Blecker, C. and Gebhardt, H. and
                   Kirsch, P. and Stark, R. and Vaitl, D.},
  title = {Acquisition of typical {EEG} waveforms during f{MRI}:
                   {SSVEP}, {LRP}, and frontal theta.},
  journal = {Neuroimage},
  volume = {24},
  number = {4},
  pages = {1012-1024},
  abstract = {Recent work has demonstrated the feasibility of
                   simultaneous electroencephalography (EEG) and
                   functional magnetic resonance imaging (fMRI). Virtually
                   no systematic comparisons between EEG recorded inside
                   and outside the MR scanner have been conducted, and it
                   is unknown if different kinds of frequency mix,
                   topography, and domain-specific processing are
                   uniformly recordable within the scanner environment.
                   The aim of the study was to investigate several typical
                   EEG waveforms in the same subjects inside the magnet
                   during fMRI and outside the MR examination room. We
                   examined whether uniform artifact subtraction allows
                   the extraction of these different EEG waveforms inside
                   the scanner during EPI scanning to the same extent as
                   outside the scanner. Three well-established experiments
                   were conducted, eliciting steady state visual evoked
                   potentials (SSVEP), lateralized readiness potentials
                   (LRP), and frontal theta enhancement induced by mental
                   addition. All waveforms could be extracted from the EEG
                   recorded during fMRI. Substantially no differences in
                   these waveforms of interest were found between
                   gradient-switching and intermediate epochs during fMRI
                   (only the SSVEP-experiment was designed for a
                   comparison of gradient-with intermediate epochs), or
                   between waveforms recorded inside the scanner during
                   EPI scanning and outside the MR examination room (all
                   experiments). However, non-specific amplitude
                   differences were found between inside and outside
                   recorded EEG at lateral electrodes, which were not in
                   any interaction with the effects of interest. The
                   source of these differences requires further
                   exploration. The high concordance of activation
                   patterns with published results demonstrates that
                   EPI-images could be acquired during EEG recording
                   without significant distortion.},
  authoraddress = {Bender Institute of Neuroimaging, University of
                   Giessen, Otto-Behaghel-Str. 10F, D-35394 Giessen,
                   Germany.},
  language = {eng},
  medline-aid = {S1053-8119(04)00633-0 [pii] ;
                   10.1016/j.neuroimage.2004.10.026 [doi]},
  medline-da = {20050126},
  medline-dep = {20041213},
  medline-edat = {2005/01/27 09:00},
  medline-fau = {Sammer, Gebhard ; Blecker, Carlo ; Gebhardt, Helge ;
                   Kirsch, Peter ; Stark, Rudolf ; Vaitl, Dieter},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2005/01/27 09:00},
  medline-own = {NLM},
  medline-phst = {2004/04/10 [received] ; 2004/09/27 [revised] ;
                   2004/10/26 [accepted] ; 2004/12/13 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {15670678},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage 2005 Feb 15;24(4):1012-24. Epub 2004 Dec
                   13.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15670678},
  year = 2005
}
@ARTICLE{SBH+02,
  author = {Singh, K. D. and Barnes, G. R. and Hillebrand, A. and
                   Forde, E. M. and Williams, A. L.},
  title = {Task-related changes in cortical synchronization are
                   spatially coincident with the hemodynamic response},
  journal = {NeuroImage},
  volume = {16},
  number = {1},
  pages = {103-114},
  abstract = {Using group functional Magnetic Resonance Imaging
                   (fMRI) and group Magnetoencephalography (MEG) we
                   studied two cognitive paradigms: A language task
                   involving covert letter fluency and a visual task
                   involving biological motion direction discrimination.
                   The MEG data were analyzed using an adaptive
                   beam-former technique known as Synthetic Aperture
                   Magnetometry (SAM), which provides continuous 3-D
                   images of cortical power changes. These images were
                   spatially normalized and averaged across subjects to
                   provide a group SAM image in the same template space as
                   the group fMRI data. The results show that
                   frequency-specific, task-related changes in cortical
                   synchronization, detected using MEG, match those areas
                   of the brain showing an evoked cortical hemodynamic
                   response with fMRI. The majority of these changes were
                   event-related desynchronizations (ERDs) in the 5-10 Hz
                   and 15-25 Hz frequency ranges. Our study demonstrates
                   how SAM, spatial normalization, and intersubject
                   averaging enable group MEG studies to be performed. SAM
                   analysis also allows the MEG experiment to have exactly
                   the same task design as the corresponding fMRI
                   experiment. This new analysis framework represents an
                   important advance in the use of MEG as a cognitive
                   neuroimaging technique and also allows mutual
                   cross-validation with fMRI.},
  authoraddress = {The Wellcome Trust Laboratory for MEG Studies,
                   Neurosciences Research Institute, Aston University,
                   Birmingham, United Kingdom.},
  keywords = {Adult ; Cerebral Cortex/anatomy &
                   histology/physiology ; Cerebrovascular
                   Circulation/*physiology ; *Cortical Synchronization ;
                   Discrimination (Psychology)/physiology ; Female ; Human
                   ; Magnetic Resonance Imaging ; Magnetoencephalography ;
                   Male ; Motion Perception/physiology ; Nerve Net/anatomy
                   & histology/physiology ; Psychomotor
                   Performance/physiology ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1006/nimg.2001.1050 [doi] ; S105381190191050X [pii]},
  medline-ci = {2002 Elsevier Science (USA).},
  medline-da = {20020423},
  medline-dcom = {20040329},
  medline-edat = {2002/04/24 10:00},
  medline-fau = {Singh, Krish D ; Barnes, Gareth R ; Hillebrand, Arjan
                   ; Forde, Emer M E ; Williams, Adrian L},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/03/30 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11969322},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2002 May;16(1):103-14.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11969322},
  year = 2002
}
@ARTICLE{SBL+00,
  author = {Schomer, D. L. and Bonmassar, G. and Lazeyras, F. and
                   Seeck, M. and Blum, A. and Anami, K. and Schwartz, D.
                   and Belliveau, J. W. and Ives, J.},
  title = {E{EG}-{L}inked functional magnetic resonance imaging
                   in epilepsy and cognitive neurophysiology},
  journal = {J Clin Neurophysiol},
  volume = {17},
  number = {1},
  pages = {43-58},
  abstract = {The ability to trigger functional magnetic resonance
                   imaging (fMRI) acquisitions related to the occurrence
                   of EEG-based physiologic transients has changed the
                   field of fMRI into a more dynamically based technique.
                   By knowing the temporal relationship between focal
                   increases in neuronal firing rates and the provoked
                   focal increase in blood flow, investigators are able to
                   maximize the fMR-linked images that show where the
                   activity originates. Our mastery of recording EEG
                   inside the bore of a MR scanner has also allowed us to
                   develop cognitive paradigms that record not only the
                   fMR BOLD images, but also the evoked potentials (EPs).
                   The EPs can subsequently be subjected to localization
                   paradigms that can be compared to the localization seen
                   on the BOLD images. These two techniques will most
                   probably be complimentary. BOLD responses are dependent
                   on a focal increase in metabolic demand while the EPs
                   may or may not be related to energy demand increases.
                   Additionally, recording EPs require that the source or
                   sources of that potential come from an area that is
                   able to generate far-field potentials. These potentials
                   are related to the laminar organization of the neuronal
                   population generating that potential. As best we know
                   the BOLD response does not depend on any inherent
                   laminar neuronal organization. Therefore, by merging
                   these two recording methods, it is likely that we will
                   gain a more detailed understanding of not only the
                   areas involved in certain physiologic events, e.g.
                   focal epilepsy or cognitive processing, but also on the
                   sequencing of the activation of the various
                   participating regions.},
  authoraddress = {Neurology Department, Beth Israel Deaconess Medical
                   Center, Harvard University, Boston, MA 02215, USA.},
  keywords = {Artifacts ; Brain
                   Diseases/complications/*diagnosis/physiopathology ;
                   Electrodes ;
                   Electroencephalography/instrumentation/*methods ;
                   Epilepsy/*etiology/physiopathology ; Equipment Design ;
                   Evoked Potentials/physiology ; Human ; Image
                   Enhancement/methods ; Magnetic Resonance
                   Imaging/*methods ; Signal Processing, Computer-Assisted},
  language = {eng},
  medline-da = {20000328},
  medline-dcom = {20000328},
  medline-edat = {2000/03/10 09:00},
  medline-fau = {Schomer, D L ; Bonmassar, G ; Lazeyras, F ; Seeck, M ;
                   Blum, A ; Anami, K ; Schwartz, D ; Belliveau, J W ;
                   Ives, J},
  medline-is = {0736-0258},
  medline-jid = {8506708},
  medline-lr = {20001218},
  medline-mhda = {2000/04/01 09:00},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10709810},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {62},
  medline-sb = {IM},
  medline-so = {J Clin Neurophysiol 2000 Jan;17(1):43-58.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10709810},
  year = 2000
}
@ARTICLE{SCG+04,
  author = {Schulz, M. and Chau, W. and Graham, S. J. and
                   McIntosh, A. R. and Ross, B. and Ishii, R. and Pantev,
                   C.},
  title = {An integrative {MEG}-f{MRI} study of the primary
                   somatosensory cortex using cross-modal correspondence
                   analysis},
  journal = {NeuroImage},
  volume = {22},
  number = {1},
  pages = {120-133},
  abstract = {We develop a novel approach of cross-modal
                   correspondence analysis (CMCA) to address whether brain
                   activities observed in magnetoencephalography (MEG) and
                   functional magnetic resonance imaging (fMRI) represent
                   a common neuronal subpopulation, and if so, which
                   frequency band obtained by MEG best fits the common
                   brain areas. Fourteen adults were investigated by
                   whole-head MEG using a single equivalent current dipole
                   (ECD) and synthetic aperture magnetometry (SAM)
                   approaches and by fMRI at 1.5 T using linear
                   time-invariant modeling to generate statistical maps.
                   The same somatosensory stimulus sequences consisting of
                   tactile impulses to the right sided: digit 1, digit 4
                   and lower lip were used in both neuroimaging
                   modalities. To evaluate the reproducibility of MEG and
                   fMRI results, one subject was measured repeatedly.
                   Despite different MEG dipole locations and locations of
                   maximum activation in SAM and fMRI, CMCA revealed a
                   common subpopulation of the primary somatosensory
                   cortex, which displays a clear homuncular organization.
                   MEG activity in the frequency range between 30 and 60
                   Hz, followed by the ranges of 20-30 and 60-100 Hz,
                   explained best the defined subrepresentation given by
                   both MEG and fMRI. These findings have important
                   implications for improving and understanding of the
                   biophysics underlying both neuroimaging techniques, and
                   for determining the best strategy to combine MEG and
                   fMRI data to study the spatiotemporal nature of brain
                   activity.},
  authoraddress = {Institute for Biomagnetism and Biosignalanalysis,
                   Munster University Hospital, University of Munster,
                   Kardinal-von-Galen-Ring 10, 48129 Munster, Germany.},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.10.049 [doi] ;
                   S1053811903006815 [pii]},
  medline-da = {20040427},
  medline-edat = {2004/04/28 05:00},
  medline-fau = {Schulz, Matthias ; Chau, Wilkin ; Graham, Simon J ;
                   McIntosh, Anthony R ; Ross, Bernhard ; Ishii, Ryouhei ;
                   Pantev, Christo},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/04/28 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Jun/12 [received] ; 2003/Oct/16 [revised] ;
                   2003/Oct/22 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15110002},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 May;22(1):120-33.},
  medline-stat = {in-process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15110002},
  year = 2004
}
@MISC{SCI:SCIRun,
  crossref = {SCI_SCIRun}
}
@INPROCEEDINGS{SCI:Wol2005a,
  author = {C. H. Wolters and A. Anwander and X. Tricoche and
                  S. Lew and C. R. Johnson},
  title = {Influence of Local and Remote White Matter
                  Conductivity Anisotropy for a Thalamic Source on
                  EEG/MEG Field and Return Current Computation},
  booktitle = {Proceedings of The Joint Meeting of The 5th International Conference on Bioelectromagnetism and The 5th International Symposium on Noninvasive Functional Source Imaging within the Human Brain and Heart},
  pages = {(accepted)},
  year = {2005},
  keywords = {forward problems inverse problems forward simulation
                  inverse solutions, finite elements, forward
                  simulation, anisotropy, thalamus},
  url = {http://www.sci.utah.edu/publications/wolters05/NFSI-Paper05.pdf},
  urldate = {2005-05-09}
}
@MISC{SCI_BioPSE,
  key = {BioPSE},
  title = {Problem Solving Environment for modeling,
                  simulation, and visualization of bioelectric fields},
  note = {Scientific Computing and Imaging Institute (SCI)},
  year = 2002,
  url = {http://software.sci.utah.edu/biopse.html}
}
@MISC{SCI_SCIRun,
  key = {SCIRun},
  title = {{SCIRun}: a Scientific Computing Problem Solving
                  Environment},
  note = {Scientific Computing and Imaging Institute (SCI)},
  url = {http://software.sci.utah.edu/scirun.html},
  year = 2002
}
@ARTICLE{SCL+05,
  author = {Srivastava, G. and Crottaz-Herbette, S. and Lau, K.M.
                   and Glover, G.H. and Menon, V.},
  title = {I{CA}-based procedures for removing ballistocardiogram
                   artifacts from {EEG} data acquired in the {MRI}
                   scanner.},
  journal = {Neuroimage},
  volume = {24},
  number = {1},
  pages = {50-60},
  abstract = {Electroencephalogram (EEG) data acquired in the MRI
                   scanner contains significant artifacts, one of the most
                   prominent of which is ballistocardiogram (BCG)
                   artifact. BCG artifacts are generated by movement of
                   EEG electrodes inside the magnetic field due to
                   pulsatile changes in blood flow tied to the cardiac
                   cycle. Independent Component Analysis (ICA) is a
                   statistical algorithm that is useful for removing
                   artifacts that are linearly and independently mixed
                   with signals of interest. Here, we demonstrate and
                   validate the usefulness of ICA in removing BCG
                   artifacts from EEG data acquired in the MRI scanner. In
                   accordance with our hypothesis that BCG artifacts are
                   physiologically independent from EEG, it was found that
                   ICA consistently resulted in five to six independent
                   components representing the BCG artifact. Following
                   removal of these components, a significant reduction in
                   spectral power at frequencies associated with the BCG
                   artifact was observed. We also show that our ICA-based
                   procedures perform significantly better than
                   noise-cancellation methods that rely on estimation and
                   subtraction of averaged artifact waveforms from the
                   recorded EEG. Additionally, the proposed ICA-based
                   method has the advantage that it is useful in
                   situations where ECG reference signals are corrupted or
                   not available.},
  authoraddress = {Department of Psychiatry and Behavioral Sciences,
                   Stanford University, Stanford, CA 94305, USA;
                   Department of Electrical Engineering, Stanford
                   University, Stanford, CA 94305, USA.},
  language = {eng},
  medline-aid = {S1053-8119(04)00568-3 [pii] ;
                   10.1016/j.neuroimage.2004.09.041 [doi]},
  medline-da = {20041213},
  medline-edat = {2004/12/14 09:00},
  medline-fau = {Srivastava, G ; Crottaz-Herbette, S ; Lau, K M ;
                   Glover, G H ; Menon, V},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/12/14 09:00},
  medline-own = {NLM},
  medline-phst = {2003/12/23 [received] ; 2004/07/29 [revised] ;
                   2004/09/28 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15588596},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuroimage 2005 Jan 1;24(1):50-60.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15588596},
  year = 2005
}
@ARTICLE{SCT+02,
  author = {Strangman, G. and Culver, J. P. and Thompson, J. H.
                   and Boas, D. A.},
  title = {A quantitative comparison of simultaneous {BOLD}
                   f{MRI} and {NIRS} recordings during functional brain
                   activation},
  journal = {NeuroImage},
  volume = {17},
  number = {2},
  pages = {719-731},
  abstract = {Near-infrared spectroscopy (NIRS) has been used to
                   noninvasively monitor adult human brain function in a
                   wide variety of tasks. While rough spatial
                   correspondences with maps generated from functional
                   magnetic resonance imaging (fMRI) have been found in
                   such experiments, the amplitude correspondences between
                   the two recording modalities have not been fully
                   characterized. To do so, we simultaneously acquired
                   NIRS and blood-oxygenation level-dependent (BOLD) fMRI
                   data and compared Delta(1/BOLD) (approximately R(2)(*))
                   to changes in oxyhemoglobin, deoxyhemoglobin, and total
                   hemoglobin concentrations derived from the NIRS data
                   from subjects performing a simple motor task. We
                   expected the correlation with deoxyhemoglobin to be
                   strongest, due to the causal relation between changes
                   in deoxyhemoglobin concentrations and BOLD signal.
                   Instead we found highly variable correlations,
                   suggesting the need to account for individual subject
                   differences in our NIRS calculations. We argue that the
                   variability resulted from systematic errors associated
                   with each of the signals, including: (1) partial volume
                   errors due to focal concentration changes, (2)
                   wavelength dependence of this partial volume effect,
                   (3) tissue model errors, and (4) possible spatial
                   incongruence between oxy- and deoxyhemoglobin
                   concentration changes. After such effects were
                   accounted for, strong correlations were found between
                   fMRI changes and all optical measures, with
                   oxyhemoglobin providing the strongest correlation.
                   Importantly, this finding held even when including
                   scalp, skull, and inactive brain tissue in the average
                   BOLD signal. This may reflect, at least in part, the
                   superior contrast-to-noise ratio for oxyhemoglobin
                   relative to deoxyhemoglobin (from optical
                   measurements), rather than physiology related to BOLD
                   signal interpretation.},
  authoraddress = {Neural Systems Group, NMR Center, Massachusetts
                   General Hospital-Harvard Medical School, Harvard-MIT
                   Division of Health Sciences and Technology, Charlestown
                   02129, USA.},
  keywords = {Adult ; Brain/*physiology ; Brain
                   Chemistry/*physiology ; Comparative Study ; Data
                   Interpretation, Statistical ; Diffusion ;
                   Hemoglobins/metabolism ; Human ; Magnetic Resonance
                   Imaging/*methods ; Oxygen/*blood ; Spectroscopy,
                   Near-Infrared/*methods ; Support, Non-U.S. Gov't ;
                   Support, U.S. Gov't, Non-P.H.S. ; Support, U.S. Gov't,
                   P.H.S.},
  language = {eng},
  medline-aid = {S1053811902912279 [pii]},
  medline-da = {20021014},
  medline-dcom = {20021125},
  medline-edat = {2002/10/16 04:00},
  medline-fau = {Strangman, Gary ; Culver, Joseph P ; Thompson, John H
                   ; Boas, David A},
  medline-fir = {Sutton, J P},
  medline-gr = {F32-NS10567-01/NS/NINDS ; P41-RR14075/RR/NCRR ;
                   R29-NS38842/NS/NINDS},
  medline-ir = {Sutton JP},
  medline-irad = {Harvard U, Cambridge},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20030728},
  medline-mhda = {2002/11/26 04:00},
  medline-ot = {NASA Discipline Life Sciences Technologies ; Non-NASA
                   Center},
  medline-oto = {NASA},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12377147},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-rn = {0 (Hemoglobins) ; 7782-44-7 (Oxygen)},
  medline-sb = {IM ; S},
  medline-so = {NeuroImage 2002 Oct;17(2):719-31.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12377147},
  year = 2002
}
@ARTICLE{SDH+06,
  author = {Salek-Haddadi, A. and Diehl, B. and Hamandi, K. and
                   Merschhemke, M. and Liston, A. and Friston, K. and
                   Duncan, J. S. and Fish, D. R. and Lemieux, L.},
  title = {Hemodynamic correlates of epileptiform discharges:
                   {A}n {EEG}-f{MRI} study of 63 patients with focal
                   epilepsy.},
  journal = {Brain Res},
  abstract = {Using continuous EEG-correlated fMRI, we investigated
                   the Blood Oxygen Level Dependent (BOLD) signal
                   correlates of interictal epileptic discharges (IEDs) in
                   63 consecutively recruited patients with focal
                   epilepsy. Semi-automated spike detection and advanced
                   modeling strategies are introduced to account for
                   different EEG event types, and to minimize false
                   activations from uncontrolled motion. We show that: (1)
                   significant hemodynamic correlates were detectable in
                   over 68% of patients in whom discharges were captured
                   and were highly, but not entirely, concordant with
                   site(s) of presumed seizure generation where known; (2)
                   deactivations were less concordant and may
                   non-specifically reflect the consequential or
                   downstream effects of IEDs on brain activity; (3) a
                   striking pattern of retrosplenial deactivation was
                   observed in 7 cases mainly with focal discharges; (4)
                   the basic hemodynamic response to IEDs is
                   physiological; (5) incorporating information about
                   different types of IEDs, their durations and saturation
                   effects resulted in more powerful models for the
                   detection of fMRI correlates; (6) focal activations
                   were more likely when there was good electroclinical
                   localization, frequent stereotyped spikes, less head
                   motion and less background EEG abnormality, but were
                   also seen in patients in whom the electroclinical focus
                   localization was uncertain. These findings provide
                   important new information on the optimal use and
                   interpretation of EEG-fMRI in focal epilepsy and
                   suggest a possible role for EEG-fMRI in providing new
                   targets for invasive EEG monitoring.},
  authoraddress = {Department of Clinical and Experimental Epilepsy,
                   Institute of Neurology, Queen Square, London, UK; MRI
                   Unit, National Society for Epilepsy, Chalfont St Peter,
                   Buckinghamshire, UK.},
  language = {ENG},
  medline-aid = {S0006-8993(06)00524-5 [pii] ;
                   10.1016/j.brainres.2006.02.098 [doi]},
  medline-da = {20060508},
  medline-dep = {20060504},
  medline-edat = {2006/05/09 09:00},
  medline-is = {0006-8993 (Print)},
  medline-jid = {0045503},
  medline-mhda = {2006/05/09 09:00},
  medline-own = {NLM},
  medline-phst = {2005/11/30 [received] ; 2006/02/21 [revised] ;
                   2006/02/22 [accepted]},
  medline-pmid = {16678803},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Brain Res. 2006 May 4;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16678803},
  year = 2006
}
@ARTICLE{SFL+03,
  author = {Salek-Haddadi, A. and Friston, K. J. and Lemieux, L.
                   and Fish, D. R.},
  title = {Studying spontaneous {EEG} activity with f{MRI}},
  journal = {Brain Res Brain Res Rev},
  volume = {43},
  number = {1},
  pages = {110-133},
  abstract = {The multifaceted technological challenge of acquiring
                   simultaneous EEG-correlated fMRI data has now been met
                   and the potential exists for mapping
                   electrophysiological activity with unprecedented
                   spatio-temporal resolution. Work has already begun on
                   studying a host of spontaneous EEG phenomena ranging
                   from alpha rhythm and sleep patterns to epileptiform
                   discharges and seizures, with far reaching clinical
                   implications. However, the transformation of EEG data
                   into linear models suitable for voxel-based statistical
                   hypothesis testing is central to the endeavour. This in
                   turn is predicated upon a number of assumptions
                   regarding the manner in which the generators of EEG
                   phenomena may engender changes in the blood oxygen
                   level dependent (BOLD) signal. Furthermore, important
                   limitations are posed by a set of considerations quite
                   unique to 'paradigmless fMRI'. Here, these issues are
                   assembled and explored to provide an overview of
                   progress made and unresolved questions, with an
                   emphasis on applications in epilepsy.},
  authoraddress = {Department of Clinical and Experimental Epilepsy,
                   Institute of Neurology, University College London,
                   Queen Square, WC1N 3BG, London, UK.
                   a.haddadi@ion.ucl.ac.uk},
  language = {eng},
  medline-aid = {S0165017303001930 [pii]},
  medline-da = {20030922},
  medline-edat = {2003/09/23 05:00},
  medline-fau = {Salek-Haddadi, A ; Friston, K J ; Lemieux, L ; Fish, D
                   R},
  medline-is = {0165-0173},
  medline-jid = {8908638},
  medline-mhda = {2003/09/23 05:00},
  medline-own = {NLM},
  medline-pl = {Netherlands},
  medline-pmid = {14499465},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Academic},
  medline-rf = {213},
  medline-sb = {IM},
  medline-so = {Brain Res Brain Res Rev 2003 Sep;43(1):110-33.},
  medline-stat = {in-process},
  year = 2003
}
@ARTICLE{SHF+97,
  author = {Singh, K. D. and Holliday, I. E. and Furlong, P. L.
                   and Harding, G. F.},
  title = {Evaluation of {MRI}-{MEG}/{EEG} co-registration
                   strategies using {M}onte {C}arlo simulation},
  journal = {Electroencephalogr Clin Neurophysiol},
  volume = {102},
  number = {2},
  pages = {81-85},
  abstract = {We present a Monte Carlo analysis method for
                   evaluating MRI-MEG/EEG co-registration techniques. The
                   method estimates the error in co-registration as a
                   function of position within the brain. Using this
                   analysis technique, we demonstrate the limitations of
                   conventional head-based fiducial point methods, and
                   propose a new strategy utilising a dental bite-bar
                   incorporating accurately machined fiducial markers.
                   Results presented demonstrate the improved accuracy of
                   MEG/EEG to MRI co-registration using the bite-bar.},
  authoraddress = {Department of Vision Sciences, Aston University, Aston
                   Triangle, Birmingham, UK. k.singh@rhbnc.ac.uk},
  keywords = {Brain/*physiology ; *Electroencephalography ; Human ;
                   *Magnetic Resonance Imaging ; *Magnetoencephalography ;
                   *Monte Carlo Method ; Reference Standards},
  language = {eng},
  medline-aid = {S0921884X96965704 [pii]},
  medline-da = {19970401},
  medline-dcom = {19970401},
  medline-edat = {1997/02/01},
  medline-fau = {Singh, K D ; Holliday, I E ; Furlong, P L ; Harding, G
                   F},
  medline-is = {0013-4694},
  medline-jid = {0375035},
  medline-lr = {20001218},
  medline-mhda = {1997/02/01 00:01},
  medline-own = {NLM},
  medline-pl = {IRELAND},
  medline-pmid = {9060858},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Electroencephalogr Clin Neurophysiol 1997
                   Feb;102(2):81-5.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9060858},
  year = 1997
}
@ARTICLE{SHP+04,
  author = {Stephan, K.E. and Harrison, L.M. and Penny, W.D. and
                   Friston, K.J.},
  title = {Biophysical models of f{MRI} responses.},
  journal = {Curr Opin Neurobiol},
  volume = {14},
  number = {5},
  pages = {629-635},
  abstract = {Functional magnetic resonance imaging (fMRI) is used
                   to investigate where the neural implementation of
                   specific cognitive processes occurs. The standard
                   approach uses linear convolution models that relate
                   experimentally designed inputs, through a haemodynamic
                   response function, to observed blood oxygen level
                   dependent (BOLD) signals. Such models are, however,
                   blind to the causal mechanisms that underlie observed
                   BOLD responses. Recent developments have focused on how
                   BOLD responses are generated and include biophysical
                   input-state-output models with neural and haemodynamic
                   state equations and models of functional integration
                   that explain local dynamics through interactions with
                   remote areas. Forward models with parameters at the
                   neural level, such as dynamic causal modelling, combine
                   both approaches, modelling the whole causal chain from
                   external stimuli, via induced neural dynamics, to
                   observed BOLD responses.},
  authoraddress = {The Wellcome Department of Imaging Neuroscience,
                   Institute of Neurology, University College London, 12
                   Queen Square, London WC1N 3BG, UK.
                   k.stephan@fil.ion.ucl.ac.uk},
  language = {eng},
  medline-aid = {S0959-4388(04)00120-5 [pii] ;
                   10.1016/j.conb.2004.08.006 [doi]},
  medline-da = {20041006},
  medline-edat = {2004/10/07 09:00},
  medline-fau = {Stephan, Klaas E ; Harrison, Lee M ; Penny, Will D ;
                   Friston, Karl J},
  medline-is = {0959-4388},
  medline-jid = {9111376},
  medline-mhda = {2004/10/07 09:00},
  medline-own = {NLM},
  medline-pl = {England},
  medline-pmid = {15464897},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Curr Opin Neurobiol 2004 Oct;14(5):629-35.},
  medline-stat = {In-Process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15464897},
  year = 2004
}
@ARTICLE{SKK03,
  author = {Singh, M. and Kim, S. and Kim, T. S.},
  title = {Correlation between {BOLD}-f{MRI} and {EEG} signal
                   changes in response to visual stimulus frequency in
                   humans},
  journal = {Magn Reson Med},
  volume = {49},
  number = {1},
  pages = {108-114},
  abstract = {The correlation between signals acquired using
                   electroencephalography (EEG) and fMRI was investigated
                   in humans during visual stimulation. Evoked potential
                   EEG and BOLD fMRI data were acquired independently
                   under similar conditions from eight subjects during
                   stimulation by a checkerboard flashed at frequencies
                   ranging from 2-12 Hz. The results indicate highly
                   correlated changes in the strength of the EEG signal
                   averaged over two occipital electrodes and the BOLD
                   signal within the occipital lobe as a function of flash
                   frequency for 7/8 subjects (average linear correlation
                   coefficient of 0.76). Both signals peaked at
                   approximately 8 Hz. For one subject the correlation
                   coefficient was 0.20; the EEG signal peaked at 6 Hz and
                   the BOLD signal peaked at 10 Hz. Overall, the EEG and
                   BOLD signals, each averaged over 40-sec stimulation
                   periods, appear to be coupled linearly during visual
                   stimulation by a flashing checkerboard.},
  authoraddress = {Department of Radiology and Biomedical Engineering,
                   University of Southern California (USC), University
                   Park, Los Angeles 90089-1451, USA. msingh@usc.edu},
  keywords = {*Brain Mapping ; *Cerebrovascular Circulation ;
                   Comparative Study ; *Electroencephalography ; Evoked
                   Potentials, Visual ; Human ; *Magnetic Resonance
                   Imaging ; Oxygen/*blood ; *Photic Stimulation ;
                   Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {10.1002/mrm.10335 [doi]},
  medline-ci = {Copyright 2003 Wiley-Liss, Inc.},
  medline-da = {20030101},
  medline-dcom = {20030422},
  medline-edat = {2003/01/02 04:00},
  medline-fau = {Singh, Manbir ; Kim, Sungheon ; Kim, Tae-Seong},
  medline-gr = {P50 AG05142/AG/NIA ; R01 53213/PHS},
  medline-is = {0740-3194},
  medline-jid = {8505245},
  medline-mhda = {2003/04/23 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12509825},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Magn Reson Med 2003 Jan;49(1):108-14.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12509825},
  year = 2003
}
@ARTICLE{SKV+01,
  author = {Salli, E. and Korvenoja, A. and Visa, A. and Katila,
                   T. and Aronen, H. J.},
  title = {Reproducibility of f{MRI}: effect of the use of
                   contextual information},
  journal = {NeuroImage},
  volume = {13},
  number = {3},
  pages = {459-471},
  abstract = {We studied the effect of use of contextual information
                   on the reproducibility of the results in analysis of
                   fMRI data. We used data from a repeated simple motor
                   fMRI experiment. In the first approach, statistical
                   parametric maps were computed from a spatially
                   unsmoothed data and thresholded using a Bonferroni
                   corrected threshold. In the second approach, the maps
                   were computed from a spatially unsmoothed data but were
                   segmented into nonactive and active regions using a
                   spatial contextual clustering method. In the third
                   approach, the statistical parametric maps were computed
                   from spatially smoothed data and thresholded, using,
                   optionally, a spatial extent threshold. The variation
                   in the classification was largest in the Bonferroni
                   thresholded statistical parametric maps. There were no
                   significant differences in variation between
                   statistical parametric maps generated with all the
                   other methods. In addition to reproducibility, the
                   detection rates of weak simulated activations in the
                   presence of measured scanner and physiological noise
                   were investigated. Contextual clustering method was the
                   most sensitive method, while the least sensitive method
                   was the Bonferroni corrected thresholding. Using
                   simulated data, we demonstrated that the contextual
                   clustering method preserves the shapes of activation
                   regions better than the method using spatial smoothing
                   of the data.},
  authoraddress = {Laboratory of Biomedical Engineering, Helsinki
                   University of Technology, Finland.},
  keywords = {Adult ; Attention/*physiology ; *Brain Mapping ;
                   Cerebral Cortex/*physiology ; Cluster Analysis ;
                   Comparative Study ; Echo-Planar Imaging ; Human ;
                   *Image Processing, Computer-Assisted ; *Magnetic
                   Resonance Imaging ; Motor Activity/*physiology ;
                   Pattern Recognition, Visual ; Phantoms, Imaging ;
                   Sensitivity and Specificity ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {10.1006/nimg.2000.0702 [doi] ; S105381190090702X [pii]},
  medline-ci = {Copyright 2001 Academic Press.},
  medline-da = {20010222},
  medline-dcom = {20010517},
  medline-edat = {2001/02/15 11:00},
  medline-fau = {Salli, E ; Korvenoja, A ; Visa, A ; Katila, T ;
                   Aronen, H J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20011119},
  medline-mhda = {2001/05/18 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11170811},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2001 Mar;13(3):459-71.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11170811},
  year = 2001
}
@ARTICLE{SL02,
  author = {Schmitt, U and Louis, A K},
  title = {Efficient algorithms for the regularization of dynamic
                   inverse problems: i. theory},
  journal = {Inverse Problems},
  volume = {18},
  number = {3},
  pages = {645-658},
  abstract = {In this paper dynamic inverse problems are studied,
                   where the investigated object is allowed to change
                   during the measurement procedure. In order to achieve
                   reasonable results, temporal a priori information will
                   be considered. Here, &lquot;temporal
                   smoothness&rquot; is used as a quite general, but for
                   many applications sufficient, a priori information.
                   This is justified in the case of slight movements
                   during an x-ray scan in computerized tomography, or in
                   the field of current density reconstruction, where one
                   wants to conclude from electrical measurements on the
                   surface of the head, the locations of brain activity.
                   First, the notion of a dynamic inverse problem is
                   introduced, then we describe how temporal smoothness
                   can be incorporated in the regularization of the
                   problem, and finally an efficient solver and some
                   regularization properties of this solver are presented.
                   This theory will be exploited in three practically
                   relevant applications in a following paper. },
  year = 2002
}
@ARTICLE{SLM+98,
  author = {Seeck, M. and Lazeyras, F. and Michel, C. M. and
                   Blanke, O. and Gericke, C. A. and Ives, J. and
                   Delavelle, J. and Golay, X. and Haenggeli, C. A. and de
                   Tribolet, N. and Landis, T.},
  title = {Non-invasive epileptic focus localization using
                   {EEG}-triggered functional {MRI} and electromagnetic
                   tomography},
  journal = {Electroencephalogr Clin Neurophysiol},
  volume = {106},
  number = {6},
  pages = {508-512},
  abstract = {We present a new approach for non-invasive
                   localization of focal epileptogenic discharges in
                   patients considered for surgical treatment.
                   EEG-triggered functional MR imaging (fMRI) and 3D EEG
                   source localization were combined to map the primary
                   electrical source with high spatial resolution. The
                   method is illustrated by the case of a patient with
                   medically intractable frontal lobe epilepsy. EEG
                   obtained in the MRI system allowed triggering of the
                   fMRI acquisition by the patient's habitual
                   epileptogenic discharges. fMRI revealed multiple areas
                   of signal enhancement. Three-dimensional EEG source
                   localization identified the same active areas and
                   provided evidence of onset in the left frontal lobe.
                   Subsequent electrocorticography from subdural
                   electrodes confirmed spike and seizure onset over this
                   region. This approach, i.e. the combination of
                   EEG-triggered fMRI and 3D EEG source analysis,
                   represents a promising additional tool for presurgical
                   epilepsy evaluation allowing precise non-invasive
                   identification of the epileptic foci.},
  authoraddress = {Department of Neurology, University Hospital of
                   Geneva, Switzerland. mase@diogenes.hcuge.ch},
  keywords = {Adolescent ; Electroencephalography/*methods ;
                   Epilepsies, Partial/*physiopathology ; Epilepsy,
                   Frontal Lobe/*physiopathology ; Female ; Human ; Image
                   Processing, Computer-Assisted ; Magnetic Resonance
                   Imaging/*methods ; Magnetoencephalography/*methods ;
                   Support, Non-U.S. Gov't ; Tomography},
  language = {eng},
  medline-aid = {S0013469498000170 [pii]},
  medline-da = {19980928},
  medline-dcom = {19980928},
  medline-edat = {1998/09/19},
  medline-fau = {Seeck, M ; Lazeyras, F ; Michel, C M ; Blanke, O ;
                   Gericke, C A ; Ives, J ; Delavelle, J ; Golay, X ;
                   Haenggeli, C A ; de Tribolet, N ; Landis, T},
  medline-is = {0013-4694},
  medline-jid = {0375035},
  medline-lr = {20031114},
  medline-mhda = {1998/09/19 00:01},
  medline-own = {NLM},
  medline-pl = {IRELAND},
  medline-pmid = {9741750},
  medline-pst = {ppublish},
  medline-pt = {Case Reports ; Journal Article},
  medline-sb = {IM},
  medline-so = {Electroencephalogr Clin Neurophysiol 1998
                   Jun;106(6):508-12.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9741750},
  year = 1998
}
@ARTICLE{SLO96,
  author = {Sanders, J. A. and Lewine, J. D. and Orrison, Jr, W.
                   W.},
  title = {Comparison of primary motor cortex localization using
                   functional magnetic resonance imaging and
                   magnetoencephalography},
  journal = {Human Brain Mapping},
  volume = {4},
  number = {1},
  pages = {47--57},
  abstract = {The primary goal of the study was to compare estimates
                   of motor cortex localization from functional magnetic
                   resonance imaging (FMRI) and magnetoencephalography
                   (MEG). Thirteen normal volunteers were studied using
                   both methods. FMRI was performed on a clinical 1.5 T
                   system using gradient-echo acquisitions and basic
                   t-test processing. MEG primary motor field was
                   characterized by a single dipole model. Comparisons
                   between the location of the best-fitting MEG dipole and
                   the FMRI activation results were made using both fixed
                   regions-of-interest weighted averaging and clustering
                   analysis to reduce the observed FMRI activations to a
                   single representative location.Both FMRI and MEG
                   identified expected anatomic regions of primary motor
                   activity and there was overall agreement to within 10
                   mm between these two functional imaging modalities.
                   Given the observed agreement between these two
                   techniques, it does not appear that the proposed
                   artifactual mechanisms of local bulk motions or
                   large-vessel sensitivity will seriously preclude the
                   clinical utility of FMRI for preoperative localization
                   of sensorimotor cortex.  1996 Wiley-Liss, Inc.},
  owner = {yoh},
  timestamp = {2006.06.05},
  url = {http://dx.doi.org/10.1002/(SICI)1097-0193(1996)4:1<47::AID-HBM3>3.0.CO;2-P},
  year = 1996
}
@ARTICLE{SLW+02,
  author = {Schmitt, U and Louis, A K and Wolters, C and
                   Vauhkonen, M},
  title = {Efficient algorithms for the regularization of dynamic
                   inverse problems: ii. applications},
  journal = {Inverse Problems},
  volume = {18},
  number = {3},
  pages = {659-676},
  abstract = {In the first part of this paper the notion of dynamic
                   inverse problems was introduced and two procedures,
                   namely STR and STR-C, for the efficient spatio-temporal
                   regularization of such problems were developed. In this
                   part the application of the new methods to three
                   practically important problems, namely dynamic
                   computerized tomography, dynamic electrical impedance
                   tomography and spatio-temporal current density
                   reconstructions will be presented. Dynamic
                   reconstructions will be carried out in simulated
                   objects which show the quality of the methods and the
                   efficiency of the solution process. A comparison to a
                   Kalman smoother approach will be given for dynEIT. },
  year = 2002
}
@ARTICLE{SMJ+05,
  author = {Sehatpour, P. and Molholm, S. and Javitt, D.C. and
                   Foxe, J.J.},
  title = {Spatiotemporal dynamics of human object recognition
                   processing: {A}n integrated high-density electrical
                   mapping and functional imaging study of "closure"
                   processes.},
  journal = {Neuroimage},
  abstract = {Humans are capable of recognizing objects, often
                   despite highly adverse viewing conditions (e.g.,
                   occlusion). The term "perceptual closure" has been used
                   to refer to the neural processes responsible for
                   "filling-in" missing information in the visual image
                   under such conditions. Closure phenomena have been
                   linked to a group of object recognition areas, the
                   so-called lateral-occipital complex (LOC). Here, we
                   investigated the spatiotemporal dynamics of perceptual
                   closure processes by coregistering data from
                   high-density electrical recordings (ERPs) and
                   functional magnetic resonance imaging (fMRI) while
                   subjects participated in a perceptual closure task.
                   Subjects were presented with highly fragmented images
                   and control scrambled images. Fragmented images were
                   calibrated to be 'just' recognizable as objects (that
                   is, perceptual closure was necessary), whereas the
                   scrambled images were unrecognizable. Comparison of
                   responses to these two stimulus classes revealed the
                   neural processes underlying perceptual closure. fMRI
                   revealed an object recognition system that mediates
                   these closure processes, the core of which consists of
                   the LOC regions. ERP recordings resulted in the
                   well-characterized N(CL) component (for negativity
                   associated with closure), a robust relative negativity
                   over bilateral occipito-temporal scalp that occurs in
                   the 230-400 ms timeframe. Our investigations further
                   revealed an extended network of dorsal and frontal
                   regions, also involved in perceptual closure processes.
                   Inverse source analysis showed that the major
                   generators of N(CL) localized to the identical regions
                   within LOC revealed by the fMRI recordings and detailed
                   the temporal dynamics across these LOC regions
                   including interactions between LOC and these other
                   nodes of the object recognition circuit.},
  authoraddress = {The Cognitive Neurophysiology Laboratory, Nathan S.
                   Kline Institute for Psychiatric Research, Program in
                   Cognitive Neuroscience and Schizophrenia, 140 Old
                   Orangeburg Road, Orangeburg, NY 10962, USA; Ferkauf
                   Graduate School Of Psychology, Albert Einstein College
                   of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461,
                   USA.},
  language = {ENG},
  medline-aid = {S1053-8119(05)00563-X [pii] ;
                   10.1016/j.neuroimage.2005.07.049 [doi]},
  medline-da = {20050919},
  medline-dep = {20050914},
  medline-edat = {2005/09/20 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2005/09/20 09:00},
  medline-own = {NLM},
  medline-phst = {2005/04/27 [received] ; 2005/07/03 [revised] ;
                   2005/07/27 [accepted]},
  medline-pmid = {16168676},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2005 Sep 14;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16168676},
  year = 2005
}
@ARTICLE{SMJ+07,
  author = {Siniatchkin, M. and Moeller, F. and Jacobs, J. and
                   Stephani, U. and Boor, R. and Wolff, S. and Jansen, O.
                   and Siebner, H. and Scherg, M.},
  title = {Spatial filters and automated spike detection based on
                   brain topographies improve sensitivity of {EEG}-f{MRI}
                   studies in focal epilepsy.},
  journal = {Neuroimage},
  volume = {37},
  number = {3},
  pages = {834-43},
  abstract = {The ballistocardiogram (BCG) represents one of the
                   most prominent sources of artifacts that contaminate
                   the electroencephalogram (EEG) during functional MRI.
                   The BCG artifacts may affect the detection of
                   interictal epileptiform discharges (IED) in patients
                   with epilepsy, reducing the sensitivity of the combined
                   EEG-fMRI method. In this study we improved the BCG
                   artifact correction using a multiple source correction
                   (MSC) approach. On the one hand, a source analysis of
                   the IEDs was applied to the EEG data obtained outside
                   the MRI scanner to prevent the distortion of EEG
                   signals of interest during the correction of BCG
                   artifacts. On the other hand, the topographies of the
                   BCG artifacts were defined based on the EEG recorded
                   inside the scanner. The topographies of the BCG
                   artifacts were then added to the surrogate model of IED
                   sources and a combined source model was applied to the
                   data obtained inside the scanner. The artifact signal
                   was then subtracted without considerable distortion of
                   the IED topography. The MSC approach was compared with
                   the traditional averaged artifact subtraction (AAS)
                   method. Both methods reduced the spectral power of
                   BCG-related harmonics and enabled better detection of
                   IEDs. Compared with the conventional AAS method, the
                   MSC approach increased the sensitivity of IED detection
                   because the IED signal was less attenuated when
                   subtracting the BCG artifacts. The proposed MSC method
                   is particularly useful in situations in which the BCG
                   artifact is spatially correlated and time-locked with
                   the EEG signal produced by the focal brain activity of
                   interest.},
  authoraddress = {Christian-Albrechts-University, University Hospital of
                   Pediatric Neurology, Schwanenweg 20, D-24105 Kiel,
                   Germany. m.siniatchkin@pedneuro.uni-kiel.de},
  language = {eng},
  medline-aid = {S1053-8119(07)00420-X [pii] ;
                   10.1016/j.neuroimage.2007.05.049 [doi]},
  medline-da = {20070820},
  medline-dep = {20070607},
  medline-edat = {2007/07/14 09:00},
  medline-fau = {Siniatchkin, Michael ; Moeller, Friederike ; Jacobs,
                   Julia ; Stephani, Ulrich ; Boor, Rainer ; Wolff,
                   Stephan ; Jansen, Olav ; Siebner, Hartwig ; Scherg,
                   Michael},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage},
  medline-mhda = {2007/07/14 09:00},
  medline-own = {NLM},
  medline-phst = {2006/12/22 [received] ; 2007/05/03 [revised] ;
                   2007/05/07 [accepted] ; 2007/06/07 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {17627849},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2007 Sep 1;37(3):834-43. Epub 2007 Jun 7.},
  medline-stat = {In-Process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17627849},
  year = 2007
}
@ARTICLE{SML+02,
  author = {Salek-Haddadi, A. and Merschhemke, M. and Lemieux, L.
                   and Fish, D. R.},
  title = {Simultaneous {EEG}-{C}orrelated {I}ctal f{MRI}},
  journal = {NeuroImage},
  volume = {16},
  number = {1},
  pages = {32-40},
  abstract = {The ability to continuously acquire simultaneous EEG
                   and fMRI data during seizures presents a formidable
                   challenge both clinically and technically. Published
                   ictal fMRI reports have so far been unable to benefit
                   from simultaneous electrographic recordings and remain
                   largely assumptive. Unique findings from a Continuous
                   EEG-correlated fMRI experiment are presented in which a
                   focal subclinical seizure was captured in its entirety.
                   For the first time dynamic and biphasic Blood Oxygen
                   Level Dependent (BOLD) signal changes are shown using
                   statistical parametric mapping time-locked to the ictal
                   EEG activity localizing seizure generation and
                   propagation sites, with millimeter resolution, to
                   electroclinically concordant gray matter structures.
                   Though presently of limited clinical applicability, a
                   new avenue is opened for further research.},
  authoraddress = {Department of Clinical and Experimental Epilepsy,
                   Institute of Neurology, University College London,
                   Queen Square, London, United Kingdom.},
  keywords = {Brain Mapping ; *Electroencephalography ;
                   Epilepsy/*pathology/*physiopathology ; Epilepsy,
                   Tonic-Clonic/pathology/physiopathology ; Fourier
                   Analysis ; Human ; Image Processing, Computer-Assisted
                   ; *Magnetic Resonance Imaging ; Male ; Middle Aged ;
                   Oxygen/blood ; Support, Non-U.S. Gov't ; Telemetry},
  language = {eng},
  medline-aid = {10.1006/nimg.2002.1073 [doi] ; S1053811902910736 [pii]},
  medline-ci = {2002 Elsevier Science (USA).},
  medline-da = {20020423},
  medline-dcom = {20040329},
  medline-edat = {2002/04/24 10:00},
  medline-fau = {Salek-Haddadi, Afraim ; Merschhemke, Martin ; Lemieux,
                   Louis ; Fish, David R},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/03/30 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11969315},
  medline-pst = {ppublish},
  medline-pt = {Case Reports ; Journal Article},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {NeuroImage 2002 May;16(1):32-40.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11969315},
  year = 2002
}
@ARTICLE{SMV+99,
  author = {Sijbers, J. and Michiels, I. and Verhoye, M. and Van
                   Audekerke, J. and Van der Linden, A. and Van Dyck, D.},
  title = {Restoration of {MR}-induced artifacts in
                   simultaneously recorded {MR}/{EEG} data},
  journal = {Magn Reson Imaging},
  volume = {17},
  number = {9},
  pages = {1383-1391},
  abstract = {During a Magnetic Resonance sequence, simultaneously
                   acquired ElectroEncephaloGraphy (EEG) data are
                   compromised by severe pollution due to artifacts
                   originating from the switching of the magnetic field
                   gradients. In this work, it is shown how these
                   artifacts can be strongly reduced or even removed
                   through application of an adaptive artifact restoration
                   scheme. The method has proved to be fully automatic and
                   to retain high frequency EEG information, which is
                   indispensable for many EEG applications.},
  authoraddress = {Vision Lab, University of Antwerp, Belgium.
                   sijbers@ruca.ua.ac.be},
  keywords = {Animals ; *Artifacts ;
                   Electroencephalography/instrumentation/*methods ; Image
                   Processing, Computer-Assisted/methods ; Magnetic
                   Resonance Imaging/instrumentation/*methods ; Rats ;
                   Rats, Wistar ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S0730725X9900096X [pii]},
  medline-da = {20000215},
  medline-dcom = {20000215},
  medline-edat = {1999/11/27 09:00},
  medline-fau = {Sijbers, J ; Michiels, I ; Verhoye, M ; Van Audekerke,
                   J ; Van der Linden, A ; Van Dyck, D},
  medline-is = {0730-725X},
  medline-jid = {8214883},
  medline-lr = {20031114},
  medline-mhda = {2000/02/19 09:00},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10576723},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Magn Reson Imaging 1999 Nov;17(9):1383-91.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10576723},
  year = 1999
}
@ARTICLE{SMV03,
  author = {Sommer, M. and Meinhardt, J. and Volz, H. P.},
  title = {Combined measurement of event-related potentials
                   ({ERP}s) and f{MRI}},
  journal = {Acta Neurobiol Exp (Wars)},
  volume = {63},
  number = {1},
  pages = {49-53},
  abstract = {The study investigates the possibility of combined
                   recording event-related potentials (ERPs) and
                   functional MRI (fMRI). Visual evoked potentials (VEPs)
                   were elicited by an alternating black and white
                   checkerboard, which was presented blockwise outside the
                   static 1.5 T magnetic field and during an echo planar
                   imaging (EPI). An fMRI sequence with a time window for
                   interleaved EEG-measurement and a measurement protocol
                   which reduces pulse artifacts and vibrations was used.
                   Thus, during an EPI sequence, it was possible to detect
                   VEPs which had the same structure and latencies as VEPs
                   outside the magnetic field and which corresponded well
                   with the observed activated areas of the visual cortex.},
  authoraddress = {Department of Psychiatry and Psychotherapy, University
                   of Regensburg, Regensburg, Germany.
                   monika.sommer@bkr-regensburg.de},
  keywords = {Adult ; Brain/*physiology ; *Echo-Planar Imaging ;
                   *Electroencephalography ; *Evoked Potentials, Visual ;
                   Female ; Human ; Male ; Reaction Time},
  language = {eng},
  medline-da = {20030604},
  medline-dcom = {20030721},
  medline-edat = {2003/06/06 05:00},
  medline-fau = {Sommer, Monika ; Meinhardt, Jorg ; Volz, Hans-Peter},
  medline-is = {0065-1400},
  medline-jid = {1246675},
  medline-lr = {20031003},
  medline-mhda = {2003/07/23 05:00},
  medline-own = {NLM},
  medline-pl = {Poland},
  medline-pmid = {12784932},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Acta Neurobiol Exp (Wars) 2003;63(1):49-53.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12784932},
  year = 2003
}
@ARTICLE{SN97,
  author = {Saleheen, H. I. and Ng, K. T.},
  title = {New finite difference formulations for general
                   inhomogeneous anisotropic bioelectric problems},
  journal = {IEEE Trans Biomed Eng},
  volume = {44},
  number = {9},
  pages = {800-809},
  abstract = {Due to its low computational complexity, finite
                   difference modeling offers a viable tool for studying
                   bioelectric problems, allowing the field behavior to be
                   observed easily as different system parameters are
                   varied. Previous finite difference formulations,
                   however, have been limited mainly to systems in which
                   the conductivity is orthotropic, i.e., a strictly
                   diagonal conductivity tensor. This in turn has limited
                   the effectiveness of the finite difference, technique
                   in modeling complex anatomies with arbitrarily
                   anisotropic conductivities, e.g., detailed fiber
                   structures of muscles where the fiber can lie in any
                   arbitrary direction. In this paper, we present both
                   two-dimensional and three-dimensional finite difference
                   formulations that are valid for structures with an
                   inhomogeneous and nondiagonal conductivity tensor. A
                   data parallel computer, the connection machine CM-5, is
                   used in the finite difference implementation to provide
                   the computational power and memory for solving large
                   problems. The finite difference grid is mapped
                   effectively to the CM-5 by associating a group of nodes
                   with one processor. Details on the new approach and its
                   data parallel implementation are presented together
                   with validation and computational performance results.
                   In addition, an application of the new formulation in
                   providing the potential distribution inside a canine
                   torso during electrical defibrillation is demonstrated.},
  authoraddress = {National Applied Software Engineering Center,
                   Concurrent Technologies Corporation, Johnstown, PA
                   15904, USA.},
  keywords = {Algorithms ; Animals ; Anisotropy ; *Computer
                   Simulation ; Dogs ; Electric Conductivity ; *Electric
                   Countershock ; *Models, Cardiovascular ; Radiography,
                   Thoracic ; Support, U.S. Gov't, P.H.S. ; Tomography,
                   X-Ray Computed},
  language = {eng},
  medline-da = {19970916},
  medline-dcom = {19970916},
  medline-edat = {1997/09/01},
  medline-fau = {Saleheen, H I ; Ng, K T},
  medline-gr = {R01-HL-44747/HL/NHLBI},
  medline-is = {0018-9294},
  medline-jid = {0012737},
  medline-lr = {20031114},
  medline-mhda = {1997/09/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9282472},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng 1997 Sep;44(9):800-9.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9282472},
  year = 1997
}
@ARTICLE{SOJ+06,
  author = {Schmid, M. C. and Oeltermann, A. and Juchem, C. and
                   Logothetis, N. K. and Smirnakis, S. M.},
  title = {Simultaneous {EEG} and f{MRI} in the macaque monkey at
                   4.7 {T}esla.},
  journal = {Magn Reson Imaging},
  volume = {24},
  number = {4},
  pages = {335-42},
  abstract = {Simultaneous electroencephalography (EEG)/functional
                   magnetic resonance imaging (fMRI) acquisition can
                   identify the brain networks involved in generating
                   specific EEG patterns. Yet, the combination of these
                   methodologies is hampered by strong artifacts that
                   arise due to electromagnetic interference during
                   magnetic resonance (MR) image acquisition. Here, we
                   report corrections of the gradient-induced artifact in
                   phantom measurements and in experiments with an awake
                   behaving macaque monkey during fMRI acquisition at a
                   magnetic field strength of 4.7 T. Ninety-one percent of
                   the amplitude of a 10 microV, 10 Hz phantom signal
                   could successfully be recovered without phase
                   distortions. Using this method, we were able to extract
                   the monkey EEG from scalp recordings obtained during MR
                   image acquisition. Visual evoked potentials could also
                   be reliably identified. In conclusion, simultaneous
                   EEG/fMRI acquisition is feasible in the macaque monkey
                   preparation at 4.7 T and holds promise for
                   investigating the neural processes that give rise to
                   particular EEG patterns.},
  authoraddress = {Max Planck Institute for Biological Cybernetics,
                   D-72076 Tubingen, Germany.
                   michael.schmid@tuebingen.mpg.de},
  language = {eng},
  medline-aid = {S0730-725X(06)00038-5 [pii] ;
                   10.1016/j.mri.2005.12.024 [doi]},
  medline-da = {20060508},
  medline-dep = {20060329},
  medline-edat = {2006/05/09 09:00},
  medline-fau = {Schmid, Michael C ; Oeltermann, Axel ; Juchem,
                   Christoph ; Logothetis, Nikos K ; Smirnakis, Stelios M},
  medline-gr = {KO8/PHS},
  medline-is = {0730-725X (Print)},
  medline-jid = {8214883},
  medline-jt = {Magnetic resonance imaging.},
  medline-mhda = {2006/05/09 09:00},
  medline-own = {NLM},
  medline-phst = {2005/12/02 [received] ; 2005/12/02 [accepted] ;
                   2006/03/29 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16677938},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Magn Reson Imaging. 2006 May;24(4):335-42. Epub 2006
                   Mar 29.},
  medline-stat = {In-Process},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16677938},
  year = 2006
}
@ARTICLE{SPW+04,
  author = {Soltysik, D. A. and Peck, K. K. and White, K. D. and
                   Crosson, B. and Briggs, R. W.},
  title = {Comparison of hemodynamic response nonlinearity across
                   primary cortical areas},
  journal = {NeuroImage},
  volume = {22},
  number = {3},
  pages = {1117-1127},
  abstract = {Hemodynamic responses to auditory and visual stimuli
                   and motor tasks were assessed for the nonlinearity of
                   response in each of the respective primary cortices.
                   Five stimulus or task durations were used (1, 2, 4, 8,
                   and 16 s), and five male subjects (aged 19 +/- 1.9
                   years) were imaged. Two tests of linearity were
                   conducted. The first test consisted of using BOLD
                   responses to short stimuli to predict responses to
                   longer stimuli. The second test consisted of fitting
                   ideal impulse response functions to the observed
                   responses for each event duration. Both methods show
                   that the extent of the nonlinearity varies across
                   cortices. Results for the second method indicate that
                   the hemodynamic response is nonlinear for stimuli less
                   than 10 s in the primary auditory cortex, nonlinear for
                   tasks less than 7 s in the primary motor cortex, and
                   nonlinear for stimuli less than 3 s in the primary
                   visual cortex. In addition, neural adaptation functions
                   were characterized that could model the observed
                   nonlinearities.},
  authoraddress = {Department of Nuclear and Radiological Engineering,
                   University of Florida, Gainesville, FL 32610, USA.
                   dsoltysi@mcw.edu},
  keywords = {Acoustic Stimulation ; Adaptation, Physiological ;
                   Adult ; Algorithms ; Cerebral Cortex/*blood
                   supply/physiology ; *Cerebrovascular Circulation ;
                   Comparative Study ; Hemodynamic Processes ; Human ;
                   Linear Models ; Male ; *Models, Cardiovascular ; Motor
                   Activity/physiology ; *Nonlinear Dynamics ; Photic
                   Stimulation ; Physical Stimulation ; Support, Non-U.S.
                   Gov't ; Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2004.03.024 [doi] ;
                   S1053811904001624 [pii]},
  medline-ci = {Copyright 2004 Elsevier Inc.},
  medline-da = {20040628},
  medline-dcom = {20040916},
  medline-edat = {2004/06/29 05:00},
  medline-fau = {Soltysik, David A ; Peck, Kyung K ; White, Keith D ;
                   Crosson, Bruce ; Briggs, Richard W},
  medline-gr = {P50-DC03888/DC/NIDCD},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/09/17 05:00},
  medline-own = {NLM},
  medline-phst = {2003/10/21 [received] ; 2004/03/03 [revised] ;
                   2004/03/08 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15219583},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Jul;22(3):1117-27.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15219583},
  year = 2004
}
@ARTICLE{SST+04,
  author = {Seiyama, A. and Seki, J. and Tanabe, H. C. and Sase,
                   I. and Takatsuki, A. and Miyauchi, S. and Eda, H. and
                   Hayashi, S. and Imaruoka, T. and Iwakura, T. and
                   Yanagida, T.},
  title = {Circulatory basis of f{MRI} signals: relationship
                   between changes in the hemodynamic parameters and
                   {BOLD} signal intensity},
  journal = {NeuroImage},
  volume = {21},
  number = {4},
  pages = {1204-1214},
  abstract = {Blood oxygenation level-dependent functional magnetic
                   resonance imaging (BOLD-fMRI) is widely used as a tool
                   for functional brain mapping. During brain activation,
                   increases in the regional blood flow lead to an
                   increase in blood oxygenation and a decrease in
                   paramagnetic deoxygenated hemoglobin (deoxy-Hb),
                   causing an increase in the MR signal intensity at the
                   site of brain activation. However, not a few studies
                   using fMRI have failed to detect activation of areas
                   that ought to have been activated. We assigned
                   BOLD-positive (an increase in the signal intensity),
                   BOLD-negative (a decrease in the signal intensity), and
                   BOLD-silent (no change) brain activation to respective
                   circulatory conditions through a description of fMRI
                   signals as a function of the concentration of
                   oxygenated Hb (oxy-Hb) and deoxy-Hb obtained with
                   near-infrared optical imaging (NIOI). Using this model,
                   we explain the sensory motor paradox in terms of
                   BOLD-positive, BOLD-negative, and BOLD-silent brain
                   activation.},
  authoraddress = {Brain Information Group, Kansai Advanced Research
                   Center, Communications Research Laboratory, Nishi-ku,
                   Kobe, Hyogo, Japan. aseiyama@po.crl.go.jp},
  keywords = {Adult ; Afferent Pathways/physiology ;
                   Arousal/*physiology ; Brain/*blood supply ; Brain
                   Mapping ; Electric Stimulation ;
                   *Electroencephalography ; Evoked Potentials/physiology
                   ; Female ; Hemoglobins/metabolism ; Human ; *Image
                   Enhancement ; *Image Processing, Computer-Assisted ;
                   *Imaging, Three-Dimensional ; Laser-Doppler Flowmetry ;
                   *Magnetic Resonance Imaging ; Male ; Median
                   Nerve/physiology ; Middle Aged ; Motor
                   Cortex/physiology ; Oxygen/*blood ; Oxygen
                   Consumption/physiology ; Oxyhemoglobins/metabolism ;
                   Pattern Recognition, Visual/physiology ; Photic
                   Stimulation ; Reference Values ; Somatosensory
                   Cortex/physiology ; Support, Non-U.S. Gov't ;
                   *Tomography, Optical ; Visual Cortex/physiology},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.12.002 [doi] ;
                   S1053811903007523 [pii]},
  medline-da = {20040330},
  medline-dcom = {20040806},
  medline-edat = {2004/03/31 05:00},
  medline-fau = {Seiyama, Akitoshi ; Seki, Junji ; Tanabe, Hiroki C ;
                   Sase, Ichiro ; Takatsuki, Akira ; Miyauchi, Satoru ;
                   Eda, Hideo ; Hayashi, Shigeru ; Imaruoka, Toshihide ;
                   Iwakura, Takeo ; Yanagida, Toshio},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/08/07 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Mar/31 [received] ; 2003/Dec/03 [revised] ;
                   2003/Dec/03 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15050548},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-rn = {0 (Hemoglobins) ; 0 (Oxyhemoglobins) ; 7782-44-7
                   (Oxygen) ; 9008-02-0 (deoxyhemoglobin)},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Apr;21(4):1204-14.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15050548},
  year = 2004
}
@ARTICLE{SVVH+00,
  author = {Sijbers, J. and Vanrumste, B. and Van Hoey, G. and
                   Boon, P. and Verhoye, M. and Van der Linden, A. and Van
                   Dyck, D.},
  title = {Automatic localization of {EEG} electrode markers
                   within 3{D} {MR} data},
  journal = {Magn Reson Imaging},
  volume = {18},
  number = {4},
  pages = {485-488},
  abstract = {The electrical activity of the brain can be monitored
                   using ElectroEncephaloGraphy (EEG). From the positions
                   of the EEG electrodes, it is possible to localize focal
                   brain activity. Thereby, the accuracy of the
                   localization strongly depends on the accuracy with
                   which the positions of the electrodes can be
                   determined. In this work, we present an automatic,
                   simple, and accurate scheme that detects EEG electrode
                   markers from 3D MR data of the human head.},
  authoraddress = {Vision Lab, University of Antwerp, Antwerp, Belgium.
                   Sijbers@ua.ac.be},
  keywords = {*Electrodes ;
                   *Electroencephalography/instrumentation/methods ; Human
                   ; *Image Processing, Computer-Assisted ; *Magnetic
                   Resonance Imaging ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S0730725X00001211 [pii]},
  medline-da = {20000518},
  medline-dcom = {20000518},
  medline-edat = {2000/05/02 09:00},
  medline-fau = {Sijbers, J ; Vanrumste, B ; Van Hoey, G ; Boon, P ;
                   Verhoye, M ; Van der Linden, A ; Van Dyck, D},
  medline-is = {0730-725X},
  medline-jid = {8214883},
  medline-lr = {20001218},
  medline-mhda = {2000/05/20 09:00},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10788727},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Magn Reson Imaging 2000 May;18(4):485-8.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10788727},
  year = 2000
}
@ARTICLE{SWD+07,
  author = {Stephan, K. E. and Weiskopf, N. and Drysdale, P. M.
                   and Robinson, P. A. and Friston, K. J.},
  title = {Comparing hemodynamic models with {DCM}.},
  journal = {Neuroimage},
  abstract = {The classical model of blood oxygen level-dependent
                   (BOLD) responses by Buxton et al. [Buxton, R.B., Wong,
                   E.C., Frank, L.R., 1998. Dynamics of blood flow and
                   oxygenation changes during brain activation: the
                   Balloon model. Magn. Reson. Med. 39, 855-864] has been
                   very important in providing a biophysically plausible
                   framework for explaining different aspects of
                   hemodynamic responses. It also plays an important role
                   in the hemodynamic forward model for dynamic causal
                   modeling (DCM) of fMRI data. A recent study by Obata et
                   al. [Obata, T., Liu, T.T., Miller, K.L., Luh, W.M.,
                   Wong, E.C., Frank, L.R., Buxton, R.B., 2004.
                   Discrepancies between BOLD and flow dynamics in primary
                   and supplementary motor areas: application of the
                   Balloon model to the interpretation of BOLD transients.
                   NeuroImage 21, 144-153] linearized the BOLD signal
                   equation and suggested a revised form for the model
                   coefficients. In this paper, we show that the classical
                   and revised models are special cases of a generalized
                   model. The BOLD signal equation of this generalized
                   model can be reduced to that of the classical Buxton
                   model by simplifying the coefficients or can be
                   linearized to give the Obata model. Given the
                   importance of hemodynamic models for investigating BOLD
                   responses and analyses of effective connectivity with
                   DCM, the question arises which formulation is the best
                   model for empirically measured BOLD responses. In this
                   article, we address this question by embedding
                   different variants of the BOLD signal equation in a
                   well-established DCM of functional interactions among
                   visual areas. This allows us to compare the ensuing
                   models using Bayesian model selection. Our model
                   comparison approach had a factorial structure,
                   comparing eight different hemodynamic models based on
                   (i) classical vs. revised forms for the coefficients,
                   (ii) linear vs. non-linear output equations, and (iii)
                   fixed vs. free parameters, epsilon, for region-specific
                   ratios of intra- and extravascular signals. Using fMRI
                   data from a group of twelve subjects, we demonstrate
                   that the best model is a non-linear model with a
                   revised form for the coefficients, in which epsilon is
                   treated as a free parameter.},
  authoraddress = {Wellcome Trust Centre for Neuroimaging, Institute of
                   Neurology, University College London, 12 Queen Square,
                   London WC1N 3BG, UK.},
  language = {ENG},
  medline-aid = {S1053-8119(07)00648-9 [pii] ;
                   10.1016/j.neuroimage.2007.07.040 [doi]},
  medline-da = {20070921},
  medline-dep = {20070811},
  medline-edat = {2007/09/22 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2007/09/22 09:00},
  medline-own = {NLM},
  medline-phst = {2007/02/25 [received] ; 2007/07/15 [revised] ;
                   2007/07/20 [accepted]},
  medline-pmid = {17884583},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2007 Aug 11;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17884583},
  year = 2007
}
@ARTICLE{SWP04,
  author = {Stefanovic, B. and Warnking, J. M. and Pike, G. B.},
  title = {Hemodynamic and metabolic responses to neuronal
                   inhibition},
  journal = {NeuroImage},
  volume = {22},
  number = {2},
  pages = {771-778},
  abstract = {Functional magnetic resonance imaging (fMRI) was used
                   to investigate the changes in blood oxygenation level
                   dependent (BOLD) signal, cerebral blood flow (CBF) and
                   cerebral metabolic rate of oxygen consumption
                   (CMR(O(2))) accompanying neuronal inhibition. Eight
                   healthy volunteers performed a periodic right-hand
                   pinch grip every second using 5\% of their maximum
                   voluntary contraction (MVC), a paradigm previously
                   shown to produce robust ipsilateral neuronal
                   inhibition. To simultaneously quantify CBF and BOLD
                   signals, an interleaved multislice pulsed arterial spin
                   labeling (PASL) and T(2)*-weighted gradient echo
                   sequence was employed. The CMR(O(2)) was calculated
                   using the deoxyhemoglobin dilution model, calibrated by
                   data measured during graded hypercapnia. In all
                   subjects, BOLD, CBF and CMR(O(2)) signals increased in
                   the contralateral and decreased in the ipsilateral
                   primary motor (M1) cortex. The relative changes in
                   CMR(O(2)) and CBF were linearly related, with a slope
                   of approximately 0.4. The coupling ratio thus
                   established for both positive and negative CMR(O(2))
                   and CBF changes is in close agreement with the ones
                   observed by earlier studies investigating M1 perfusion
                   and oxygen consumption increases. These findings
                   characterize the hemodynamic and metabolic
                   downregulation accompanying neuronal inhibition and
                   thereby establish the sustained negative BOLD response
                   as a marker of neuronal deactivation.},
  authoraddress = {McConnell Brain Imaging Centre, Montreal Neurological
                   Institute, Montreal, Quebec, Canada H3A 2B4.},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2004.01.036 [doi] ;
                   S1053811904000321 [pii]},
  medline-da = {20040614},
  medline-edat = {2004/06/15 05:00},
  medline-fau = {Stefanovic, Bojana ; Warnking, Jan M ; Pike, G Bruce},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/06/15 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Sep/30 [received] ; 2003/Dec/11 [revised] ;
                   2004/Jan/06 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15193606},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Jun;22(2):771-8.},
  medline-stat = {in-data-review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15193606},
  year = 2004
}
@ARTICLE{Sar87,
  author = {Sarvas, J.},
  title = {Basic mathematical and electromagnetic concepts of the
                   biomagnetic inverse problem},
  journal = {Phys Med Biol},
  volume = {32},
  number = {1},
  pages = {11-22},
  abstract = {In this paper basic mathematical and physical concepts
                   of the biomagnetic inverse problem are reviewed with
                   some new approaches. The forward problem is discussed
                   for both homogeneous and inhomogeneous media.
                   Geselowitz' formulae and a surface integral equation
                   are presented to handle a piecewise homogeneous
                   conductor. The special cases of a spherically symmetric
                   conductor and a horizontally layered medium are
                   discussed in detail. The non-uniqueness of the solution
                   of the magnetic inverse problem is discussed and the
                   difficulty caused by the contribution of the electric
                   potential to the magnetic field outside the conductor
                   is studied. As practical methods of solving the inverse
                   problem, a weighted least-squares search with
                   confidence limits and the method of minimum norm
                   estimate are discussed.},
  keywords = {Animals ; Electric Conductivity ; Human ; *Magnetics ;
                   Mathematics ; *Models, Biological ; Support, Non-U.S.
                   Gov't},
  language = {eng},
  medline-da = {19870410},
  medline-dcom = {19870410},
  medline-edat = {1987/01/01},
  medline-fau = {Sarvas, J},
  medline-is = {0031-9155},
  medline-jid = {0401220},
  medline-lr = {20031114},
  medline-mhda = {1987/01/01 00:01},
  medline-own = {NLM},
  medline-pl = {ENGLAND},
  medline-pmid = {3823129},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Phys Med Biol 1987 Jan;32(1):11-22.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=3823129},
  year = 1987
}
@ARTICLE{Sin99,
  author = {Singer, W.},
  title = {Time as coding space?},
  journal = {Curr Opin Neurobiol},
  volume = {9},
  number = {2},
  pages = {189-94},
  abstract = {There is increasing evidence that neuronal networks
                   can operate with a temporal resolution in the
                   millisecond range. In principle, this provides the
                   option to encode information not only in the amplitude
                   of neuronal responses but also in the precise temporal
                   relations between the discharges of distributed
                   neurons.},
  authoraddress = {Max Planck Institute for Brain Research,
                   Deutschordenstrasse 46, 60528,Frankfurt/Main, Germany.
                   singer@mpih-frankfurt.mpg.de},
  keywords = {Acoustic Stimulation ; Animals ; Excitatory
                   Postsynaptic Potentials ; Humans ; Nerve
                   Net/*physiology ; Neurons/*physiology ; Psychophysics ;
                   Signal Transduction/physiology ; Synaptic
                   Transmission/*physiology ; Time Factors},
  language = {eng},
  medline-aid = {S0959-4388(99)80026-9 [pii]},
  medline-da = {19990615},
  medline-dcom = {19990615},
  medline-edat = {1999/05/14},
  medline-fau = {Singer, W},
  medline-is = {0959-4388 (Print)},
  medline-jid = {9111376},
  medline-jt = {Current opinion in neurobiology.},
  medline-lr = {20051116},
  medline-mhda = {1999/05/14 00:01},
  medline-own = {NLM},
  medline-pl = {ENGLAND},
  medline-pmid = {10322191},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review},
  medline-pubm = {Print},
  medline-rf = {70},
  medline-sb = {IM},
  medline-so = {Curr Opin Neurobiol. 1999 Apr;9(2):189-94.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=10322191},
  year = 1999
}
@ARTICLE{TAV04,
  author = {Trujillo-Barreto, N. J. and Aubert-Vazquez, E. and
                   Valdes-Sosa, P. A.},
  title = {Bayesian model averaging in {EEG}/{MEG} imaging},
  journal = {NeuroImage},
  volume = {21},
  number = {4},
  pages = {1300-1319},
  abstract = {In this paper, the Bayesian Theory is used to
                   formulate the Inverse Problem (IP) of the EEG/MEG. This
                   formulation offers a comparison framework for the wide
                   range of inverse methods available and allows us to
                   address the problem of model uncertainty that arises
                   when dealing with different solutions for a single
                   data. In this case, each model is defined by the set of
                   assumptions of the inverse method used, as well as by
                   the functional dependence between the data and the
                   Primary Current Density (PCD) inside the brain. The key
                   point is that the Bayesian Theory not only provides for
                   posterior estimates of the parameters of interest (the
                   PCD) for a given model, but also gives the possibility
                   of finding posterior expected utilities unconditional
                   on the models assumed. In the present work, this is
                   achieved by considering a third level of inference that
                   has been systematically omitted by previous Bayesian
                   formulations of the IP. This level is known as Bayesian
                   model averaging (BMA). The new approach is illustrated
                   in the case of considering different anatomical
                   constraints for solving the IP of the EEG in the
                   frequency domain. This methodology allows us to address
                   two of the main problems that affect linear inverse
                   solutions (LIS): (a) the existence of ghost sources and
                   (b) the tendency to underestimate deep activity. Both
                   simulated and real experimental data are used to
                   demonstrate the capabilities of the BMA approach, and
                   some of the results are compared with the solutions
                   obtained using the popular low-resolution
                   electromagnetic tomography (LORETA) and its
                   anatomically constraint version (cLORETA).},
  authoraddress = {Cuban Neuroscience Center, Havana, Cuba.
                   trujillo@cneuro.edu.cu},
  keywords = {Artifacts ; *Bayes Theorem ; Brain/*physiology ; Brain
                   Mapping ; Data Collection/statistics & numerical data
                   ; Dominance, Cerebral/physiology ;
                   Electroencephalography/*statistics & numerical data ;
                   Evoked Potentials, Auditory/physiology ; Human ; Image
                   Processing, Computer-Assisted/*statistics & numerical
                   data ; Imaging, Three-Dimensional/*statistics &
                   numerical data ; Linear Models ; Magnetic Resonance
                   Imaging ; Magnetoencephalography/*statistics &
                   numerical data ; Mathematical Computing ; Models,
                   Neurological ; Nerve Net/physiology ; Occipital
                   Lobe/physiology ; Reproducibility of Results ; *Signal
                   Processing, Computer-Assisted ; Thalamus/physiology},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.11.008 [doi] ;
                   S1053811903007286 [pii]},
  medline-da = {20040330},
  medline-dcom = {20040806},
  medline-edat = {2004/03/31 05:00},
  medline-fau = {Trujillo-Barreto, Nelson J ; Aubert-Vazquez, Eduardo ;
                   Valdes-Sosa, Pedro A},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/08/07 05:00},
  medline-own = {NLM},
  medline-phst = {2003/06/10 [received] ; 2003/11/03 [revised] ;
                   2003/11/04 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15050557},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Apr;21(4):1300-19.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15050557},
  year = 2004
}
@ARTICLE{TBS+93,
  author = {Towle, V. L. and Bolanos, J. and Suarez, D. and Tan,
                   K. and Grzeszczuk, R. and Levin, D. N. and Cakmur, R.
                   and Frank, S. A. and Spire, J. P.},
  title = {The spatial location of {EEG} electrodes: locating the
                   best-fitting sphere relative to cortical anatomy},
  journal = {Electroencephalogr Clin Neurophysiol},
  volume = {86},
  number = {1},
  pages = {1-6},
  abstract = {The location of the international 10-20 system
                   electrode positions and 14 fiducial landmarks are
                   described in cartesian coordinates (+/- 1.4 mm average
                   accuracy). Six replications were obtained on 3 separate
                   days from 4 normal subjects, who were compared to each
                   other with a best-fit sphere algorithm. Test-retest
                   reliability depended on the electrode position: the
                   parasagittal electrodes were associated with greater
                   measurement errors (maximum 7 mm) than midline
                   locations. Location variability due to head shape was
                   greatest in the temporal region, averaging 5 mm from
                   the mean. For each subject's electrode locations a
                   best-fitting sphere was determined (79-87 mm radius,
                   6\% average error). A surface-fitting algorithm was
                   used to transfer the electrode locations and
                   best-fitting sphere to MR images of the brain and
                   scalp. The center of the best-fitting sphere coincided
                   with the floor of the third ventricle 5 mm anterior to
                   the posterior commissure. The melding of EEG electrode
                   location information with brain anatomy provides an
                   empirical basis for associating hypothetical equivalent
                   dipole locations with their anatomical substrates.},
  authoraddress = {Department of Neurology, University of Chicago, IL
                   60637.},
  keywords = {Adult ; Brain/*anatomy & histology/physiology ; Brain
                   Mapping ; Electrodes ;
                   Electroencephalography/*instrumentation ; Evoked
                   Potentials, Visual/physiology ; Female ; Human ;
                   Magnetic Resonance Imaging ; Male ; Photic Stimulation},
  language = {eng},
  medline-da = {19930218},
  medline-dcom = {19930218},
  medline-edat = {1993/01/01},
  medline-fau = {Towle, V L ; Bolanos, J ; Suarez, D ; Tan, K ;
                   Grzeszczuk, R ; Levin, D N ; Cakmur, R ; Frank, S A ;
                   Spire, J P},
  medline-is = {0013-4694},
  medline-jid = {0375035},
  medline-lr = {20001218},
  medline-mhda = {1993/01/01 00:01},
  medline-own = {NLM},
  medline-pl = {IRELAND},
  medline-pmid = {7678386},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Electroencephalogr Clin Neurophysiol 1993
                   Jan;86(1):1-6.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=7678386},
  year = 1993
}
@ARTICLE{TBT+03-a,
  author = {Thees, S. and Blankenburg, F. and Taskin, B. and
                   Curio, G. and Villringer, A.},
  title = {Dipole source localization and f{MRI} of
                   simultaneously recorded data applied to somatosensory
                   categorization},
  journal = {NeuroImage},
  volume = {18},
  number = {3},
  pages = {707-719},
  abstract = {In this study, the feasibility of dipole source
                   localization (DSL) and coregistration with functional
                   magnetic resonance imaging (fMRI) activation patterns
                   on the basis of simultaneously acquired data is
                   demonstrated. Brain activity was mapped during the
                   performance of a somatosensory single reaction and a
                   choice reaction task at high spatiotemporal resolution
                   in six healthy subjects. The choice reaction task
                   required a categorization of two different stimulus
                   intensities, whereas for the single reaction task
                   merely the perception of a tactile stimulus had to be
                   confirmed by the subjects. An offline artifact
                   correction algorithm was applied to 32-channel EEG data
                   that were acquired between subsequent MRI scans. Using
                   a multiple dipole approach, five distinct dipole
                   sources were identified within areas of the
                   somatosensory system. Coregistration of fMRI and DSL
                   showed consistent spatial activation patterns with a
                   mean distance of 9.2 +/- 6.8 mm between dipole sources
                   and fMRI activation maxima. However, since the number
                   of fMRI activation sites exceeded the number of
                   cerebral dipole sources, it was not possible to assign
                   a dipole source to each fMRI activation site. Dipole
                   moment time courses were consistent with previously
                   reported results of similar experiments. A comparison
                   of brain activation patterns during the two tasks with
                   both fMRI and DSL indicated an involvement of the
                   contralateral secondary somatosensory cortex in
                   somatosensory categorization.},
  authoraddress = {Department of Neurology, Charite University Hospital,
                   Humboldt-University, Berlin, Germany.
                   sebastian.thees@charite.de},
  keywords = {Adult ; Artifacts ; Attention/*physiology ; Brain
                   Mapping/methods ; Choice Behavior/*physiology ;
                   Dominance, Cerebral/physiology ;
                   Electroencephalography/*methods ; Evoked Potentials,
                   Somatosensory/physiology ; Female ; Human ; Image
                   Processing, Computer-Assisted/*methods ; Imaging,
                   Three-Dimensional/*methods ; Magnetic Resonance
                   Imaging/*methods ; Male ; Median Nerve/physiology ;
                   Motor Neurons/physiology ; Oxygen
                   Consumption/physiology ; Parietal Lobe/*physiology ;
                   Reaction Time/*physiology ; Sensory Thresholds ;
                   Somatosensory Cortex/*physiology ; Support, Non-U.S.
                   Gov't ; Touch/*physiology},
  language = {eng},
  medline-aid = {S105381190200054X [pii]},
  medline-da = {20030401},
  medline-dcom = {20030519},
  medline-edat = {2003/04/02 05:00},
  medline-fau = {Thees, S ; Blankenburg, F ; Taskin, B ; Curio, G ;
                   Villringer, A},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2003/05/20 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12667848},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2003 Mar;18(3):707-19.},
  medline-stat = {completed},
  year = 2003
}
@ARTICLE{TFG06,
  author = {Thomason, M. E. and Foland, L. C. and Glover, G. H.},
  title = {Calibration of {BOLD} f{MRI} using breath holding
                   reduces group variance during a cognitive task.},
  journal = {Hum Brain Mapp},
  abstract = {The proportionality of blood oxygen level-dependent
                   (BOLD) response during a cognitive task and that from a
                   hypercapnic challenge was investigated in cortical
                   structures involved in working memory (WM). Breath
                   holding (BH) following inspiration was used to induce a
                   BOLD response characteristic of regional vasomotor
                   reactivity but devoid of metabolic changes. BOLD
                   effects measured during BH were used to normalize
                   individual subject activations during WM, which
                   effectively reduced the confounding influence of
                   individual- and region-specific differences in
                   hemodynamic responsivity common to both tasks. In a
                   study of seven subjects, the BH calibration reduced
                   intersubject variability in WM effect amplitude by
                   24.8% (P < 0.03). Reduced intersubject variability
                   resulted in a 23.7% increase in group WM activation
                   voxel extent significant at P < 0.001, with further
                   increases at more stringent thresholds. Because the BH
                   task does not require CO(2) inhalation or other
                   invasive manipulations and is broadly applicable across
                   cortical regions, the proposed approach is simple to
                   implement and may be beneficial for use not only in
                   quantitative group fMRI analyses, but also for
                   multicenter and longitudinal studies. Hum Brain Mapp,
                   2006. (c) 2006 Wiley-Liss, Inc.},
  authoraddress = {Neurosciences Program, Stanford University School of
                   Medicine, Stanford, California.},
  language = {ENG},
  medline-aid = {10.1002/hbm.20241 [doi]},
  medline-da = {20060615},
  medline-dep = {20060502},
  medline-edat = {2006/05/04 09:00},
  medline-is = {1065-9471 (Print)},
  medline-jid = {9419065},
  medline-mhda = {2006/05/04 09:00},
  medline-own = {NLM},
  medline-pmid = {16671081},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Hum Brain Mapp. 2006 May 2;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16671081},
  year = 2006
}
@ARTICLE{TPB+05,
  author = {Torquati, K. and Pizzella, V. and Babiloni, C. and Del
                   Gratta, C. and Della Penna, S. and Ferretti, A. and
                   Franciotti, R. and Rossini, P. M. and Romani, G. L.},
  title = {Nociceptive and non-nociceptive sub-regions in the
                   human secondary somatosensory cortex: an {MEG} study
                   using f{MRI} constraints.},
  journal = {Neuroimage},
  volume = {26},
  number = {1},
  pages = {48-56},
  abstract = {Previous evidence from functional magnetic resonance
                   imaging (fMRI) has shown that a painful galvanic
                   stimulation mainly activates a posterior sub-region in
                   the secondary somatosensory cortex (SII), whereas a
                   non-painful sensory stimulation mainly activates an
                   anterior sub-region of SII [Ferretti, A., Babiloni, C.,
                   Del Gratta, C., Caulo, M., Tartaro, A., Bonomo, L.,
                   Rossini, P.M., Romani, G.L., 2003. Functional
                   topography of the secondary somatosensory cortex for
                   non-painful and painful stimuli: an fMRI study.
                   Neuroimage 20 (3), 1625-1638.]. The present study,
                   combining fMRI with magnetoencephalographic (MEG)
                   findings, assessed the working hypothesis that the
                   activity of such a posterior SII sub-region is
                   characterized by an amplitude and temporal evolution in
                   line with the bilateral functional organization of
                   nociceptive systems. Somatosensory evoked magnetic
                   fields (SEFs) recordings after alvanic median nerve
                   stimulation were obtained from the same sample of
                   subjects previously examined with fMRI [Ferretti, A.,
                   Babiloni, C., Del Gratta, C., Caulo, M., Tartaro, A.,
                   Bonomo, L., Rossini, P.M., Romani, G.L., 2003.
                   Functional topography of the secondary somatosensory
                   cortex for non-painful and painful stimuli: an fMRI
                   study. Neuroimage 20 (3), 1625-1638.]. Constraints for
                   dipole source localizations obtained from MEG
                   recordings were applied according to fMRI activations,
                   namely, at the posterior and the anterior SII
                   sub-regions. It was shown that, after painful
                   stimulation, the two posterior SII sub-regions of the
                   contralateral and ipsilateral hemispheres were
                   characterized by dipole sources with similar amplitudes
                   and latencies. In contrast, the activity of anterior
                   SII sub-regions showed statistically significant
                   differences in amplitude and latency during both
                   non-painful and painful stimulation conditions. In the
                   contralateral hemisphere, the source activity was
                   greater in amplitude and shorter in latency with
                   respect to the ipsilateral. Finally, painful stimuli
                   evoked a response from the posterior sub-regions
                   peaking significantly earlier than from the anterior
                   sub-regions. These results suggested that both ipsi and
                   contra posterior SII sub-regions process painful
                   stimuli in parallel, while the anterior SII sub-regions
                   might play an integrative role in the processing of
                   somatosensory stimuli.},
  authoraddress = {Dipartimento di Scienze Cliniche e
                   Bioimmagini-Universita G. D'Annunzio, Chieti, Italy.
                   kathya.torquati@itab.unich.it},
  keywords = {Adult ; Electric Stimulation ; Evoked Potentials,
                   Somatosensory/physiology ; Female ; Humans ;
                   Laterality/physiology ; Magnetic Resonance Imaging ;
                   Magnetoencephalography ; Male ; Models, Neurological ;
                   Nociceptors/*physiology ; Oxygen/blood ; Pain
                   Threshold/physiology ; Research Support, Non-U.S. Gov't
                   ; Somatosensory Cortex/*physiology},
  language = {eng},
  medline-aid = {S1053-8119(05)00035-2 [pii] ;
                   10.1016/j.neuroimage.2005.01.012 [doi]},
  medline-da = {20050502},
  medline-dcom = {20050712},
  medline-dep = {20050225},
  medline-edat = {2005/05/03 09:00},
  medline-fau = {Torquati, K ; Pizzella, V ; Babiloni, C ; Del Gratta,
                   C ; Della Penna, S ; Ferretti, A ; Franciotti, R ;
                   Rossini, P M ; Romani, G L},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2005/07/13 09:00},
  medline-own = {NLM},
  medline-phst = {2004/06/14 [received] ; 2004/12/15 [revised] ;
                   2005/01/11 [accepted] ; 2005/02/25 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {15862204},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-pubm = {Print-Electronic},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2005 May 15;26(1):48-56. Epub 2005 Feb 25.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15862204},
  year = 2005
}
@ARTICLE{TVK06,
  author = {Tuunanen, P. I. and Vidyasagar, R. and Kauppinen, R.
                   A.},
  title = {Effects of mild hypoxic hypoxia on poststimulus
                   undershoot of blood-oxygenation-level-dependent f{MRI}
                   signal in the human visual cortex.},
  journal = {Magn Reson Imaging},
  volume = {24},
  number = {8},
  pages = {993-9},
  abstract = {Characteristics of the
                   blood-oxygenation-level-dependent (BOLD) functional
                   magnetic resonance imaging (fMRI) signal poststimulus
                   undershoot in the visual cortex were studied at varying
                   levels of arterial blood oxygen saturation (Y(sat)).
                   Undershoot with an amplitude of -0.6+/-0.2% appeared
                   after positive BOLD response (+1.7+/-0.5%) under
                   control conditions. Cerebral blood volume (CBV), as
                   determined with vascular-space-occupancy-dependent
                   fMRI, increased by 26-43% during the positive BOLD
                   peak, but the CBV proceeded at baseline level during
                   the BOLD poststimulus undershoot. Mild hypoxic hypoxia
                   (Y(sat) ranging from 0.82 to 0.89) had no effect on the
                   amplitude or duration of poststimulus undershoot in
                   activated BOLD pixels. Hypoxia did not influence CBV
                   during the BOLD poststimulus undershoot. In contrast,
                   the positive BOLD signal at the level of all activated
                   pixels was smaller in hypoxia than in normoxia. The
                   present results show that the BOLD poststimulus
                   undershoot is not influenced by curtailed oxygen
                   availability and that, during the undershoot, CBV is
                   not different from resting state.},
  authoraddress = {Faculty of Life Sciences, The University of
                   Manchester, Manchester M13 9PT, UK; Department of
                   Biomedical NMR, A.I. Virtanen Institute, University of
                   Kuopio, FIN-70211 Kuopio, Finland.},
  language = {eng},
  medline-aid = {S0730-725X(06)00145-7 [pii] ;
                   10.1016/j.mri.2006.04.017 [doi]},
  medline-da = {20060925},
  medline-dep = {20060606},
  medline-edat = {2006/09/26 09:00},
  medline-fau = {Tuunanen, Pasi I ; Vidyasagar, Rishma ; Kauppinen,
                   Risto A},
  medline-is = {0730-725X (Print)},
  medline-jid = {8214883},
  medline-jt = {Magnetic resonance imaging.},
  medline-mhda = {2006/09/26 09:00},
  medline-own = {NLM},
  medline-phst = {2006/01/14 [received] ; 2006/04/20 [accepted] ;
                   2006/06/06 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16997068},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Magn Reson Imaging. 2006 Oct;24(8):993-9. Epub 2006
                   Jun 6.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16997068},
  year = 2006
}
@ARTICLE{TWD+01,
  author = {Tuch, D. S. and Wedeen, V. J. and Dale, A. M. and
                   George, J.S. and Belliveau, J. W.},
  title = {Conductivity tensor mapping of the human brain using
                   diffusion tensor {MRI}},
  journal = {Proc Natl Acad Sci U S A},
  volume = {98},
  number = {20},
  pages = {11697-11701},
  abstract = {Knowledge of the electrical conductivity properties of
                   excitable tissues is essential for relating the
                   electromagnetic fields generated by the tissue to the
                   underlying electrophysiological currents. Efforts to
                   characterize these endogenous currents from
                   measurements of the associated electromagnetic fields
                   would significantly benefit from the ability to measure
                   the electrical conductivity properties of the tissue
                   noninvasively. Here, using an effective medium
                   approach, we show how the electrical conductivity
                   tensor of tissue can be quantitatively inferred from
                   the water self-diffusion tensor as measured by
                   diffusion tensor magnetic resonance imaging. The
                   effective medium model indicates a strong linear
                   relationship between the conductivity and diffusion
                   tensor eigenvalues (respectively, final sigma and d) in
                   agreement with theoretical bounds and experimental
                   measurements presented here (final sigma/d
                   approximately 0.844 +/- 0.0545 S small middle
                   dots/mm(3), r(2) = 0.945). The extension to other
                   biological transport phenomena is also discussed.},
  authoraddress = {Massachusetts General Hospital, NMR Center, 149 13th
                   Street, Charlestown, MA 02129, USA. dtuch@mit.edu},
  keywords = {Brain/*anatomy & histology/physiology ; *Brain
                   Mapping/instrumentation/methods ; Diffusion ;
                   Electroencephalography ; Human ; *Magnetic Resonance
                   Imaging ; Magnetoencephalography ; Models, Neurological
                   ; Support, Non-U.S. Gov't ; Support, U.S. Gov't,
                   Non-P.H.S. ; Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {10.1073/pnas.171473898 [doi] ; 98/20/11697 [pii]},
  medline-da = {20010926},
  medline-dcom = {20011204},
  medline-edat = {2001/09/27 10:00},
  medline-fau = {Tuch, D S ; Wedeen, V J ; Dale, A M ; George, J S ;
                   Belliveau, J W},
  medline-gr = {MH 60993-04/MH/NIMH},
  medline-is = {0027-8424},
  medline-jid = {7505876},
  medline-mhda = {2002/01/05 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11573005},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Proc Natl Acad Sci U S A 2001 Sep 25;98(20):11697-701.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11573005},
  year = 2001
}
@ARTICLE{Tur02,
  author = {Turner, R.},
  title = {How much cortex can a vein drain? {D}ownstream
                   dilution of activation-related cerebral blood
                   oxygenation changes.},
  journal = {Neuroimage},
  volume = {16},
  number = {4},
  pages = {1062-7},
  abstract = {The draining vein problem is recognized as one of the
                   most severe constraints on the spatial resolution of
                   BOLD contrast fMRI, used widely in imaging
                   neuroscience. Changes in blood oxygenation arising from
                   local brain activity-related changes in blood flow
                   propagate downstream in veins and can give rise to
                   spurious activation at sites remote from neuronal
                   activity. The geometry of the venous vasculature is
                   quite regular in structure and is well depicted in
                   photomicrographs. Quantitative analysis of this
                   geometry, together with hydrodynamic considerations,
                   permit upper bounds dependent on the area of cortical
                   neuronal activity to be derived for the spatial extent
                   of draining vein contamination. It is estimated that an
                   activated cortical area of 100 mm(2) will generate an
                   oxygenation change in venous blood that extends without
                   dilution along the vein no more than 4.2 mm beyond the
                   edge of the activated area. At greater distances along
                   the draining vein this oxygenation change will be
                   diluted. The model leads to a quantitative prediction
                   of the functional form of this dilution.},
  authoraddress = {Wellcome Department of Imaging Neuroscience, Institute
                   of Neurology, 12 Queen Square, London, WC1N 3BG, United
                   Kingdom.},
  keywords = {Cerebral Cortex/*blood supply/*physiology ; Cerebral
                   Veins/*physiology ; Humans ; *Models, Cardiovascular ;
                   Oxygen/*blood ; Research Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1053811902910827 [pii]},
  medline-da = {20020830},
  medline-dcom = {20021009},
  medline-edat = {2002/08/31 10:00},
  medline-fau = {Turner, Robert},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-lr = {20041117},
  medline-mhda = {2002/10/10 04:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12202093},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-rn = {7782-44-7 (Oxygen)},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2002 Aug;16(4):1062-7.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12202093},
  year = 2002
}
@ARTICLE{UHS98,
  author = {Uutela, K. and Hamalainen, M. and Salmelin, R.},
  title = {Global optimization in the localization of
                   neuromagnetic sources},
  journal = {IEEE Trans Biomed Eng},
  volume = {45},
  number = {6},
  pages = {716-723},
  abstract = {The locations of active brain areas can be estimated
                   from the magnetic field produced by the neural current
                   sources. In many cases, the actual current distribution
                   can be modeled with a set of stationary current dipoles
                   with time-varying amplitudes. This work studies global
                   optimization methods that find the minimum of the
                   least-squares error function of the current dipole
                   estimation problem. Three different global optimization
                   methods were investigated: clustering method, simulated
                   annealing, and genetic algorithms. In simulation
                   studies, the genetic algorithm was the most effective
                   method. The methods were also applied to analysis of
                   actual measurement data.},
  authoraddress = {Low Temperature Laboratory, Helsinki University of
                   Technology, Finland. Kimmo.Uutela@hut.fi},
  keywords = {Algorithms ; Comparative Study ; Evoked Potentials,
                   Auditory ; Human ; Language Tests ; Least-Squares
                   Analysis ; Linear Models ; *Magnetoencephalography ;
                   *Models, Neurological ; Reference Values ;
                   Reproducibility of Results ; *Signal Processing,
                   Computer-Assisted ; Support, Non-U.S. Gov't ; Visual
                   Cortex/*physiology},
  language = {eng},
  medline-da = {19980616},
  medline-dcom = {19980616},
  medline-edat = {1998/06/04},
  medline-fau = {Uutela, K ; Hamalainen, M ; Salmelin, R},
  medline-is = {0018-9294},
  medline-jid = {0012737},
  medline-lr = {20001218},
  medline-mhda = {1998/06/04 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9609936},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng 1998 Jun;45(6):716-23.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9609936},
  year = 1998
}
@ARTICLE{VBP+02,
  author = {Vitacco, D. and Brandeis, D. and Pascual-Marqui, R.
                   and Martin, E.},
  title = {Correspondence of event-related potential tomography
                   and functional magnetic resonance imaging during
                   language processing},
  journal = {Hum Brain Mapp},
  volume = {17},
  number = {1},
  pages = {4-12},
  abstract = {Combining event-related potentials (ERP) and
                   functional magnetic resonance imaging (fMRI) may
                   provide sufficient temporal and spatial resolution to
                   clarify the functional connectivity of neural
                   processes, provided both methods represent the same
                   neural networks. The current study investigates the
                   statistical correspondence of ERP tomography and fMRI
                   within the common activity volume and time range in a
                   complex visual language task. The results demonstrate
                   that both methods represent similar neural networks
                   within the bilateral occipital gyrus, lingual gyrus,
                   precuneus and middle frontal gyrus, and the left
                   inferior and superior parietal lobe, middle and
                   superior temporal gyrus, cingulate gyrus, superior
                   frontal gyrus and precentral gyrus. The mean
                   correspondence of both methods over subjects was
                   significant. On an individual basis, only half of the
                   subjects showed significantly corresponding activity
                   patterns, suggesting that a one-to-one correspondence
                   between individual fMRI activation patterns and ERP
                   source tomographies integrated over microstates cannot
                   be assumed in all cases.},
  authoraddress = {University Children's Hospital Zurich, Department of
                   Magnetic Resonance, Zurich, Switzerland.},
  keywords = {Adult ; Brain/anatomy & histology/physiology ; *Brain
                   Mapping ; Cognition ; *Electroencephalography ; Evoked
                   Potentials/*physiology ; Female ; Human ; Image
                   Processing, Computer-Assisted/methods ; *Language ;
                   *Magnetic Resonance Imaging ; Male ; Nerve Net/anatomy
                   & histology/physiology ; Photic Stimulation ; Reaction
                   Time ; Reading ; Reference Values ; Support, Non-U.S.
                   Gov't ; Word Association Tests},
  language = {eng},
  medline-aid = {10.1002/hbm.10038 [doi]},
  medline-ci = {Copyright 2002 Wiley-Liss, Inc.},
  medline-da = {20020830},
  medline-dcom = {20021017},
  medline-edat = {2002/08/31 10:00},
  medline-fau = {Vitacco, Deborah ; Brandeis, Daniel ; Pascual-Marqui,
                   Roberto ; Martin, Ernst},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-mhda = {2002/10/18 04:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12203683},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 2002 Sep;17(1):4-12.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12203683},
  year = 2002
}
@ARTICLE{VCD+03,
  author = {Van Camp, N. and D'Hooge, R. and Verhoye, M. and
                   Peeters, R. R. and De Deyn, P. P. and Van der Linden,
                   A.},
  title = {Simultaneous electroencephalographic recording and
                   functional magnetic resonance imaging during
                   pentylenetetrazol-induced seizures in rat},
  journal = {NeuroImage},
  volume = {19},
  number = {3},
  pages = {627-636},
  abstract = {Truly simultaneous electroencephalogram (EEG) and
                   functional magnetic resonance imaging (fMRI) were
                   registered in curarized rats injected with convulsive
                   doses of pentylenetetrazol (PTZ, 65 mg/kg, sc).
                   Rigorous control of physiological parameters like body
                   temperature and ventilation with control of blood
                   gasses helped to avoid potential interference between
                   systemic parameters, and central PTZ-induced blood
                   oxygenation level-dependent (BOLD) changes.
                   Simultaneous EEG/fMRI recordings demonstrated
                   progressive epileptiform EEG discharges with
                   concomitant BOLD changes, the latter gradually
                   affecting most of the fore- and midbrain. Approximately
                   15 min after PTZ injection, the first BOLD contrast
                   changes mainly occurred in neocortex, and coincided
                   with the first minor EEG alterations. Most regions that
                   displayed BOLD changes were regions with reportedly
                   high GABA(A) receptor densities. Full-blown
                   epileptiform discharges occurred on the EEG tracing,
                   approximately 30 min after PTZ injection, and coincided
                   with bilateral positive and/or negative BOLD contrast
                   changes in cortical and subcortical regions. Behavioral
                   observations demonstrated the first of several
                   generalized clonic or clonic-tonic seizure episodes to
                   occur also around this time. Approximately 90 min after
                   injection, the electrographic paroxysms gradually
                   decreased in amplitude and duration, whereas the BOLD
                   signal changes still extended with alternating positive
                   and negative traces, and spread to subcortical regions
                   like caudate-putamen and globus pallidus.},
  authoraddress = {Bio Imaging Lab, RUCA, 2020 Antwerp, Belgium.},
  keywords = {Adult ; Brain Mapping ; Female ; Frontal
                   Lobe/*physiology ; Human ; Image Processing,
                   Computer-Assisted ; *Language ; Magnetic Resonance
                   Imaging ; Male ; Motion Perception/*physiology ; Motor
                   Cortex/physiology ; Parietal Lobe/anatomy &
                   histology/physiology ; Support, Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1053811903001381 [pii]},
  medline-da = {20030725},
  medline-dcom = {20030909},
  medline-edat = {2003/07/26 05:00},
  medline-fau = {Van Camp, Nadja ; D'Hooge, Rudi ; Verhoye, Marleen ;
                   Peeters, Ron R ; De Deyn, Peter P ; Van der Linden,
                   Annemie},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2003/09/10 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12880793},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2003 Jul;19(3):627-36.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12880793},
  year = 2003
}
@ARTICLE{VCG+06,
  author = {Vazquez, A. L. and Cohen, E. R. and Gulani, V. and
                   Hernandez-Garcia, L. and Zheng, Y. and Lee, G. R. and
                   Kim, S. G. and Grotberg, J. B. and Noll, D. C.},
  title = {Vascular dynamics and {BOLD} f{MRI}: {CBF} level
                   effects and analysis considerations.},
  journal = {Neuroimage},
  volume = {32},
  number = {4},
  pages = {1642-55},
  abstract = {Changes in the cerebral blood flow (CBF) baseline
                   produce significant changes to the hemodynamic
                   response. This work shows that increases in the
                   baseline blood flow level produce blood
                   oxygenation-level dependent (BOLD) and blood flow
                   responses that are slower and lower in amplitude, while
                   decreases in the baseline blood flow level produce
                   faster and higher amplitude hemodynamic responses. This
                   effect was characterized using a vascular model of the
                   hemodynamic response that separated arterial blood flow
                   response from the venous blood volume response and
                   linked the input stimulus to the vascular response. The
                   model predicted the baseline blood flow level effects
                   to be dominated by changes in the arterial vasculature.
                   Specifically, it predicted changes in the arterial
                   blood flow time constant and venous blood volume time
                   constant parameters of +294% and -24%, respectively,
                   for a 27% increase in the baseline blood flow. The
                   vascular model performance was compared to an empirical
                   model of the hemodynamic response. The vascular and
                   empirical hemodynamic models captured most of the
                   baseline blood flow level effects observed and can be
                   used to correct for these effects in fMRI data. While
                   the empirical hemodynamic model is easy to implement,
                   it did not incorporate any explicit physiological
                   information.},
  authoraddress = {Department of Biomedical Engineering, University of
                   Michigan, Ann Arbor, MI, USA.},
  language = {eng},
  medline-aid = {S1053-8119(06)00489-7 [pii] ;
                   10.1016/j.neuroimage.2006.04.195 [doi]},
  medline-da = {20060911},
  medline-dep = {20060724},
  medline-edat = {2006/07/25 09:00},
  medline-fau = {Vazquez, Alberto L ; Cohen, Eric R ; Gulani, Vikas ;
                   Hernandez-Garcia, Luis ; Zheng, Ying ; Lee, Gregory R ;
                   Kim, Seong-Gi ; Grotberg, James B ; Noll, Douglas C},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2006/07/25 09:00},
  medline-own = {NLM},
  medline-phst = {2005/07/01 [received] ; 2006/04/10 [revised] ;
                   2006/04/11 [accepted] ; 2006/07/24 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16860574},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2006 Oct 1;32(4):1642-55. Epub 2006 Jul
                   24.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16860574},
  year = 2006
}
@ARTICLE{VDW+04,
  author = {Vanni, S. and Dojat, M. and Warnking, J. and
                   Delon-Martin, C. and Segebarth, C. and Bullier, J.},
  title = {Timing of interactions across the visual field in the
                   human cortex},
  journal = {NeuroImage},
  volume = {21},
  number = {3},
  pages = {818-828},
  abstract = {While it is generally believed that interactions
                   across long distances in the visual field occur only in
                   the higher-order cortical areas, other results suggest
                   that such interactions are processed very early. In the
                   preceding paper, we identified the latencies within a
                   subset of cortical areas in the human visual system. In
                   the present study, we test in which areas and at which
                   latencies the responses to two visual patterns start
                   interacting. We used functional magnetic resonance
                   imaging directly combined with visual-evoked potential
                   source analysis. Interactions appeared first
                   anterolaterally to the retinotopic areas, at 80 ms for
                   two stimuli presented in the left lower visual quadrant
                   and at 100 ms for symmetrical stimulation of both lower
                   quadrants. In the lateral occipital-V5 region (LOV5),
                   two patterns presented simultaneously in one quadrant
                   elicited a response with shorter latency and
                   infra-linear addition of the amplitudes compared with
                   the patterns presented separately. For bilateral
                   stimulation, the timing of the LOV5 response coincided
                   with the response to contralateral stimulation alone.
                   Other visual areas showed interactions appearing later
                   than within LOV5: starting at 150 ms in V1, at 120 ms
                   in V3-V3a for the left visual hemifield stimulation and
                   at 160 ms for both visual hemifields stimulation. Our
                   data show that distinct patterns in the visual field
                   interact first in LOV5, suggesting that this region
                   must be the first to pool spatial information across
                   the whole visual field.},
  authoraddress = {Centre de Recherche Cerveau et Cognition,
                   CNRS-Universite Paul Sabatier, Toulouse, France.
                   vanni@neuro.hut.fi},
  keywords = {Adult ; Brain Mapping ; Evoked Potentials,
                   Visual/physiology ; Female ; Human ; Individuality ;
                   Laterality/physiology ; Magnetic Resonance Imaging ;
                   Male ; Middle Aged ; Models, Neurological ; Motion
                   Perception/physiology ; Photic Stimulation ;
                   Retina/physiology ; Support, Non-U.S. Gov't ; Visual
                   Cortex/*physiology ; Visual Fields/*physiology ; Visual
                   Perception/physiology},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.10.035 [doi] ;
                   S1053811903007043 [pii]},
  medline-da = {20040309},
  medline-dcom = {20040503},
  medline-edat = {2004/03/10 05:00},
  medline-fau = {Vanni, S ; Dojat, M ; Warnking, J ; Delon-Martin, C ;
                   Segebarth, C ; Bullier, J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/05/05 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Mar/12 [received] ; 2003/Oct/30 [revised] ;
                   2003/Oct/31 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15006648},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Mar;21(3):818-28.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15006648},
  year = 2004
}
@ARTICLE{VED+01,
  author = {Van Essen, D. C. and Drury, H. A. and Dickson, J. and
                   Harwell, J. and Hanlon, D. and Anderson, C. H.},
  title = {An integrated software suite for surface-based
                   analyses of cerebral cortex},
  journal = {J Am Med Inform Assoc},
  volume = {8},
  number = {5},
  pages = {443-459},
  abstract = {The authors describe and illustrate an integrated trio
                   of software programs for carrying out surface-based
                   analyses of cerebral cortex. The first component of
                   this trio, SureFit (Surface Reconstruction by Filtering
                   and Intensity Transformations), is used primarily for
                   cortical segmentation, volume visualization, surface
                   generation, and the mapping of functional neuroimaging
                   data onto surfaces. The second component, Caret
                   (Computerized Anatomical Reconstruction and Editing
                   Tool Kit), provides a wide range of surface
                   visualization and analysis options as well as
                   capabilities for surface flattening, surface-based
                   deformation, and other surface manipulations. The third
                   component, SuMS (Surface Management System), is a
                   database and associated user interface for
                   surface-related data. It provides for efficient
                   insertion, searching, and extraction of surface and
                   volume data from the database.},
  authoraddress = {Department of Anatomy and Neurobiology, Washington
                   University School of Medicine, St. Louis, Missouri
                   63110, USA. vanessen@v1.wustl.edu},
  keywords = {Anatomy, Artistic ; Anatomy, Cross-Sectional ;
                   Brain/*anatomy & histology ; Cerebral Cortex/*anatomy
                   & histology ; Databases, Factual ; Human ; *Image
                   Processing, Computer-Assisted ; Magnetic Resonance
                   Imaging ; Medical Illustration ; Neuroanatomy/methods ;
                   *Software ; Support, Non-U.S. Gov't ; Support, U.S.
                   Gov't, Non-P.H.S. ; Support, U.S. Gov't, P.H.S. ;
                   Systems Integration},
  language = {eng},
  medline-cin = {J Am Med Inform Assoc. 2001 Sep-Oct;8(5):510-1. PMID:
                   11522771},
  medline-da = {20010827},
  medline-dcom = {20011004},
  medline-edat = {2001/08/28 10:00},
  medline-fau = {Van Essen, D C ; Drury, H A ; Dickson, J ; Harwell, J
                   ; Hanlon, D ; Anderson, C H},
  medline-fir = {Van Essen, D C},
  medline-gr = {EY02091/EY/NEI ; R01 MH60974-06/MH/NIMH},
  medline-ir = {Van Essen DC},
  medline-irad = {Washington U, St Louis, MO},
  medline-is = {1067-5027},
  medline-jid = {9430800},
  medline-lr = {20020130},
  medline-mhda = {2001/10/05 10:01},
  medline-ot = {NASA Discipline Neuroscience ; Non-NASA Center},
  medline-oto = {NASA},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11522765},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM ; S},
  medline-so = {J Am Med Inform Assoc 2001 Sep-Oct;8(5):443-59.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11522765},
  year = 2001
}
@ARTICLE{VFS+00,
  author = {Veltman, D. J. and Friston, K. J. and Sanders, G. and
                   Price, C. J.},
  title = {Regionally specific sensitivity differences in f{MRI}
                   and {PET}: where do they come from?},
  journal = {NeuroImage},
  volume = {11},
  number = {6.1},
  pages = {575-588},
  abstract = {In this paper we report three neuroimaging studies of
                   language that investigate potential sources of
                   inconsistency in measured hemodynamic responses: (1)
                   between sessions for fMRI, including differences in
                   hormonal status, (2) between sessions for PET, and (3)
                   between scanning modalities (PET and fMRI). Differences
                   in evoked responses between sessions of the same
                   modality were small. In particular we did not find any
                   effect of hormone levels when testing during the first
                   and third weeks of the menstrual cycle (although we
                   cannot exclude the possibility that activation in the
                   temporoparietal regions is sensitive to hormonal
                   status). Comparing the two modalities showed that
                   prefrontal regions were more activated in fMRI than in
                   PET. This may relate to task switching between blocks
                   in fMRI that is not induced by PET paradigms or
                   increased error variance in these regions for PET. In
                   contrast, temporal activations were found in PET more
                   than in fMRI. We attribute the lack of temporal
                   activations, in fMRI, to a combination of factors,
                   including susceptibility artifacts, anticipatory
                   activity during the control condition, discontinuous
                   sampling of peristimulus time, and differences in the
                   source, acquisition, and analysis of the measured
                   signals. It is concluded that although there is
                   sufficient reproducibility of results for these
                   paradigms within each modality, the regionally specific
                   differences in sensitivity found between modalities
                   warrant further investigation. These regionally
                   specific differences are important for a properly
                   qualified interpretation of activation profiles in
                   fMRI.},
  authoraddress = {Department of Psychiatry and Department of Nuclear
                   Medicine, Vrje Universiteit, Amsterdam, The
                   Netherlands.},
  keywords = {Adult ; Brain/*anatomy &
                   histology/physiology/*radionuclide imaging ; Brain
                   Mapping ; Cerebrovascular Circulation ; Comparative
                   Study ; Female ; Hemodynamic Processes/physiology ;
                   Human ; *Magnetic Resonance Imaging ; Male ; Menstrual
                   Cycle/physiology ; Prefrontal Cortex/anatomy &
                   histology/physiology/radionuclide imaging ; Reading ;
                   Sensitivity and Specificity ; Speech/physiology ;
                   Support, Non-U.S. Gov't ; Temporal Lobe/anatomy &
                   histology/physiology/radionuclide imaging ;
                   *Tomography, Emission-Computed},
  language = {eng},
  medline-aid = {10.1006/nimg.2000.0581 [doi] ; S1053811900905810 [pii]},
  medline-ci = {Copyright 2000 Academic Press.},
  medline-da = {20000823},
  medline-dcom = {20000823},
  medline-edat = {2000/06/22 10:00},
  medline-fau = {Veltman, D J ; Friston, K J ; Sanders, G ; Price, C J},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-lr = {20031114},
  medline-mhda = {2000/08/29 11:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {10860787},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2000 Jun;11(6 Pt 1):575-88.},
  medline-stat = {completed},
  year = 2000
}
@ARTICLE{VR01,
  author = {Vrba, J. and Robinson, S. E.},
  title = {Signal processing in magnetoencephalography},
  journal = {Methods},
  volume = {25},
  number = {2},
  pages = {249-271},
  abstract = {The subject of this article is detection of brain
                   magnetic fields, or magnetoencephalography (MEG). The
                   brain fields are many orders of magnitude smaller than
                   the environmental magnetic noise and their measurement
                   represent a significant metrological challenge. The
                   only detectors capable of resolving such small fields
                   and at the same time handling the large dynamic range
                   of the environmental noise are superconducting quantum
                   interference devices (or SQUIDs). The SQUIDs are
                   coupled to the brain magnetic fields using combinations
                   of superconducting coils called flux transformers
                   (primary sensors). The environmental noise is
                   attenuated by a combination of shielding, primary
                   sensor geometry, and synthetic methods. One of the most
                   successful synthetic methods for noise elimination is
                   synthetic higher-order gradiometers. How the
                   gradiometers can be synthesized is shown and examples
                   of their noise cancellation effectiveness are given.
                   The MEG signals measured on the scalp surface must be
                   interpreted and converted into information about the
                   distribution of currents within the brain. This task is
                   complicated by the fact that such inversion is
                   nonunique. Additional mathematical simplifications,
                   constraints, or assumptions must be employed to obtain
                   useful source images. Methods for the interpretation of
                   the MEG signals include the popular point current
                   dipole, minimum norm methods, spatial filtering,
                   beamformers, MUSIC, and Bayesian techniques. The use of
                   synthetic aperture magnetometry (a class of
                   beamformers) is illustrated in examples of interictal
                   epileptic spiking and voluntary hand-motor activity.},
  authoraddress = {CTF Systems Inc., A subsidiary of VSM MedTech Ltd.,
                   15-1750 McLean Avenue, British Columbia V3C 1M9, Port
                   Coquitlam, Canada.},
  keywords = {Brain/pathology ; Electromagnetic Fields ; Human ;
                   Image Processing, Computer-Assisted ;
                   Magnetoencephalography/instrumentation/*methods ;
                   Models, Theoretical ; Software},
  language = {eng},
  medline-aid = {10.1006/meth.2001.1238 [doi] ; S1046202301912381 [pii]},
  medline-ci = {Copyright 2001 Elsevier Science.},
  medline-da = {20020128},
  medline-dcom = {20020528},
  medline-edat = {2002/01/29 10:00},
  medline-fau = {Vrba, J ; Robinson, S E},
  medline-is = {1046-2023},
  medline-jid = {9426302},
  medline-mhda = {2002/05/29 10:01},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {11812209},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {59},
  medline-sb = {IM},
  medline-so = {Methods 2001 Oct;25(2):249-71.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=11812209},
  year = 2001
}
@ARTICLE{VTB+03,
  author = {Vanhatalo, S. and Tallgren, P. and Becker, C. and
                   Holmes, M. D. and Miller, J. W. and Kaila, K. and
                   Voipio, J.},
  title = {Scalp-recorded slow {EEG} responses generated in
                   response to hemodynamic changes in the human brain},
  journal = {Clin Neurophysiol},
  volume = {114},
  number = {9},
  pages = {1744-1754},
  abstract = {OBJECTIVE: To study whether hemodynamic changes in
                   human brain generate scalp-EEG responses. METHODS:
                   Direct current EEG (DC-EEG) was recorded from 12
                   subjects during 5 non-invasive manipulations that
                   affect intracranial hemodynamics by different
                   mechanisms: bilateral jugular vein compression (JVC),
                   head-up tilt (HUT), head-down tilt (HDT), Valsalva
                   maneuver (VM), and Mueller maneuver (MM). DC shifts
                   were compared to changes in cerebral blood volume (CBV)
                   measured by near-infrared spectroscopy (NIRS). RESULTS:
                   DC shifts were observed during all manipulations with
                   highest amplitudes (up to 250 microV) at the midline
                   electrodes, and the most pronounced changes (up to 15
                   microV/cm) in the DC voltage gradient around vertex. In
                   spite of inter-individual variation in both amplitude
                   and polarity, the DC shifts were consistent and
                   reproducible for each subject and they showed a clear
                   temporal correlation with changes in CBV. CONCLUSIONS:
                   Our results indicate that hemodynamic changes in human
                   brain are associated with marked DC shifts that cannot
                   be accounted for by intracortical neuronal or glial
                   currents. Instead, the data are consistent with a
                   non-neuronal generator mechanism that is associated
                   with the blood-brain barrier. SIGNIFICANCE: These
                   findings have direct implications for mechanistic
                   interpretation of slow EEG responses in various
                   experimental paradigms.},
  authoraddress = {Department of Biosciences, University of Helsinki,
                   Helsinki, Finland. sampsa.vanhatalo@helsinki.fi},
  keywords = {Adult ; Brain/*physiology ; Brain Mapping ;
                   Cerebrovascular Circulation/*physiology ; Comparative
                   Study ; Electrodes ; *Electroencephalography ; Female ;
                   Head/physiology ; Hemodynamic Processes/*physiology ;
                   Human ; Jugular Veins/physiology ; Laterality ; Male ;
                   Posture/physiology ; Scalp ; Spectroscopy,
                   Near-Infrared/instrumentation/methods ; Support,
                   Non-U.S. Gov't},
  language = {eng},
  medline-aid = {S1388245703001639 [pii]},
  medline-da = {20030901},
  medline-dcom = {20031104},
  medline-edat = {2003/09/02 05:00},
  medline-fau = {Vanhatalo, S ; Tallgren, P ; Becker, C ; Holmes, M D ;
                   Miller, J W ; Kaila, K ; Voipio, J},
  medline-is = {1388-2457},
  medline-jid = {100883319},
  medline-lr = {20031114},
  medline-mhda = {2003/11/05 05:00},
  medline-own = {NLM},
  medline-pl = {Netherlands},
  medline-pmid = {12948805},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Clin Neurophysiol 2003 Sep;114(9):1744-54.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12948805},
  year = 2003
}
@ARTICLE{VVvD+97,
  author = {Van Veen, B. D. and van Drongelen, W. and Yuchtman, M.
                   and Suzuki, A.},
  title = {Localization of brain electrical activity via linearly
                   constrained minimum variance spatial filtering},
  journal = {IEEE Trans Biomed Eng},
  volume = {44},
  number = {9},
  pages = {867-880},
  abstract = {A spatial filtering method for localizing sources of
                   brain electrical activity from surface recordings is
                   described and analyzed. The spatial filters are
                   implemented as a weighted sum of the data recorded at
                   different sites. The weights are chosen to minimize the
                   filter output power subject to a linear constraint. The
                   linear constraint forces the filter to pass brain
                   electrical activity from a specified location, while
                   the power minimization attenuates activity originating
                   at other locations. The estimated output power as a
                   function of location is normalized by the estimated
                   noise power as a function of location to obtain a
                   neural activity index map. Locations of source activity
                   correspond to maxima in the neural activity index map.
                   The method does not require any prior assumptions about
                   the number of active sources of their geometry because
                   it exploits the spatial covariance of the source
                   electrical activity. This paper presents a development
                   and analysis of the method and explores its sensitivity
                   to deviations between actual and assumed data models.
                   The effect on the algorithm of covariance matrix
                   estimation, correlation between sources, and choice of
                   reference is discussed. Simulated and measured data is
                   used to illustrate the efficacy of the approach.},
  authoraddress = {Department of Electrical and Computer Engineering,
                   University of Wisconsin, Madison 53706, USA.
                   vanveen@engr.wisc.edu},
  keywords = {Algorithms ; Craniotomy ; Electrodes, Implanted ;
                   *Electroencephalography ; Human ; Intraoperative Period
                   ; Linear Models ; Models, Neurological ; Sensitivity
                   and Specificity ; *Signal Processing, Computer-Assisted},
  language = {eng},
  medline-da = {19970916},
  medline-dcom = {19970916},
  medline-edat = {1997/09/01},
  medline-fau = {Van Veen, B D ; van Drongelen, W ; Yuchtman, M ;
                   Suzuki, A},
  medline-is = {0018-9294},
  medline-jid = {0012737},
  medline-lr = {20001218},
  medline-mhda = {1997/09/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {9282479},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {IEEE Trans Biomed Eng 1997 Sep;44(9):867-80.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=9282479},
  year = 1997
}
@ARTICLE{VWD+04,
  author = {Vanni, S. and Warnking, J. and Dojat, M. and
                   Delon-Martin, C. and Bullier, J. and Segebarth, C.},
  title = {Sequence of pattern onset responses in the human
                   visual areas: an f{MRI} constrained {VEP} source
                   analysis},
  journal = {NeuroImage},
  volume = {21},
  number = {3},
  pages = {801-817},
  abstract = {We measured the timing of activity in distinct
                   functional areas of the human visual cortex after onset
                   of a visual pattern. This is not possible with visual
                   evoked potentials (VEPs) or magnetic fields alone, and
                   direct combination of functional magnetic resonance
                   imaging (fMRI) with electromagnetic data has turned out
                   to be difficult. We tested a relatively new approach,
                   where both position and orientation of the active
                   cortex was given to the VEP source model. Subjects saw
                   the same visual patterns flashed ON and OFF, both when
                   recording VEPs and fMRI responses. We identified the
                   positions and orientations of the activated cortex in
                   four retinotopic areas in each individual, and the
                   corresponding dipoles were seeded to model the
                   individual evoked potential data. Unexplained variance,
                   comprising signals from other areas, was inversely
                   modeled. Despite the partially a priori fixed model and
                   optimized signal-to-noise ratio of VEP data, full
                   separation of retinotopic areas was only seldom
                   possible due to crosstalk between the adjacent sources,
                   but separation was usually possible between areas V1
                   and V3/V3a. Whereas the latencies generally followed
                   the hierarchical organization of cortical areas
                   (V1-V2-V3), with around 25 ms between the strongest
                   responses, an early activation emerged 10-20 ms after
                   V1, close to the temporo-occipital junction (LO/V5) and
                   with an additional 20-ms latency in the corresponding
                   region of the opposite hemisphere. Our approach shows
                   that it is feasible to directly seed information from
                   fMRI to electromagnetic source models and to identify
                   the components and dynamics of VEPs in different
                   retinotopic areas of a human individual.},
  authoraddress = {Centre de Recherche Cerveau et Cognition,
                   CNRS-Universite Paul Sabatier, Toulouse, France.
                   vanni@neuro.hut.fi},
  keywords = {Adult ; Brain Mapping ; Electroencephalography ;
                   Evoked Potentials, Visual/*physiology ; Female ; Human
                   ; Individuality ; Magnetic Resonance Imaging ; Male ;
                   Middle Aged ; Models, Neurological ; Occipital
                   Lobe/physiology ; Photic Stimulation ;
                   Retina/physiology ; Support, Non-U.S. Gov't ; Visual
                   Cortex/*physiology ; Visual Fields/physiology ; Visual
                   Pathways/physiology},
  language = {eng},
  medline-aid = {10.1016/j.neuroimage.2003.10.047 [doi] ;
                   S1053811903007055 [pii]},
  medline-da = {20040309},
  medline-dcom = {20040503},
  medline-edat = {2004/03/10 05:00},
  medline-fau = {Vanni, S ; Warnking, J ; Dojat, M ; Delon-Martin, C ;
                   Bullier, J ; Segebarth, C},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/05/05 05:00},
  medline-own = {NLM},
  medline-phst = {2003/Mar/12 [received] ; 2003/Oct/30 [revised] ;
                   2003/Oct/31 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15006647},
  medline-pst = {ppublish},
  medline-pt = {Clinical Trial ; Journal Article},
  medline-sb = {IM},
  medline-so = {NeuroImage 2004 Mar;21(3):801-17.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15006647},
  year = 2004
}
@ARTICLE{WAT+05,
  author = {Wolters, C.H. and Anwander, A. and Tricoche, X. and
                   Weinstein, D. and Koch, M.A. and Macleod, R.S.},
  title = {Influence of tissue conductivity anisotropy on
                   {EEG}/{MEG} field and return current computation in a
                   realistic head model: {A} simulation and visualization
                   study using high-resolution finite element modeling.},
  journal = {Neuroimage},
  abstract = {To achieve a deeper understanding of the brain,
                   scientists, and clinicians use electroencephalography
                   (EEG) and magnetoencephalography (MEG) inverse methods
                   to reconstruct sources in the cortical sheet of the
                   human brain. The influence of structural and electrical
                   anisotropy in both the skull and the white matter on
                   the EEG and MEG source reconstruction is not well
                   understood. In this paper, we report on a study of the
                   sensitivity to tissue anisotropy of the EEG/MEG forward
                   problem for deep and superficial neocortical sources
                   with differing orientation components in an
                   anatomically accurate model of the human head. The goal
                   of the study was to gain insight into the effect of
                   anisotropy of skull and white matter conductivity
                   through the visualization of field distributions,
                   isopotential surfaces, and return current flow and
                   through statistical error measures. One implicit
                   premise of the study is that factors that affect the
                   accuracy of the forward solution will have at least as
                   strong an influence over solutions to the associated
                   inverse problem. Major findings of the study include
                   (1) anisotropic white matter conductivity causes return
                   currents to flow in directions parallel to the white
                   matter fiber tracts; (2) skull anisotropy has a
                   smearing effect on the forward potential computation;
                   and (3) the deeper a source lies and the more it is
                   surrounded by anisotropic tissue, the larger the
                   influence of this anisotropy on the resulting electric
                   and magnetic fields. Therefore, for the EEG, the
                   presence of tissue anisotropy both for the skull and
                   white matter compartment substantially compromises the
                   forward potential computation and as a consequence, the
                   inverse source reconstruction. In contrast, for the
                   MEG, only the anisotropy of the white matter
                   compartment has a significant effect. Finally, return
                   currents with high amplitudes were found in the highly
                   conducting cerebrospinal fluid compartment,
                   underscoring the need for accurate modeling of this
                   space.},
  authoraddress = {Westfalische Wilhelms-Universitat Munster, Institut
                   fur Biomagnetismus und Biosignalanalyse, Malmedyweg 15,
                   48149 Munster, Germany; University of Utah, Scientific
                   Computing and Imaging Institute, 50 S. Central Campus
                   Dr., Room 3493, Salt Lake City, UT 84112, USA.},
  language = {ENG},
  medline-aid = {S1053-8119(05)00787-1 [pii] ;
                   10.1016/j.neuroimage.2005.10.014 [doi]},
  medline-da = {20051220},
  medline-dep = {20051215},
  medline-edat = {2005/12/21 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2005/12/21 09:00},
  medline-own = {NLM},
  medline-phst = {2005/07/15 [received] ; 2005/09/15 [revised] ;
                   2005/10/05 [accepted]},
  medline-pmid = {16364662},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2005 Dec 15;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16364662},
  year = 2005
}
@ARTICLE{WGW93,
  author = {Wikswo, Jr, J. P. and Gevins, A. and Williamson, S. J.},
  title = {The future of the {EEG} and {MEG}},
  journal = {Electroencephalogr Clin Neurophysiol},
  volume = {87},
  number = {1},
  pages = {1-9},
  authoraddress = {Department of Physics and Astronomy, Vanderbilt
                   University, Nashville, TN 37235.},
  keywords = {Animals ; Comparative Study ;
                   Electroencephalography/*trends ; Forecasting ; Human ;
                   Magnetic Resonance Imaging ;
                   Magnetoencephalography/*trends ; Sensitivity and
                   Specificity ; Support, U.S. Gov't, Non-P.H.S. ;
                   Tomography, Emission-Computed ; Tomography,
                   Emission-Computed, Single-Photon},
  language = {eng},
  medline-da = {19930830},
  medline-dcom = {19930830},
  medline-edat = {1993/07/01},
  medline-fau = {Wikswo, J P Jr ; Gevins, A ; Williamson, S J},
  medline-is = {0013-4694},
  medline-jid = {0375035},
  medline-lr = {20031114},
  medline-mhda = {2001/03/28 10:01},
  medline-own = {NLM},
  medline-pl = {IRELAND},
  medline-pmid = {7687949},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {55},
  medline-sb = {IM},
  medline-so = {Electroencephalogr Clin Neurophysiol 1993
                   Jul;87(1):1-9.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=7687949},
  year = 1993
}
@ARTICLE{WIS+96,
  author = {Warach, S. and Ives, J. R. and Schlaug, G. and Patel,
                   M. R. and Darby, D. G. and Thangaraj, V. and Edelman,
                   R. R. and Schomer, D. L.},
  title = {E{EG}-triggered echo-planar functional {MRI} in
                   epilepsy},
  journal = {Neurology},
  volume = {47},
  number = {1},
  pages = {89-93},
  abstract = {We investigated whether: (1) EEG recordings could be
                   successfully performed in an MRI imager, (2)
                   subclinical epileptic discharges could be used to
                   trigger ultrafast functional MRI images, (3)
                   artifact-free functional MRI images could be obtained
                   while the patient was having the EEG monitored, and (4)
                   the functional MRI images so obtained would show focal
                   signal increases in relation to epileptic discharges.
                   We report our results in two patients who showed
                   focally higher signal intensity, reflective of
                   increased local blood flow, in ultrafast functional MRI
                   timed to epileptic discharges recorded while the
                   patients were in the imager and compared with images
                   not associated with discharges. One patient showed a
                   focal increase despite a clinical and EEG history of
                   generalized discharges. This approach may have the
                   potential to identify brain regions activated during
                   brief focal epileptic discharges.},
  authoraddress = {Department of Neurnlogy, Beth Israel Hospital, Boston,
                   MA 02215, USA.},
  keywords = {Adult ; *Echo-Planar Imaging ;
                   Electroencephalography/*methods ;
                   Epilepsy/*physiopathology ; Female ; Human ; Magnetic
                   Resonance Imaging},
  language = {eng},
  medline-da = {19960912},
  medline-dcom = {19960912},
  medline-edat = {1996/07/01},
  medline-fau = {Warach, S ; Ives, J R ; Schlaug, G ; Patel, M R ;
                   Darby, D G ; Thangaraj, V ; Edelman, R R ; Schomer, D L},
  medline-is = {0028-3878},
  medline-jid = {0401060},
  medline-lr = {20031114},
  medline-mhda = {1996/07/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {8710131},
  medline-pst = {ppublish},
  medline-pt = {Case Reports ; Journal Article},
  medline-sb = {AIM ; IM},
  medline-so = {Neurology 1996 Jul;47(1):89-93.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=8710131},
  year = 1996
}
@ARTICLE{WPLdS93,
  author = {Wieringa, H. J. and Peters, M. J. and Lopes da Silva,
                   F.H.},
  title = {The estimation of a realistic localization of dipole
                   layers within the brain based on functional ({EEG},
                   {MEG}) and structural ({MRI}) data: a preliminary note},
  journal = {Brain Topogr},
  volume = {5},
  number = {4},
  pages = {327-330},
  authoraddress = {Department of Applied Physics, University of Twente,
                   Enschede, The Netherlands.},
  keywords = {Brain/*pathology/*physiology ; Electroencephalography
                   ; Human ; Magnetic Resonance Imaging ;
                   Magnetoencephalography},
  language = {eng},
  medline-da = {19930930},
  medline-dcom = {19930930},
  medline-edat = {1993/01/01},
  medline-fau = {Wieringa, H J ; Peters, M J ; Lopes da Silva, F H},
  medline-is = {0896-0267},
  medline-jid = {8903034},
  medline-lr = {20001218},
  medline-mhda = {1993/01/01 00:01},
  medline-own = {NLM},
  medline-pl = {UNITED STATES},
  medline-pmid = {8357702},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Review ; Review, Tutorial},
  medline-rf = {13},
  medline-sb = {IM},
  medline-so = {Brain Topogr 1993 Summer;5(4):327-30.},
  medline-stat = {completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=8357702},
  year = 1993
}
@ARTICLE{WRI+06,
  author = {Wan, X. and Riera, J. and Iwata, K. and Takahashi, M.
                   and Wakabayashi, T. and Kawashima, R.},
  title = {The neural basis of the hemodynamic response
                   nonlinearity in human primary visual cortex:
                   {I}mplications for neurovascular coupling mechanism.},
  journal = {Neuroimage},
  abstract = {It has been well recognized that the nonlinear
                   hemodynamic responses of the blood oxygenation
                   level-dependent (BOLD) functional MRI (fMRI) are
                   important and ubiquitous in a series of experimental
                   paradigms, especially for the event-related fMRI.
                   Although this phenomenon has been intensively studied
                   and it has been found that the post-capillary venous
                   expansion is an intrinsically nonlinear mechanical
                   process, the existence of an additional neural basis
                   for the nonlinearity has not been clearly shown. In
                   this paper, we assessed the correlation between the
                   electric and vascular indices by performing
                   simultaneous electroencephalography (EEG) and fMRI
                   recordings in humans during a series of visual
                   stimulation (i.e., radial checkerboard). With changes
                   of the visual stimulation frequencies (from 0.5 to 16
                   Hz) and contrasts (from 1% to 100%), both the event
                   related potentials (ERPs) and hemodynamic responses
                   show nonlinear behaviors. In particular, the mean power
                   of the brain electric sources and the neuronal
                   efficacies (as originally defined in the hemodynamics
                   model [Friston et al. Neuroimage, 12, 466-477, 2000],
                   here represent the vascular inputs) in primary visual
                   cortex consistently show a linear correlation for all
                   subjects. This indicates that the hemodynamic response
                   nonlinearity found in this paper primarily reflects the
                   nonlinearity of underlying neural activity. Most
                   importantly, this finding underpins a nonlinear
                   neurovascular coupling. Specifically, it is shown that
                   the transferring function of the neurovascular coupling
                   is likely a power transducer, which integrates the fast
                   dynamics of neural activity into the vascular input of
                   slow hemodynamics.},
  authoraddress = {Advanced Science and Technology of Materials, NICHe,
                   Tohoku University, Sendai, 980-8579 Miyagi, Japan;
                   Department of Quantum Science and Energy Engineering,
                   Tohoku University, Sendai, 980-8579 Miyagi, Japan.},
  language = {ENG},
  medline-aid = {S1053-8119(06)00237-0 [pii] ;
                   10.1016/j.neuroimage.2006.03.040 [doi]},
  medline-da = {20060515},
  medline-dep = {20060510},
  medline-edat = {2006/05/16 09:00},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-mhda = {2006/05/16 09:00},
  medline-own = {NLM},
  medline-phst = {2005/09/01 [received] ; 2006/03/15 [revised] ;
                   2006/03/23 [accepted]},
  medline-pmid = {16697664},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Neuroimage. 2006 May 10;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16697664},
  year = 2006
}
@ARTICLE{WSB+05b,
  author = {Waites, A.B. and Shaw, M.E. and Briellmann, R.S. and
                   Labate, A. and Abbott, D.F. and Jackson, G.D.},
  title = {How reliable are f{MRI}-{EEG} studies of epilepsy? {A}
                   nonparametric approach to analysis validation and
                   optimization.},
  journal = {Neuroimage},
  volume = {24},
  number = {1},
  pages = {192-199},
  abstract = {Simultaneously acquired functional magnetic resonance
                   imaging (fMRI) and electroencephalography (EEG) data
                   hold great promise for localizing the spatial source of
                   epileptiform events detected in the EEG trace. Despite
                   a number of studies applying this method, there has
                   been no independent and systematic validation of the
                   approach. The present study uses a nonparametric method
                   to show that interictal discharges lead to a blood
                   oxygen level dependent (BOLD) response that is
                   significantly different to that obtained by examining
                   random 'events'. We also use this approach to examine
                   the optimization of analysis strategy for detecting
                   these BOLD responses. Two patients with frequent
                   epileptiform events and a healthy control were studied.
                   The fMRI data for each patient were analyzed using a
                   model derived from the timings of the epileptiform
                   events detected on EEG during fMRI scanning. Twenty
                   sets of random pseudoevents were used to generate a
                   null distribution representing the level of chance
                   correlation between the EEG events and fMRI data. The
                   same pseudoevents were applied to control data. We
                   demonstrate that it is possible to detect blood oxygen
                   level-dependent (BOLD) changes related to interictal
                   discharges with specific and independent knowledge
                   about the reliability of this activation. Biologically
                   generated events complicate the fMRI-EEG experiment.
                   Our proposed validation examines whether identified
                   events have an associated BOLD response beyond chance
                   and allows optimization of analysis strategies. This is
                   an important step beyond standard analysis. It informs
                   clinical interpretation because it permits assessment
                   of the reliability of the connection between interictal
                   EEG events and the BOLD response to those events.},
  authoraddress = {Brain Research Institute, Austin Health, Heidelberg
                   West, Australia.},
  language = {eng},
  medline-aid = {S1053-8119(04)00519-1 [pii] ;
                   10.1016/j.neuroimage.2004.09.005 [doi]},
  medline-da = {20041213},
  medline-edat = {2004/12/14 09:00},
  medline-fau = {Waites, Anthony B ; Shaw, Marnie E ; Briellmann,
                   Regula S ; Labate, Angelo ; Abbott, David F ; Jackson,
                   Graeme D},
  medline-is = {1053-8119},
  medline-jid = {9215515},
  medline-mhda = {2004/12/14 09:00},
  medline-own = {NLM},
  medline-phst = {2004/04/06 [received] ; 2004/06/18 [revised] ;
                   2004/09/07 [accepted]},
  medline-pl = {United States},
  medline-pmid = {15588610},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Neuroimage 2005 Jan 1;24(1):192-9.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=15588610},
  year = 2005
}
@ARTICLE{WSS06,
  author = {Whittingstall, K. and Stroink, G. and Schmidt, M.},
  title = {Evaluating the spatial relationship of event-related
                   potential and functional {MRI} sources in the primary
                   visual cortex.},
  journal = {Hum Brain Mapp},
  abstract = {The integration of electroencephalogram (EEG)
                   recordings and functional magnetic resonance imaging
                   (fMRI) can provide considerable insight into brain
                   functionality. However, the direct relationship between
                   neural and hemodynamic activity is still poorly
                   understood. Of particular interest is the spatial
                   correspondence between event-related potential (ERP)
                   and fMRI sources. In the current study we localized
                   sources generated by a checkerboard stimulus presented
                   to eight subjects using both EEG and fMRI. The location
                   of the sources of the visual evoked potential (VEP)
                   were estimated at each timepoint and compared to the
                   location of peak fMRI activity. In the majority of
                   participants we found that the N75 dipole location
                   coincides with a region of positive blood oxygenation
                   level-dependent (BOLD) activation and the P100 dipole
                   location coincides with a region of negative BOLD
                   activation. These findings demonstrate the importance
                   of including the negative BOLD response in combined
                   EEG/fMRI studies. Hum Brain Mapp, 2006. (c) 2006
                   Wiley-Liss, Inc.},
  authoraddress = {Department of Physics, Dalhousie University, Halifax,
                   Canada.},
  language = {ENG},
  medline-aid = {10.1002/hbm.20265 [doi]},
  medline-da = {20060615},
  medline-dep = {20060607},
  medline-edat = {2006/06/09 09:00},
  medline-is = {1065-9471 (Print)},
  medline-jid = {9419065},
  medline-mhda = {2006/06/09 09:00},
  medline-own = {NLM},
  medline-pmid = {16761265},
  medline-pst = {aheadofprint},
  medline-pt = {JOURNAL ARTICLE},
  medline-pubm = {Print-Electronic},
  medline-so = {Hum Brain Mapp. 2006 Jun 7;.},
  medline-stat = {Publisher},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16761265},
  year = 2006
}
@ARTICLE{XFG03,
  author = {Xiong, J. and Fox, P. T. and Gao, J. H.},
  title = {Directly mapping magnetic field effects of neuronal
                   activity by magnetic resonance imaging},
  journal = {Hum Brain Mapp},
  volume = {20},
  number = {1},
  pages = {41-49},
  abstract = {Magnetic resonance imaging (MRI) of brain functional
                   activity relies principally on changes in cerebral
                   hemodynamics, which are more spatially and temporally
                   distributed than the underlying neuronal activity
                   changes. We present a novel MRI technique for mapping
                   brain functional activity by directly detecting
                   magnetic fields induced by neuronal firing. Using a
                   well-established visuomotor paradigm, the locations and
                   latencies of activations in visual, motor, and premotor
                   cortices were imaged at a temporal resolution of 100
                   msec and a spatial resolution of 3 mm, and were found
                   to be in consistent with the electrophysiological and
                   functional MRI (fMRI) literature. Signal strength was
                   comparable to traditional event-related fMRI methods:
                   about 1\% of the baseline signal. The magnetic-source
                   MRI technique greatly increases the temporal accuracy
                   in detecting neuronal activity, providing a powerful
                   new tool for mapping brain functional organization in
                   human and animals.},
  authoraddress = {Research Imaging Center, University of Texas Health
                   Science Center at San Antonio, San Antonio, Texas.},
  keywords = {*Action Potentials ; Brain/*physiology ; Brain
                   Mapping/*methods ; Female ; Human ; *Magnetic Resonance
                   Imaging ; Male ; Neurons/*physiology ; Support, U.S.
                   Gov't, Non-P.H.S. ; Support, U.S. Gov't, P.H.S.},
  language = {eng},
  medline-aid = {10.1002/hbm.10124 [doi]},
  medline-ci = {Copyright 2003 Wiley-Liss, Inc.},
  medline-da = {20030903},
  medline-dcom = {20031110},
  medline-edat = {2003/09/04 05:00},
  medline-fau = {Xiong, Jinhu ; Fox, Peter T ; Gao, Jia-Hong},
  medline-gr = {AG19844/AG/NIA ; RO1 MH067163/MH/NIMH ;
                   RR17198/RR/NCRR},
  medline-is = {1065-9471},
  medline-jid = {9419065},
  medline-mhda = {2003/11/11 05:00},
  medline-own = {NLM},
  medline-pl = {United States},
  medline-pmid = {12953305},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-sb = {IM},
  medline-so = {Hum Brain Mapp 2003 Sep;20(1):41-9.},
  medline-stat = {Completed},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12953305},
  year = 2003
}
@ARTICLE{ZJB+05,
  author = {Zheng, Y. and Johnston, D. and Berwick, J. and Chen,
                   D. and Billings, S. and Mayhew, J.},
  title = {A three-compartment model of the hemodynamic response
                   and oxygen delivery to brain.},
  journal = {Neuroimage},
  volume = {28},
  number = {4},
  pages = {925-39},
  abstract = {We describe a mathematical model linking changes in
                   cerebral blood flow, blood volume and the blood
                   oxygenation state in response to stimulation. The model
                   has three compartments to take into account the fact
                   that the cerebral blood flow and volume as measured
                   concurrently using laser Doppler flowmetry and optical
                   imaging spectroscopy have contributions from the
                   arterial, capillary as well as the venous compartments
                   of the vasculature. It is an extension to previous
                   one-compartment hemodynamic models which assume that
                   the measured blood volume changes are from the venous
                   compartment only. An important assumption of the model
                   is that the tissue oxygen concentration is a time
                   varying state variable of the system and is driven by
                   the changes in metabolic demand resulting from changes
                   in neural activity. The model takes into account the
                   pre-capillary oxygen diffusion by flexibly allowing the
                   saturation of the arterial compartment to be less than
                   unity. Simulations are used to explore the sensitivity
                   of the model and to optimise the parameters for
                   experimental data. We conclude that the
                   three-compartment model was better than the
                   one-compartment model at capturing the hemodynamics of
                   the response to changes in neural activation following
                   stimulation.},
  authoraddress = {Department of Psychology, University of Sheffield,
                   Sheffield S10 2TP, UK.},
  language = {eng},
  medline-aid = {S1053-8119(05)00485-4 [pii] ;
                   10.1016/j.neuroimage.2005.06.042 [doi]},
  medline-da = {20051205},
  medline-dep = {20050802},
  medline-edat = {2005/08/03 09:00},
  medline-fau = {Zheng, Ying ; Johnston, David ; Berwick, Jason ; Chen,
                   Danmei ; Billings, Steve ; Mayhew, John},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage.},
  medline-mhda = {2005/08/03 09:00},
  medline-own = {NLM},
  medline-phst = {2005/01/17 [received] ; 2005/06/22 [revised] ;
                   2005/06/30 [accepted] ; 2005/08/02 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {16061400},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2005 Dec;28(4):925-39. Epub 2005 Aug 2.},
  medline-stat = {In-Data-Review},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=16061400},
  year = 2005
}
@ARTICLE{ary81,
  author = {Ary, J. and Klein, S. and Fenders, D.},
  title = {Location of sources of evoked scalp potentials:
                  correction for skull and scalp thicknesses},
  journal = {IEEE Trans. Biomed. Eng.},
  year = 1981,
  volume = 28,
  pages = {447-452},
  keywords = {Inverse}
}
@ARTICLE{babiloni01,
  author = {Babiloni, F. and Babiloni, C. and Carducci, F. and
                  Angelone, L. and Del-Gratta, C. and Romani,
                  G. L. and Rossini, P. M. and Cincotti, F.},
  title = {Linear inverse estimation of cortical sources by
                  using high resolution {EEG} and f{MRI} priors},
  journal = {Int. J. Bioelectromag.},
  year = 2001,
  volume = 3,
  number = 1,
  keywords = {Fusion},
  abstract = {In this paper we presented two methods for the
                  modeling of human cortical activity by using
                  combined high-resolution electroencephalography
                  (EEG) and functional magnetic resonance imaging
                  (fMRI) data. These methods were based on linear
                  inverse estimation and used subjects
                  multi-compartment head model (scalp, skull, dura
                  mater, cortex) constructed from magnetic resonance
                  images and a multi-dipole source model. Hemodynamic
                  responses of the investigated cortical areas as
                  derived from block-design and event-related
                  functional Magnetic Resonance Imaging (fMRI) were
                  used as priors in the resolution of the linear
                  inverse problem. High resolution EEG (128
                  electrodes) and fMRI data were recorded in separate
                  sessions, while normal subjects executed voluntary
                  right one-digit movements. Results showed that
                  linear inverse solutions obtained with fMRI priors
                  present more localized spots of activation with
                  respect to those obtained without fMRI
                  priors. Remarkably, the spots of activation were
                  localized in the hand regions of the primary
                  somatosensory (post-central) and motor (pre-central)
                  areas contralateral to the movement. This may
                  suggest that both methods increased the spatial
                  resolution of linear inverse solutions computed from
                  EEG data.},
  url = {http://www.ijbem.org/volume3/number1/babilioni/i/index.htm},
  urldate = {2004-06-26}
}
@ARTICLE{backusGilbert68,
  author = {Backus, G. and Gilbert, F.},
  journal = {Geophys. J. R. Astron. Soc.},
  pages = {169-205},
  title = {The resolving power of gross {Earth} data},
  volume = 16,
  year = 1968
}
@UNPUBLISHED{baillet-chapter01,
  author = {Baillet, S.},
  title = {Probleme Inverse {MEG}/{EEG}},
  url = {http://web.ccr.jussieu.fr/meg-center/media/ecp2001/SBaillet.pdf}
}
@ARTICLE{baillet-etal01,
  author = {Baillet, S. and Mosher, J. C. and Leahy, M.},
  title = {Electromagnetic Brain Mapping},
  journal = {IEEE Sig Proc Mag},
  month = NOV,
  year = 2001,
  volume = 18,
  number = 6,
  pages = {14-30}
}
@ARTICLE{baillet-garnero97,
  author = {Baillet, S. and Garnero, L.},
  title = {A Bayesian Approach to Introducing
                  Anatomo-Functional Priors in the {EEG}/{MEG} Inverse
                  Problem},
  year = 1997,
  journal = {IEEE Trans. Biomed. Eng.},
  month = MAY,
  volume = 44,
  pages = {374-385},
  modified = {faugeras},
  number = 5,
  abstract = {In this paper, we present a new approach to the
                  recovering of dipole magnitudes in a distributed
                  source model for magnetoencephalographic (MEG) and
                  electroencephalographic (EEG) imaging. This method
                  consists in introducing spatial and temporal a
                  priori information as a cure to this ill-posed
                  inverse problem. A nonlinear spatial regularization
                  scheme allows the preservation of dipole moment
                  discontinuities between some a priori noncorrelated
                  sources, for instance, when considering dipoles
                  located on both sides of a sulcus. Moreover, we
                  introduce temporal smoothness constraints on dipole
                  magnitude evolution at time scales smaller than
                  those of cognitive processes. These priors are
                  easily integrated into a Bayesian formalism,
                  yielding a maximum a posteriori (MAP) estimator of
                  brain electrical activity. Results from EEG
                  simulations of our method are presented and compared
                  with those of classical quadratic regularization and
                  a now popular generalized minimum-norm technique
                  called low-resolution electromagnetic tomography
                  (LORETA).},
  url = {http://citeseer.nj.nec.com/519829.html}
}
@MISC{brainstorm-sw,
  author = {Leahy, R. M. and Baillet, S. and Mosher, J. C.},
  title = {Integrated Matlab Toolbox dedicated to
                  Magnetoencephalography ({MEG}) and
                  Electroencephalography ({EEG}) data visualization
                  and processing},
  url = {http://neuroimage.usc.edu/brainstorm/},
  urldate = {2004-10-04},
  year = 2004
}
@ARTICLE{brainsuite-sw,
  author = {Shattuck, D.W. and Leahy, R.M.},
  title = {Brain{S}uite: an automated cortical surface
                   identification tool.},
  journal = {Med Image Anal},
  volume = {6},
  number = {2},
  pages = {129-142},
  abstract = {We describe a new magnetic resonance (MR) image
                   analysis tool that produces cortical surface
                   representations with spherical topology from MR images
                   of the human brain. The tool provides a sequence of
                   low-level operations in a single package that can
                   produce accurate brain segmentations in clinical time.
                   The tools include skull and scalp removal, image
                   nonuniformity compensation, voxel-based tissue
                   classification, topological correction, rendering, and
                   editing functions. The collection of tools is designed
                   to require minimal user interaction to produce cortical
                   representations. In this paper we describe the theory
                   of each stage of the cortical surface identification
                   process. We then present classification validation
                   results using real and phantom data. We also present a
                   study of interoperator variability.},
  authoraddress = {Signal and Image Processing Institute, Department of
                   Electrical Engineering Systems, University of Southern
                   California, Los Angeles 90089-2564, USA},
  keywords = {Algorithms ; Automation ; Brain/anatomy & histology ;
                   Cerebral Cortex/*anatomy & histology ; Computer
                   Simulation ; Humans ; *Image Processing,
                   Computer-Assisted ; Magnetic Resonance Imaging/*methods
                   ; Models, Anatomic ; *Models, Neurological ; Research
                   Support, U.S. Gov't, P.H.S. ; Sensitivity and
                   Specificity ; *Software ; Surface Properties},
  language = {eng},
  medline-aid = {S1361841502000543 [pii]},
  medline-da = {20020604},
  medline-dcom = {20020917},
  medline-edat = {2002/06/05 10:00},
  medline-fau = {Shattuck, David W ; Leahy, Richard M},
  medline-gr = {R01-MH53213/MH/NIMH ; RR13642/RR/NCRR},
  medline-jid = {9713490},
  medline-lr = {20041117},
  medline-mhda = {2002/09/18 10:01},
  medline-own = {NLM},
  medline-pl = {England},
  medline-pmid = {12045000},
  medline-pst = {ppublish},
  medline-pt = {Journal Article ; Validation Studies},
  medline-pubm = {Print},
  medline-sb = {IM},
  medline-so = {Med Image Anal 2002 Jun;6(2):129-42.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=12045000},
  year = 2002
}
@ARTICLE{brazier49,
  author = {Brazier, M. A. B.},
  title = {A study of the electric field at the surface of the
                  head},
  journal = {Electroencephalogr. Clin. Neurophysiol.},
  year = 1949,
  volume = 2,
  pages = {38-52}
}
@MISC{burger01regularization,
  author = {Burger, M. and Scherzer, O.},
  title = {Regularization methods for blind deconvolution and
                  blind source separation problems},
  text = {Math. Cont. Signals & Systems (2001), to apppear.},
  year = {2001},
  abstract = {This paper is devoted to blind deconvolution and
                  blind separation problems. Blind deconvolution is
                  the identification of a point spread function and an
                  input signal from an observation of their
                  convolution. Blind source separation is the recovery
                  of a vector of input signals from a vector of
                  observed signals, which are mixed by a linear
                  (unknown) operator. We show that both problems are
                  paradigms of nonlinear ill--posed
                  problems. Consequently, regularization techniques
                  have to be used for stable numerical
                  reconstructions. In this paper we develop a rigorous
                  convergence analysis for regularization techniques
                  for the solution of blind deconvolution and blind
                  separation problems. We prove convergence of the
                  alternating minimization algorithm for the numerical
                  solution of regularized blind deconvolution problems
                  and present some numerical examples. Moreover, we
                  show that many neural network approaches for blind
                  inversion can be considered in the framework of
                  regularization theory. },
  url = {http://citeseer.nj.nec.com/burger01regularization.html}
}
@INPROCEEDINGS{calhoun-etal03,
  author = {V. D. Calhoun and T. Adali and L. K. Hansen and
                  J. Larsen and J. J. Pekar},
  title = {{ICA} of Functional {MRI} Data: An Overview},
  year = 2003,
  month = APR,
  keywords = {fMRI, {ICA}, review},
  pages = {281-288},
  booktitle = {Fourth International Symposium on Independent
                  Component Analysis and Blind Source Separation},
  address = {Nara, Japan},
  note = {Invited Paper},
  url = {http://www.imm.dtu.dk/pubdb/p.php?1669}
}
@PHDTHESIS{castellanosmith99,
  author = {Castellano, S. A.},
  title = {The Folding of the Human Brain: From Shape to
                  Function},
  school = {University of London},
  year = 1999,
  address = {Division of Radiological Sciences and Medical
                  Engineering, King's College London},
  month = SEP,
  abstract = {This thesis explores the relationship between the
                  shape of the surface of the human brain and the
                  function of the underlying tissue. In this work,
                  structural information is provided by magnetic
                  resonance imaging. Functional information is
                  gathered using functional magnetic resonance imaging
                  and by electrophysiological monitoring with
                  sub-durally implanted metal electrodes lying
                  directly on the brain surface, which are localised
                  using X-ray computed tomography images. The thesis
                  examines techniques for comparing the information
                  provided by the functional modalities with the shape
                  of the underlying brain surface structures. The
                  feasibility of comparing localisation of functional
                  regions provided by functional magnetic resonance
                  imaging with that provided by direct
                  electrophysiological mapping is explored. The
                  possibility of relating the shape of the cortical
                  surface to the function of the brain is
                  examined. Suitable geometrical measures for
                  quantifying the shape of the brain surface are
                  proposed. The measures discussed include measures of
                  convexity in both two and three dimensions, measures
                  based on surface area and volume measurements, and a
                  set of measures based on integrals of intrinsic and
                  extrinsic curvatures. Published work comparing
                  surface shape and function is reviewed. Practical
                  methods for applying the set of measures considered
                  to discrete surfaces extracted from MR volumes are
                  proposed. A discrete triangulated surface model has
                  been devised to allow the calculation of these shape
                  measures, and is described in detail. The smoothing
                  of this surface model, and of measures extracted
                  from it, is discussed in relation to noise in the
                  surface fitted to the discrete dataset obtained from
                  the anatomical images. The techniques are then
                  applied to three-dimensional magnetic resonance
                  images of a number of human brains. Initially the
                  set of measures is applied to a series of normal
                  ex-vivo foetal brains with gestational ages ranging
                  from 19 weeks to 40 weeks. The shape measures are
                  shown to reliably characterise the development of
                  folding during normal development, with differences
                  between gestational ages being significantly greater
                  than the variability in the measures when applied to
                  several brains of the same gestational age. The
                  measures are then applied to a series of abnormally
                  developed foetal brains, to a set of normal adult
                  brains, and to a set of schizophrenic adult brains,
                  in order to characterise the ability of the measures
                  to distinguish between normal and abnormal brain
                  surface shapes.},
  url = {http://www-ipg.umds.ac.uk/a.d.smith/phd/contents.html}
}
@ARTICLE{cocosco-etal97,
  author = {Cocosco, C. A. and Kollokian, V. and Kwan, R.K.-S.
                  and Evans, A. C.},
  title = {BrainWeb: Online Interface to a 3D MRI Simulated
                  Brain Database},
  journal = {NeuroImage},
  volume = 5,
  number = 4,
  booktitle = {Proceedings of 3-rd International Conference on
                  Functional Mapping of the Human Brain, Copenhagen},
  year = 1997,
  month = MAY
}
@INCOLLECTION{cohen-halgren03,
  author = {Cohen, D. and Halgren, E. },
  booktitle = {Encyclopedia of Neuroscience},
  title = {Magnetoencephalography (Neuromagnetism)},
  publisher = {Elsevier},
  year = 2003,
  edition = {3rd},
  pages = {1-7},
  keywords = {MEG, overview},
  annote = {Short introductory to {MEG}. Covers difference
                  between {EEG} and {MEG}. Has a photo of 1st SQUID
                  MEG at MIT},
  url = {http://www.nmr.mgh.harvard.edu/meg/pdfs/2003EncycNeuroSc.pdf}
}
@MISC{cohen04patent,
  author = {Cohen, M. S.},
  title = {Method and apparatus for reducing contamination of
                  an electrical signal},
  howpublished = {United States Patent application 0040097802},
  number = {PCT NO: PCT/US01/25480},
  url = {http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&co1=AND&d=PG01&s1=%2210%2F344%2C776%22&OS=%2210/344,776%22&RS=%2210/344,776%22},
  year = 2004,
  urldate = {2004-08-31}
}
@ARTICLE{dMG+07,
  author = {de Munck, J. C. and Goncalves, S. I. and Huijboom, L.
                   and Kuijer, J. P. and Pouwels, P. J. and Heethaar, R.
                   M. and Lopes da Silva, F. H.},
  title = {The hemodynamic response of the alpha rhythm: an
                   {EEG}/f{MRI} study.},
  journal = {Neuroimage},
  volume = {35},
  number = {3},
  pages = {1142-51},
  abstract = {EEG was recorded during fMRI scanning of 16 normal
                   controls in resting condition with eyes closed. Time
                   variations of the occipital alpha band amplitudes were
                   correlated to the fMRI signal variations to obtain
                   insight into the hemodynamic correlates of the EEG
                   alpha activity. Contrary to earlier studies, no a
                   priori assumptions were made on the expected shape of
                   the alpha band response function (ARF). The ARF of
                   different brain regions and subjects were explored and
                   compared. It was found that: (1) the ARF of the
                   thalamus is mainly positive. (2) The ARFs at the
                   occipital and left and right parietal points are
                   similar in amplitude and timing. (3) The peak time of
                   the thalamus is a few seconds earlier than that of
                   occipital and parietal cortex. (4) No systematic BOLD
                   activity was found preceding the alpha band activity,
                   although in the two subjects with the strongest alpha
                   band power such correlation was present. (5) There is a
                   strong and immediate positive correlation at the
                   eyeball, and a strong negative correlation at the back
                   of the eye. Furthermore, it was found that in one
                   subject the cortical ARF was positive, contrary to the
                   other subjects. Finally, a cluster analysis of the
                   observed ARF, in combination with a Modulated Sine
                   Model (MSM) fit to the estimated ARF, revealed that
                   within the cortex the ARF peak time shows a spatial
                   pattern that may be interpreted as a traveling wave.
                   The spatial pattern of alpha band response function
                   represents the combined effect of local differences in
                   electrical alpha band activity and local differences in
                   the hemodynamic response function (HRF) onto these
                   electrical activities. To disentangle the contributions
                   of both factors, more advanced integration of EEG
                   inverse modeling and hemodynamic response modeling is
                   required in future studies.},
  authoraddress = {Department PMT, VU Medical Center, De Boelelaan 1117,
                   1081 HV Amsterdam, The Netherlands. jc.munck@vumc.nl
                   },
  keywords = {Adult ; Alpha Rhythm/*methods ; Blood Flow
                   Velocity/physiology ; Brain/*blood supply/*physiology ;
                   Brain Mapping/*methods ; Cerebrovascular
                   Circulation/*physiology ; Female ; Humans ; Magnetic
                   Resonance Imaging/*methods ; Male ; Reproducibility of
                   Results ; Sensitivity and Specificity},
  language = {eng},
  medline-aid = {S1053-8119(07)00089-4 [pii] ;
                   10.1016/j.neuroimage.2007.01.022 [doi]},
  medline-da = {20070409},
  medline-dcom = {20070612},
  medline-dep = {20070204},
  medline-edat = {2007/03/06 09:00},
  medline-fau = {de Munck, J C ; Goncalves, S I ; Huijboom, L ; Kuijer,
                   J P A ; Pouwels, P J W ; Heethaar, R M ; Lopes da
                   Silva, F H},
  medline-is = {1053-8119 (Print)},
  medline-jid = {9215515},
  medline-jt = {NeuroImage},
  medline-mhda = {2007/06/15 09:00},
  medline-own = {NLM},
  medline-phst = {2006/09/26 [received] ; 2007/01/23 [revised] ;
                   2007/01/24 [accepted] ; 2007/02/04 [aheadofprint]},
  medline-pl = {United States},
  medline-pmid = {17336548},
  medline-pst = {ppublish},
  medline-pt = {Journal Article},
  medline-pubm = {Print-Electronic},
  medline-sb = {IM},
  medline-so = {Neuroimage. 2007 Apr 15;35(3):1142-51. Epub 2007 Feb
                   4.},
  medline-stat = {MEDLINE},
  url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?cmd=prlinks&dbfrom=pubmed&retmode=ref&id=17336548},
  year = 2007
}
@ARTICLE{dale-liu-etal00,
  author = {Dale, A. M. and Liu, A. K. and Fischl, B. and
                  Lewine, J. D. and Buckner, R. L. and Belliveau,
                  J. W. and Halgren, E.},
  title = {Dynamic statistical parameter mapping: combining
                  f{MRI} and {MEG} to produce high resolution imaging
                  of cortical activity},
  journal = {Neuron},
  year = 2000,
  volume = 26,
  pages = {55-67},
  abstract = {Functional magnetic resonance imaging (fMRI) can
                  provide maps of brain activation with millimeter
                  spatial resolution but is limited in its temporal
                  resolution to the order of seconds. Here, we
                  describe a technique that combines structural and
                  functional MRI with magnetoencephalography (MEG) to
                  obtain spatiotemporal maps of human brain activity
                  with millisecond temporal resolution. This new
                  technique was used to obtain dynamic statistical
                  parametric maps of cortical activity during semantic
                  processing of visually presented words. An initial
                  wave of activity was found to spread rapidly from
                  occipital visual cortex to temporal, parietal, and
                  frontal areas within 185 ms, with a high degree of
                  temporal overlap between different areas. Repetition
                  effects were observed in many of the same areas
                  following this initial wave of activation, providing
                  evidence for the involvement of feedback mechanisms
                  in repetition priming.},
  url = {http://www.fmri.org/pdfs/anders_neuron2000.pdf}
}
@ARTICLE{dale-sereno93,
  author = {Dale, A. M. and Sereno, M. I. },
  title = {Improved Localization of Cortical Activity by
                  Combining {EEG} and {MEG} with {MRI} Cortical
                  Surface Reconstruction: A Linear Approach},
  year = 1993,
  journal = {J. Cog. Neurosci.},
  volume = 5,
  pages = {162-176},
  modified = {faugeras},
  number = 2,
  abstract = {We describe a comprehensive linear approach to the
                  problem of imaging brain activity with high temporal
                  as well as spatial resolution based on combining EEG
                  and MEG data with anatomical constraints derived
                  from MRI images. The inverse problem of estimating
                  the distribution of dipole strengths over the
                  cortical surface is highly underdetermined, even
                  given closely spaced EEG and MEG recordings. We have
                  obtained much better solutions to this problem by
                  explicitly incorporating both local cortical
                  orientation as well as spatial covariance of sources
                  and sensors into our formulation. An explicit
                  polygonal model of the cortical manifold is first
                  constructed as follows: (1) slice data in three
                  orthogonal planes of section (needle-shaped voxels)
                  are combined with a linear deblurring technique to
                  make a single high-resolution 3-D image (cubic
                  voxels), (2) the image is recursively flood-filled
                  to determine the topology of the gray-white matter
                  border, and (3) the resulting continuous surface is
                  refined by relaxing it against the original 3-D
                  gray-scale image using a deformable template method,
                  which is also used to computationally flatten the
                  cortex for easier viewing. The explicit solution to
                  an error minimization formulation of an optimal
                  inverse linear operator (for a particular cortical
                  manifold, sensor placement, noise and prior source
                  covariance) gives rise to a compact expression that
                  is practically computable for hundreds of sensors
                  and thousands of sources. The inverse solution can
                  then be weighted for a particular (averaged) event
                  using the sensor covariance for that event. Model
                  studies suggest that we may be able to localize
                  multiple cortical sources with spatial resolution as
                  good as PET with this technique, while retaining a
                  much more fine grained picture of activity over
                  time.},
  url = {http://cogsci.ucsd.edu/~sereno/}
}
@INPROCEEDINGS{dojat03,
  author = {Dojat, M. and Warnking, J. and Segebarth, C.},
  title = {Detection at 1.5 Tesla of sustained negative {BOLD}
                  signal in the human visual cortex during partial
                  visual field stimulation},
  booktitle = {Intern. Soc. for Magn. Resonance in Med.},
  year = 2003,
  keywords = {HRF},
  address = {Toronto},
  abstract = {Sustained negative BOLD responses, in the human
                  visual system, have not been reported at the usual
                  field strengths. Such negative responses are likely
                  due to a decrease of cerebral perfusion in
                  non-stimulated areas adjacent to the activated ones,
                  as a result of reallocation of the cortical blood
                  resources. This reallocation may even affect
                  activated areas, thus inducing signal extinction or
                  negative BOLD signal in areas where positive BOLD
                  responses would be anticipated. In combining partial
                  visual field stimulation experiments and retinotopic
                  mapping experiments at 1.5 T, we show that such
                  negative responses may be detected, following
                  reduced visual field stimulation.},
  url = {http://rhea.ujf-grenoble.fr/people/mdojat/publications.htm}
}
@MISC{eegmritoolbox-sw,
  author = {Weber, D.},
  title = {{EEG} and {MRI} {Matlab} Toolbox},
  url = {http://eeg.sourceforge.net/},
  urldate = {2004-10-04},
  year = 2004
}
@INPROCEEDINGS{ermer00,
  author = {Ermer, J. J. and Leahy, R. M. and Mosher, J. C. and
                  Baillet, S.},
  title = {Rapidly Recomputable {EEG} Forward Models for
                  Realistic Head Shapes},
  booktitle = {Proceedings of BIOMAG2000},
  year = 2000,
  series = {12th International Conference on Biomagnetism},
  address = {Helsinki, Finland},
  month = AUG,
  abstract = {Using precomputed BEM form fit the best
                  approximating sphere for each sensor and then use 3d
                  interpolation to approximate forward field}
}
@ARTICLE{frahm-dechentetal04,
  author = {Frahm, J. and Dechent, P. and Baudewig, J. and
                  Merboldt, K. D.},
  title = {Advances in functional {MRI} of the human brain},
  journal = {Progr. Nucl. Magn. Res. Spectr.},
  year = 2004,
  month = FEB,
  abstract = {Based on an improved understanding of the underlying
                  physiologic mechanisms and a growing number of
                  applications to selected brain systems, the main
                  purpose of this contribution is to present a
                  discussion of the general potential and the specific
                  challenges of this continuously expanding
                  field. Rather than providing a comprehensive survey,
                  emphasis will be placed on both characteristic
                  advantages that render MRI particularly attractive
                  for functional neuroimaging and potential problems
                  that may hamper the interpretation of the
                  experimental results. Apart from discussing crucial
                  aspects ranging from cerebral hemodynamics to data
                  acquisition and parametric mapping, specific points
                  addressed are the neural basis of the functional MRI
                  signal as well as the achievable spatial and
                  temporal resolution. Technical complications will be
                  discussed as well as limitations resulting from
                  pharmacological and pathological modulations of the
                  neurovascular coupling. A final section covers the
                  increasingly difficult translation of a
                  neuroscientific question into a proper
                  MRI-compatible paradigm.},
  url = {http://dx.doi.org/10.1016/j.pnmrs.2003.11.002}
}
@MISC{freesurfer-sw,
  key = {FreeSurfer},
  title = {{FreeSurfer}},
  note = {{CorTechs and the Athinoula A. Martinos Center for
                  Biomedical Imaging}},
  url = {http://surfer.nmr.mgh.harvard.edu/},
  urldate = {2004-10-15},
  year = 2004
}
@ARTICLE{friston-etal94,
  author = {Friston, K. J. and Jezzard, P. and Turner, R.},
  title = {Analysis of functional {MRI} time-series},
  journal = {Hum. Brain Mapp.},
  year = 1994,
  volume = 1,
  pages = {153-171},
  abstract = {We present a method for detecting significant and
                  regionally specific correlatio ns between sensory
                  input and the braiifs physiological response, as
                  measured with functional MRI. The method involves
                  testing for correlations, between sensory input and
                  the hemodynamic response, after convolving the
                  sensory input with an estimate of the hemodynamic
                  response function. This estimate is obtained without
                  reference to any assumed input. To lend the approach
                  statistical validity, it is brought into the
                  framework of s tatistical parametric mapping by
                  using a measure of cross-correlations, between
                  sensory input and hemo dynamic response, that is
                  valid in the presence of intrinsic
                  autocorrelations. These autocorrelations are
                  necessarily present, due to the hemodynamic response
                  function or temporal point spread function.}
}
@INPROCEEDINGS{garcia-trujillo04,
  author = {Melie-Garc{\'i}a, L. and Trujillo-Barreto, N. J. and
                  Mart{\'i}nez-Montes, E. and Koenig, T. and
                  Vald{\'e}s-Sosa, P. A.},
  title = {{EEG} imaging via {BMA} with {fMRI} pre-defined
                  prior model probabilities},
  booktitle = {Hum. Brain Mapp.},
  address = {Budapest, Hungary},
  year = 2004,
  month = JUN,
  annote = {Poster #WE 245},
  abstract = {In the present work, a modification of the EEG/MEG
                  inverse solution method presented by Trujillo
                  et. al. 2004 (known as Bayesian Model Averaging
                  (BMA)), is introduced in order to include prior
                  information provided by fMRI. This BMA approach
                  basically finds a "model-free" Primary Current
                  Density (PCD) inside the brain by dealing with the
                  uncertainty of selecting a specific model to carry
                  out inference upon it. The models differ in the
                  anatomical constraint used to find the solution,
                  which are defined by different combinations of brain
                  areas taken from a segmentation of the brain into 69
                  compartments},
  url = {http://www.meetingassistant.com/ohbm/FORMATTED/CategoryAbstracts/cat19.html},
  urldate = {2004-10-07}
}
@ARTICLE{george-etal95-dup,
  author = {George, J. S. and Aine, C. J. and Mosher, J. C. and
                  Schmidt, D. M. and Ranken, D. M. and Schlitt,
                  H. A. and Wood, C. C. and Lewine, J. D. and Sanders,
                  J. A. and Belliveau, J. W.},
  title = {Mapping function in the human brain with
                  magnetoencephalography, anatomical
                  magnetic-resonance-imaging, and functional
                  magnetic-resonance-imaging},
  journal = {J. Clin. Neurophysiol.},
  year = 1995,
  volume = 12,
  number = 5,
  pages = {406-431},
  abstract = {Integrated analyses of human anatomical and
                  functional measurements offer a powerful paradigm
                  for human brain mapping, Magnetoencephalography
                  (MEG) and EEG provide excellent temporal resolution
                  of neural population dynamics as well as
                  capabilities for source localization. Anatomical
                  magnetic resonance imaging (MRI) provides excellent
                  spatial resolution of head and brain anatomy,
                  whereas functional MRI (fMRI) techniques provide an
                  alternative measure of neural activation based on
                  associated hemodynamic changes. These methodologies
                  constrain and complement each other and can thereby
                  improve our interpretation of functional neural
                  organization. We have developed a number of
                  computational tools and techniques for the
                  visualization, comparison, and integrated analysis
                  of multiple neuroimaging techniques. Construction of
                  geometric anatomical models from volumetric MRI data
                  allows improved models of the head volume conductor
                  and can provide powerful constraints for neural
                  electromagnetic source modeling. These approaches,
                  coupled to enhanced algorithmic strategies for the
                  inverse problem, can significantly enhance the
                  accuracy of source-localization procedures. We have
                  begun to apply these techniques for studies of the
                  functional organization of the human visual
                  system. Such studies have demonstrated multiple,
                  functionally distinct visual areas that can be
                  resolved on the basis of their locations, temporal
                  dynamics, and differential sensitivity to stimulus
                  parameters. Our studies have also produced evidence
                  of internal retinotopic organization in both striate
                  and extrastriate visual areas but have disclosed
                  organizational departures from classical
                  models. Comparative studies of MEG and fMRI suggest
                  a reasonable but imperfect correlation between
                  electrophysiological and hemodynamic responses. We
                  have demonstrated a method for the integrated
                  analysis of fMRI and MEG, and we outline strategies
                  for improvement of these methods. By combining
                  multiple measurement techniques, we can exploit the
                  complementary strengths and transcend the
                  limitations of the individual neuroimaging
                  methods. 'on file. good vision review. and technical
                  review.'}
}
@INBOOK{george02,
  author = {George, J. S. and Schmidt, D. M. and Rector,
                  D. M. and Wood, C. C.},
  title = {Functional {MRI}: An Introduction to Methods},
  chapter = {19. Dynamic functional neuroimaging intergratin
                  multiple modalities},
  publisher = {Oxford University Press},
  keywords = {Fusion, Fusion Review},
  year = 2002,
  pages = {353-382}
}
@ARTICLE{golub79,
  author = {Golub, G. and Heath, M. and Wahba, G.},
  title = {Generalized cross-validation as a method for
                  choosing a good ridge parameter},
  journal = {Technometrics},
  year = 1979,
  volume = 21,
  pages = {215-223}
}
@ARTICLE{gonzalez01,
  author = {Gonzalez Andino, S. L. and Blanke, O. and Lantz,
                  G. and Thut, G. and Grave de Peralta Menendez, R.},
  title = {The Use of Functional Constraints for the
                  Neuroelectromagnetic Inverse Problem: Alternatives
                  and Caveats},
  journal = {Int. J. Bioelectromag.},
  year = 2001,
  volume = 3,
  number = 1,
  keywords = {Fusion},
  abstract = {This paper starts discussing some alternatives to
                  integrate functional information as constraints for
                  the inverse solution. Concrete examples of
                  situations where functional images substantially
                  diverge from electrophysiological methods are
                  presented to promote the discussion about the most
                  reasonable alternatives to combine these image
                  modalities. The results of an anatomically
                  constrained inverse solution that employs a sound
                  physical model are compared with the EEG triggered
                  fMRI in an epileptic patient. This example serves to
                  show that the spatial resolution attainable with
                  inverse solutions is comparable in some situations
                  with that of functional images. Finally, some
                  concrete strategies to ameliorate the quality and
                  reliability of linear inverse solutions maps in more
                  general situations are briefly described. The main
                  conclusion of this paper is that integration of
                  functional modalities into the solution of the NIP
                  should be cautiously considered until a more tight
                  coupling between BOLD effects and
                  electrophysiological measurements could be
                  established},
  url = {http://www.ijbem.org/volume3/number1/gravedeperalta/index.htm},
  urldate = {2005-05-09}
}
@ARTICLE{gorodnitsky97,
  author = {Gorodnitsky, I. F. and Rao, B. D.},
  title = {Sparse Signal Reconstruction from Limited Data using
                  {FOCUSS}: A Re-weighted Minimum Norm Algorithm},
  journal = {IEEE Trans. Signal Proccessing},
  year = 1997,
  volume = 45,
  number = 3,
  pages = {600-616}
}
@INCOLLECTION{hansen92,
  author = {Hansen, P. C.},
  title = {Analysis of discrete ill-posed problems by means of
                  the {L}-curve},
  booktitle = {SIAM Review},
  pages = {561-580},
  publisher = {Society for Industrial and Applied Mathematics},
  address = {Philadelphia, PA, USA},
  year = 1992,
  volume = 34,
  issue = 4
}
@ARTICLE{heeger02,
  author = {Heeger, D. J. and Ress, D.},
  title = {What does f{MRI} tell us about neuronal activity},
  journal = {Nature Rev. Neurosci.},
  year = 2002,
  volume = 3,
  pages = {142-151},
  abstract = {In recent years, cognitive neuroscientists have
                  taken great advantage of functional magnetic
                  resonance imaging (fMRI) as a non-invasive method of
                  measuring neuronal activity in the human brain. But
                  what exactly does fMRI tell us? We know that its
                  signals arise from changes in local haemodynamics
                  that, in turn, result from alterations in neuronal
                  activity, but exactly how neuronal activity,
                  haemodynamics and fMRI signals are related is
                  unclear. It has been assumed that the fMRI signal is
                  proportional to the local average neuronal activity,
                  but many factors can influence the relationship
                  between the two. A clearer understanding of how
                  neuronal activity influences the fMRI signal is
                  needed if we are correctly to interpret functional
                  imaging data.}
}
@INPROCEEDINGS{kullmann89,
  author = {Kullmann, W. K. and Jandt, K. D. and Rehm, K. and
                  Schlitt, H. A. and Dallas, W. J. and Smith, W. E.},
  title = {A linear estimation approach to biomagnetic imaging},
  booktitle = {Proc Seventh Int Conf on Biomagnet},
  year = 1989,
  pages = {301-302}
}
@INPROCEEDINGS{lahaye-etal04,
  author = {Lahaye, P.-J. and Baillet, S. and Poline, J.-B. and
                  Garnero, L.},
  title = {Fusion of simultaneous f{MRI/EEG} data based on the
                  electro-metabolic coupling},
  booktitle = {Proc. IEEE ISBI},
  year = 2004,
  pages = {864-867},
  address = {Arlington, Virginia},
  month = APR
}
@INPROCEEDINGS{lahaye-etal04b,
  author = {Lahaye, P.-J. and Baillet, S. and Poline, J.-B. and
                  Schwartz, D. P. and Hugueville, L. and Martinerie,
                  J. and Garnero, L.},
  title = {The {BOLD}/{EEG} relationship and data fusion from
                  simultaneous {EEG}/{fMRI} recordings},
  address = {Budapest, Hungary},
  year = 2004,
  month = JUN,
  organization = {Hum. Brain Mapp.},
  annote = {Poster #WE 217},
  url = {http://www.meetingassistant.com/ohbm/FORMATTED/CategoryAbstracts/cat18.html},
  urldate = {2004-10-08}
}
@ARTICLE{lange97,
  author = {Lange, N. and Zeger, S. L.},
  title = {Non-Linear Fourier Time Series Analysis for Human
                  Brain Mapping by Functional Magnetic Resonance
                  Imaging},
  journal = {Appl. Stat.},
  year = 1997,
  volume = 46,
  number = 1,
  pages = {1-29},
  annote = {Original Gamma HRF model paper},
  url = {http://citeseer.nj.nec.com/ncontextsummary/63398/0}
}
@BOOK{lawson74,
  author = {Lawson, C. L. and Hanson, R. J.},
  title = {Solving Least Squares Problems},
  publisher = {Prentice-Hall},
  address = {Englewood Cliffs, NJ 07632, USA},
  pages = {xii + 340},
  year = 1974,
  isbn = {0-13-822585-0},
  lccn = {QA275 .L425 1974},
  series = {Series in Automatic Computation},
  alias = {Lawson 74a},
  bibsource = {ftp://ftp.math.utah.edu/pub/bibnet/authors/m/matched-field-proc.bib},
  keywords = {electronic data processing, least squares},
  sthbib = {M4 Law 82 121}
}
@INCOLLECTION{lewine90,
  author = {Lewine, J. D.},
  title = {Neuromagnetic techniques for the noninvasive
                  analysis of brain function},
  booktitle = {Noninvasive techniques in Biology and Medicine},
  publisher = {San Francisco Press},
  year = 1990,
  editor = {Freeman, S. E. andFukushima, E. and Greene, E. R.}
}
@INBOOK{logothetis03book,
  author = {Logothetis, N. K.},
  title = {Functional Magnetic Resonance Imaging in Cognitive
                  Sciences: Principles, Advanced Techniques and
                  Applications},
  year = 2003,
  publisher = {Cognitive Neurosciences III},
  chapter = {?}
}
@BOOK{malmivuo-plonsey95,
  author = {Malmivuo, J. and Plonsey, R.},
  title = {Bioelectromagnetism---Principles and Applications of
                  Bioelectric and Biomagnetic Fields},
  publisher = {Oxford University Press},
  year = 1995,
  address = {New York, 1995},
  url = {http://butler.cc.tut.fi/~malmivuo/bem/bembook/index.htm},
  urldate = {2004-10-05}
}
@ARTICLE{marin-etal98,
  author = {Marin, G. and Guerin, C. and Baillet, S. and
                  Garnero, L. and Meunier, G.},
  title = {Influence of skull anisotropy for the forward and
                  inverse problems in {EEG}: simulation studies using
                  {FEM} on realistic head models},
  year = 1998,
  journal = {Hum. Brain Mapp.},
  volume = 6,
  pages = {250-269},
  modified = {faugeras}
}
@INPROCEEDINGS{mattout-etal00,
  author = {Mattout, J. and Garnero, L. and Gavit, L. and
                  Benali, H.},
  title = {Functional {MRI} derived priors for solving the
                  {EEG}/{MEG} inverse problem},
  booktitle = {12th Int Conf Biomagnet},
  editor = {Nenonen, J. and Ilmoniemi, R.J. and Katila, T.},
  year = 2000,
  address = {Helsinski, Finlande},
  abstract = {In this study, we propose a new multimodal approach
                  for solving the EEG/MEG inverse problem. This method
                  involves a distributed source model and accounts for
                  anatomo-functional constraints derived from
                  functional magnetic resonance imaging (fMRI)
                  data. In the following, we briefly describe the
                  source model, the regularization procedure and the
                  way functional priors are introduced. In order to
                  assess the value of the proposed approach, we then
                  present results obtained using simulated data.}
}
@MISC{megtools-sw,
  key = {MEGtools},
  author = {Moran, J. E.},
  title = {{MEG} tools for {M}atlab software},
  url = {http://rambutan.phy.oakland.edu/~meg/},
  urldate = {2005-05-09},
  year = 2005
}
@ARTICLE{menedez-andino98,
  author = {Grave de Peralta Menendez, R. and Gonzalez Andino,
                  S. L.},
  title = {A critical analysis of linear inverse solutions to
                  the neuroelectromagnetic inverse problem},
  journal = {IEEE Trans. Biomed. Eng.},
  year = 1998,
  pages = {440-448}
}
@ARTICLE{miller01,
  author = {Miller, K. L. and Luh, W-M. and Liu, T. T. and
                  Martinez, A. and Obata, T. and Wong, E. C. and
                  Frank, L. R. and Buxton, R. B.},
  title = {Nonlinear temporal dynamics of the cerebral blood
                  flow response},
  journal = {Hum. Brain Mapp.},
  year = 2001,
  volume = 13,
  number = 1,
  pages = {1-12},
  abstract = {The linearity of the cerebral perfusion response
                  relative to stimulus duration is an important
                  consideration in the characterization of the
                  relationship between regional cerebral blood flow
                  (CBF), cerebral metabolism, and the blood
                  oxygenation level dependent (BOLD) signal. It is
                  also a critical component in the design and analysis
                  of functional neuroimaging studies. To study the
                  linearity of the CBF response to different duration
                  stimuli, the perfusion response in primary motor and
                  visual cortices was measured during stimulation
                  using an arterial spin labeling technique with
                  magnetic resonance imaging (MRI) that allows
                  simultaneous measurement of CBF and BOLD changes. In
                  each study, the perfusion response was measured for
                  stimuli lasting 2, 6, and 18 sec. The CBF response
                  was found in general to be nonlinearly related to
                  stimulus duration, although the strength of
                  nonlinearity varied between the motor and visual
                  cortices. In contrast, the BOLD response was found
                  to be strongly nonlinear in both regions studied, in
                  agreement with previous findings. The observed
                  nonlinearities are consistent with a model with a
                  nonlinear step from stimulus to neural activity, a
                  linear step from neural activity to CBF change, and
                  a nonlinear step from CBF change to BOLD signal
                  change. Hum. Brain Mapping 13:1-12, 2001. ? 2001
                  Wiley-Liss, Inc.}
}
@ARTICLE{mosher92,
  author = {Mosher, J. C. and Lewis, P. S. and Leahy, R. M.},
  title = {Multiple Dipole Modeling and Localization from
                  Spatio-Temporal {MEG} data},
  year = 1992,
  journal = {IEEE Trans. Biomed. Eng.},
  volume = 39,
  pages = {541-553},
  modified = {faugeras},
  number = 6,
  abstract = {The authors present general descriptive models for
                  spatiotemporal MEG (magnetoencephalogram) data and
                  show the separability of the linear moment
                  parameters and nonlinear location parameters in the
                  MEG problem. A forward model with current dipoles in
                  a spherically symmetric conductor is used as an
                  example: however, other more advanced MEG models, as
                  well as many EEG (electroencephalogram) models, can
                  also be formulated in a similar linear algebra
                  framework. A subspace methodology and computational
                  approach to solving the conventional least-squares
                  problem is presented. A new scanning approach,
                  equivalent to the statistical MUSIC method, is also
                  developed. This subspace method scans
                  three-dimensional space with a one-dipole model,
                  making it computationally feasible to scan the
                  complete head volume },
  url = {http://ieeexplore.ieee.org/xpl/abs_free.jsp?arNumber=141192}
}
@TECHREPORT{mosher97,
  author = {Mosher, J. C. and Leahy, R. M. and Lewis, P. S.},
  title = {Matrix kernels for the forward problem in {EEG} and
                  {MEG}},
  year = 1997,
  modified = {faugeras},
  institution = {Los Alamos},
  number = {LA-UR-97-3812},
  abstract = {The explicit form of the lead field is dependent on
                  the head modeling assumptions and sensor
                  configuration. The lead field can be partitioned
                  into the product of a vector dependent on sensor
                  characteristics and a matrix kernel dependent only
                  on head modeling assumptions. Here we review
                  analytic solutions for the spherical head model and
                  boundary element methods (BEMs) for arbitrary head
                  geometries. These results are presented in a unified
                  form in terms of their matrix kernels. Using this
                  formulation and a recently developed approximation
                  formula for EEG, based on the Berg parameters, we
                  present novel reformulations of the basic EEG and
                  MEG kernels that dispel the myth that EEG is
                  inherently more complicated to calculate than
                  MEG. We also present novel investigations of
                  different BEM methods and present evidence that
                  improvements over currently published E/MEG BEM
                  methods can be realized using alternative error
                  weighting methods.},
  url = {http://citeseer.nj.nec.com/mosher97matrix.html}
}
@ARTICLE{mosher99,
  author = {Mosher, J. C. and Leahy, R. M. and Lewis, P. S.},
  title = {{EEG} and {MEG}: Forward Solutions for Inverse
                  Methods},
  journal = {IEEE Trans. Biomed. Eng.},
  year = 1999,
  volume = 46,
  number = 3,
  pages = {245-260},
  month = MAR,
  abstract = {We present a unified treatment of analytical and
                  numerical solutions of the forward problem in a form
                  suitable for use in inverse methods. This
                  formulation is achieved through factorization of the
                  lead field into the product of the moment of the
                  elemental current dipole source with a kernel matrix
                  that depends on the head geometry and source and
                  sensor locations, and a sensor matrix that models
                  sensor orientation and gradiometer effects in MEG
                  and differential measurements in EEG.}
}
@ARTICLE{munck93,
  author = {{de} Munck, J. C. and Peters, J. M.},
  title = {A Fast Method to Compute the Potential in the
                  Multisphere Model},
  journal = {IEEE Trans. Biomed. Eng.},
  year = 1993,
  volume = 40,
  number = 11,
  pages = {1166-1175},
  month = NOV,
  abstract = {The infinite series analytic solution to the
                  multilayer isotropic model is presented in Cartesian
                  coordinates and the dipole moment clearly
                  separated. }
}
@MISC{neurofem-sw,
  key = {NeuroFEM},
  title = {Finite element software for fast computation of the
                  forward solution in {EEG}/{MEG} source localisation},
  note = {{Max Planck Institute for Human Cognitive and Brain
                  Sciences}},
  url = {http://www.neurofem.com/},
  urldate = {2005-05-09},
  year = 2005
}
@MISC{nielsenbib-segm,
  author = {Nielsen, F. {\AA}.},
  title = {Bibliography of Segmentation in Neuroimaging},
  url = {http://www.imm.dtu.dk/~fn/bib/Nielsen2001BibSegmentation/},
  urldate = {2004-10-14},
  year = 2001
}
@BOOK{nunez81,
  author = {Nunez, P. L.},
  title = {Electric Fields of the Brain: The Neurophysics of
                  {EEG}},
  publisher = {New York: Oxford University Press},
  year = 1981
}
@ARTICLE{obrien94,
  author = {O'Brien, M. S. and Sinclair, A. N. and Kramer, S. },
  title = {Recovery of a Sparse Spike Time Series by $L_1$ Norm
                  Deconvolution},
  journal = {IEEE Trans. Signal Proccessing},
  pages = {3353-3365},
  year = 1994,
  volume = 42,
  number = 12,
  abstract = {An L1 norm minimization scheme is applied to the
                  determination of the impulse response vector h of
                  flaws detected in practical examples of ultrasonic
                  nondestructive evaluation in CANDU nuclear
                  reactors. For each problem, parametric programming
                  is applied to find the optimum value of the damping
                  parameter that will yield the best estimate of h
                  according to a quantified performance factor. This
                  performance factor is based on a quantified analysis
                  of the transitions in estimates of h as the damping
                  parameter is varied over a wide range of possible
                  values. It is shown that for the examined cases in
                  which the true impulse response is a sparsely filled
                  spike strain, the L1 norm provides significantly
                  better results than the more commonly used L2 norm
                  minimization schemes. These results are shown to be
                  consistent with theoretical predictions },
  url = {http://ieeexplore.ieee.org/xpl/abs_free.jsp?arNumber=340772}
}
@ARTICLE{pascual-marqui94,
  author = {Pascual-Marqui, R. D. and Michel, C. M. and Lehman,
                  D.},
  title = {Low resolution electromagnetic tomography: A new
                  method for localizing electrical activity of the
                  brain},
  journal = {Int. J. Psychophysiol.},
  year = 1994,
  volume = 18,
  pages = {49-65}
}
@ARTICLE{pascual-marqui99,
  author = {Pascual-Marqui, R. D.},
  title = {Review of Methods for Solving the {EEG} Inverse
                  Problem},
  journal = {Int. J. Bioelectromag.},
  year = 1999,
  volume = 1,
  number = 1,
  pages = {75-86},
  url-pdf = {http://www.unizh.ch/keyinst/NewLORETA/TechnicalDetails/TechnicalDetails.pdf},
  url = {http://www.ijbem.org/volume1/number1/html/ar10.htm},
  urldate = {2005-05-09}
}
@INCOLLECTION{paulesu-etal97,
  author = {Paulesu, R. S. and Frackowiak, R. S. J. and Bottini,
                  G.},
  editor = {Frackowiak, R. S. J.},
  booktitle = {Human brain function},
  title = {Maps of somatosensory systems},
  publisher = {Academic Press},
  year = 1997,
  address = {San Diego, CA},
  pages = 528,
  annote = {'sensory motor paradox'}
}
@ARTICLE{pflieger01,
  author = {Pflieger, M. E. and Greenblatt, R. E.},
  title = {Nonlinear Analysis of Multimodal Dynamic Brain
                  Imaging Data},
  journal = {Int. J. Bioelectromag.},
  year = 2001,
  volume = 3,
  number = 1,
  keywords = {Fusion},
  abstract = {In the context of realizing the functional
                  requirements of a task, brain dynamics organize
                  brain activities that cause biophysical and
                  physiological signals, which the instruments of
                  various neuroimaging modalities can measure. An
                  ultimate goal is to make joint inferences about the
                  underlying activity, dynamics, and functions by
                  exploiting complementary information from multimodal
                  datasets, acquired from the same subject who
                  performed the same task. An intermediate problem is
                  to design cross-modal analyses that improve the
                  spatial and temporal resolution of one modality by
                  incorporating complementary information from another
                  modality. Given that M/EEG and fMRI BOLD signals are
                  complementary in time and space with respect to a
                  common subspace of brain activity, is there an
                  fMRI-related M/EEG analysis that spatially and
                  temporally enhances the M/EEG signal? Likewise, is
                  there an M/EEG-related fMRI analysis that temporally
                  and spatially enhances the BOLD signal? A
                  theoretical principle is to design cross-modal
                  analyses that maximize the dynamic coupling between
                  jointly observed signals within the framework of
                  nonlinear system identification. In particular, we
                  define a linear spatial estimator that maximizes the
                  empirical coupling of the estimated M/EEG source
                  activity as driven by local BOLD signal, and a
                  nonlinear dynamic transform that maximizes the
                  coupling of BOLD signal as driven by the estimated
                  M/EEG signal. The latter transformation can be the
                  basis for fMRI statistical parametric maps that
                  couple more tightly with neuronal activity compared
                  with task-derived maps. For M/EEG and fMRI datasets
                  obtained from different sessions, we describe a
                  method of temporal alignment that uses separately
                  identified nonlinear system models to simulate
                  "virtual simultaneous" datasets. The critical
                  criterion for empirical evaluation of these methods
                  is between-session reliability.},
  url = {http://www.ijbem.org/volume3/number1/greenblatt/index.htm},
  urldate = {2005-05-09}
}
@INCOLLECTION{ripp83,
  author = {Ripp, J.},
  editor = {Williamson and Romani and Kaufman and Modena},
  title = {Physical concepts and mathematical models},
  publisher = {Plenum Press},
  year = {1983},
  booktitle = {Biomagnetism: An interdisciplinary approach},
  address = {New York},
  pages = {101-139}
}
@ARTICLE{roy-sherrington1890,
  author = {Roy, C. S. and Sherrington, C. S.},
  title = {On the regulation of the blood-supply of the brain},
  journal = {J. Physiol. (London)},
  year = 1890,
  volume = 11,
  pages = {85-108}
}
@MISC{rumbatools-sw,
  author = {Bly, B. M. and Rebbechi, D.},
  title = {Software tools for brain imaging data analysis},
  url = {http://www.rumba.rutgers.edu/soft/},
  urldate = {2004-10-04},
  year = 2004
}
@ARTICLE{sabbatini97,
  author = {Sabbatini, R. M. E.},
  title = {Mapping the Brain},
  journal = {Brain & Mind},
  year = 1997,
  month = AUG # {/} # SEP,
  url = {http://www.epub.org.br/cm/n03/tecnologia/eeg.htm}
}
@ARTICLE{scherg88,
  author = {Scherg, M.},
  title = {Dipole source analysis: a key to understanding scalp
                  maps},
  journal = {Electroencephalogr. Clin. Neurophysiol.},
  year = 1988,
  volume = 70,
  number = 3,
  pages = 70
}
@ARTICLE{schmidt-etal99a,
  author = {Schmidt, D. M. and George, J. S. and Wood, C. C.},
  title = {Bayesian inference applied to the electromagnetic
                  inverse problem},
  journal = {Hum. Brain Mapp.},
  year = 1999,
  volume = 7,
  number = 3,
  pages = {195-212},
  abstract = { We present a new approach to the electromagnetic
                  inverse problem that explicitly addresses the
                  ambiguity associated with its ill-posed
                  character. Rather than calculating a single ``best''
                  solution according to some criterion, our approach
                  produces a large number of likely solutions that
                  both fit the data and any prior information that is
                  used. Whereas the range of the different likely
                  results is representative of the ambiguity in the
                  inverse problem even with prior information present,
                  features that are common across a large number of
                  the different solutions can be identified and are
                  associated with a high degree of probability. This
                  approach is implemented and quantified within the
                  formalism of Bayesian inference, which combines
                  prior information with that of measurement in a
                  common framework using a single measure. To
                  demonstrate this approach, a general neural
                  activation model is constructed that includes a
                  variable number of extended regions of activation
                  and can incorporate a great deal of prior
                  information on neural current such as information on
                  location, orientation, strength, and spatial
                  smoothness. Taken together, this activation model
                  and the Bayesian inferential approach yield
                  estimates of the probability distributions for the
                  number, location, and extent of active regions. Both
                  simulated MEG data and data from a visual evoked
                  response experiment are used to demonstrate the
                  capabilities of this approach.}
}
@ARTICLE{schwartz96,
  author = {Schwartz, D. P. and Poiseau, E. and Lemoine, D. and
                  Barillot, C.},
  title = {Registration of {MEG/EEG} Data with {3D} {MRI}:
                  Methodology and Precision Issues },
  journal = {Brain Topogr.},
  volume = 9,
  number = 1,
  year = 1996,
  pages = {101-116},
  month = {Winter},
  abstract = {Mapping neuro-physiological functions to high
                  resolution MRI is an effective means to evaluate
                  localization reconstructions and to exhibit the
                  spatio-temporal aspects of dynamic functional
                  processes. The registration step needed between
                  MEG/EEG and MRI is a source of error which, for the
                  worse cases may be greater than errors related to
                  the localization algorithms. Several registration
                  methods can be used: those based on fiducial markers
                  and those based on surface matching. The aim of this
                  paper is to propose a fully automatic surface
                  matching method and to discuss its extended
                  theoretical and experimental evaluation. The
                  registration procedure matches the skin surface,
                  segmented from MRI, and a digitized description of
                  the head performed with a 3D tracker during the
                  MEG/EEG examination. The registration uncertainties
                  at the edges of the MRI volume were estimated to be
                  between 2 and 3 mm. In comparison with commonly used
                  manual methods the improvement in accuracy is
                  significant. Registration uncertainties are smaller
                  than the localization uncertainties usually
                  observed. By minimizing manual intervention, the
                  reliability of the registration process is increased
                  and the accuracy is stabilized. With this automatic
                  registration method the fusion of MEG/EEG
                  localizations with MRI anatomical data gives highly
                  significant information. Finally the accuracy
                  obtained allows the use of complex anatomical
                  constraints in the localization process without
                  introducing large modelling errors.},
  url = {http://membres.lycos.fr/dyonis/registration/main.html},
  urldate = {2004-08-08}
}
@INCOLLECTION{speckmann-elger,
  author = {Speckmann, E. J. and Elger, C.},
  editor = {Niedermeyer, E. and Lopes da Silva, F.},
  title = {Introduction to the neurophysiological basis of the
                  {EEG} and DC potentials},
  publisher = {Baltimore, MD: Williams & Wilkins},
  booktitle = {Electroencephalography: basic principles, clinical
                  applications, and related fields},
  year = 1999,
  pages = {15-27}
}
@ARTICLE{supek-aine93,
  author = {Supek, S. and Aine, C. J.},
  title = {Simulation studies of multiple dipole neuromagnetic
                  source localization: model order and limits of
                  source resolution},
  journal = {IEEE Trans. Biomed. Eng.},
  year = 1993,
  volume = 40,
  number = 6,
  pages = {529-540},
  abstract = {Numerical simulation studies were performed using a
                  multiple dipole source model and a spherical
                  approximation of the head to examine how the
                  resolution of simultaneously active neuromagnetic
                  sources depends upon: 1) source modeling assumptions
                  (i.e., number of assumed dipoles); 2) actual source
                  parameters (e.g., location, orientation, and
                  moment); and 3) measurement errors. Forward
                  calculations were conducted for a series of source
                  configurations in which the number of dipoles,
                  specific dipole parameters, and noise levels were
                  systematically varied. Simulated noisy field
                  distributions were fit by multiple dipole models of
                  increasing model order (1, 2,..., 6 and alternative
                  statistical approaches (i.e., percent of variance,
                  reduced chi-square, and F-ratio) were compared for
                  their effectiveness in determining adequate model
                  order. Limits of spatial resolution were established
                  for a variety of multi-source configurations and
                  noise conditions. Implications for the analysis of
                  empirical data are discussed. }
}
@MISC{surefit-sw,
  title = {Surface Reconstruction by Filtering and Intensity
                  Transformations},
  author = {Van Essen, D.},
  url = {http://brainvis.wustl.edu/},
  urldate = {2004-10-04},
  year = 2004
}
@ARTICLE{trujillo-barreto01,
  author = {Trujillo-Barreto, N. J. and Mart\'inez-Montes,
                  E. and Melie-Garc\'ia, L. and Vald\'es-Sosa, P. A.},
  title = {A Symmetrical Bayesian Model for f{MRI} and
                  {EEG}/{MEG} {N}euroimage Fusion},
  journal = {Int. J. Bioelectromag.},
  year = 2001,
  volume = 3,
  number = 1,
  abstract = {A new method for EEG/MEG and fMRI data fusion
                  (EEG/MEG fMRI) is presented. A linear model for both
                  kinds of measurements is used, and the main
                  assumption is that the variability of the estimated
                  activation in both cases (variance and covariance
                  matrix) is essentially the same, except for a
                  scaling factor. Bayesian Theory is used as a natural
                  framework for including the prior information
                  associated with both kinds of imaging
                  techniques. Additionally it allows the automatic
                  estimation of all the "tuning parameters" in the
                  model. The Point Spread Function (PSF) for the new
                  model is computed, and the results are compared with
                  methods that use only electric measurements. This
                  work shows that the new methodology has a superior
                  performance according to many of the quality
                  measures used to characterize electrophysiological
                  tomographic techniques. It is also demonstrated that
                  previous procedures, based on thresh holding the
                  fMRI by means of Statistical Parametric Mapping
                  (SPM), and using the resultant active regions as
                  constraints for solving the EEG/MEG inverse problem
                  (fMRI->EEG/MEG), is biased by the fMRI
                  estimation. The use of the new method is illustrated
                  in the analysis of a Somatosensory MEG-fMRI
                  experiment.},
  url = {http://www.ijbem.org/volume3/number1/valdesosa/},
  urldate = {2004-10-06}
}
@INPROCEEDINGS{vrba-robinson00,
  author = {Vrba, J. and Robinson, S. E.},
  title = {Differences between {S}ynthetic {A}perture
                  {M}agnetometry ({SAM}) and linear beamformers},
  booktitle = {12th Int Conf Biomagnet},
  year = 2000,
  editor = {Nenonen, J. and Ilmoniemi, R.J. and Katila, T.},
  organization = {Biomag2000},
  biomag-id = {pdf/0681},
  series = {12th International Conference on Biomagnetism},
  address = {Helsinki, Finland},
  month = AUG,
  isbn = {951-22-5402-6},
  url = {http://biomag2000.hut.fi/papers/0681.pdf},
  urldate = {2004-10-21}
}
@ARTICLE{wagner01,
  author = {Wagner, M. and Fuchs, M.},
  title = {Integration of Functional {MRI}, Structural {MRI},
                  {EEG}, and {MEG}},
  journal = {Int. J. Bioelectromag.},
  year = 2001,
  volume = 3,
  number = 1,
  keywords = {Fusion},
  abstract = {Depending on the available information, different
                  co-registration methods for merging structural
                  Magnetic Resonance Imaging (sMRI) and fMRI
                  coordinate systems may be useful. The usage of
                  scanner coordinates as well as landmark-, surface-,
                  and volume-based registration is discussed. Dipole
                  fits can benefit from fMRI constraints: Meaningful
                  seed points for source locations are obtained. A
                  reconstructed dipole in the vicinity of each fMRI
                  hotspot yields the corresponding source time
                  course. Spatially unconstrained dipoles are then
                  necessary to account for remaining activity. Current
                  density reconstructions react upon fMRI constraints
                  in two ways: Activity in the vicinity of fMRI
                  hotspots is bundled. Remaining activity can be
                  localized correctly, if its field distribution
                  cannot be generated from sources within the
                  hotspots, and if the fMRI constraint is imposed
                  softly.},
  url = {http://www.ijbem.org/volume3/number1/wagner/index.htm},
  urldate = {2005-05-09}
}
@ARTICLE{wang-etal92-dup,
  author = {Wang, J. Z. and Williamson, S. J. and Kaufman, L.},
  title = {Magnetic source images determined by a lead-field
                  analysis: the unique minimum-norm least-squares
                  estimation},
  journal = {IEEE Trans. Biomed. Eng.},
  year = 1992,
  volume = 39,
  number = 7,
  pages = {665-675},
  abstract = { The minimum norm least-squares approach based on
                  lead field theory provides a unique inverse solution
                  for a magnetic source image that is the best
                  estimate in the least-squares sense. This has been
                  applied to determine the source current distribution
                  when the primary current is confined to a surface or
                  set of surfaces. In model simulations of cortical
                  activity of the human brain, the magnetic field
                  pattern across the scalp is interpreted with prior
                  knowledge of anatomy to yield a unique magnetic
                  source image across a portion of cerebral cortex,
                  without resort to an explicit source model. }
}
@BOOK{william-etal95,
  author = {Orrison, Jr., W. W. and Lewine, J. D. and Sanders,
                  J. A. and Hartshorne, M. F.},
  title = {Functional Brain Imaging},
  year = 1995,
  publisher = {Mosby},
  modified = {faugeras}
}
@INCOLLECTION{wolters-etal01,
  author = {Wolters, C. H. and Anwander, A. and Koch, M. A. and
                  Reitzinger, S. and Kuhn, M. and Svens{\'e}n, M.},
  title = {Influence of Head Tissue Conductivity Anisotropy on
                  Human {EEG} and MEG using Fast High Resolution
                  Finite Element Modeling, based on a Parallel
                  Algebraic Multigrid Solver},
  booktitle = {Forschung und wissenschaftliches Rechnen},
  publisher = {Max-Planck-Gesselschaft, M{\"u}nchen},
  editor = {Plesser, T.  and Wittenburg, P.},
  optnote = {Heinz-Billing-Preis Essay},
  year = 2001,
  abstract = {Accuracy and time play an important role in medical
                  and neuropsychological diagnosis and research. The
                  inverse problem in the field of Electro- and
                  MagnetoEncephaloGraphy requires the repeated
                  simulation of the field distribution for a given
                  dipolar source in the human brain using a
                  volume-conduction model of the head. High resolution
                  finite element head modeling allows the inclusion of
                  tissue conductivity inhomogeneities and
                  anisotropies. We will present new approaches for
                  individually determining the direction-dependent
                  conductivities of skull and brain white matter,
                  based on non-invasive multimodal magnetic resonance
                  imaging data, and for generating a high resolution
                  realistic anisotropic finite element model of the
                  human head. Error estimations will indicate the
                  necessity of the chosen complex forward model. The
                  finite element approach within the inverse problem
                  leads to a sparse, large scale, linear equation
                  system with many different right hand sides to be
                  solved. The presented solution process is based on a
                  parallel algebraic multigrid method. It is shown
                  that very short computation times can be achieved
                  through the combination of the multigrid technique
                  and the parallelization on distributed memory
                  computers. The iterative solver approach is shown to
                  be stable towards modeling of tissue anisotropy. A
                  solver time comparison to a classical parallel
                  Jacobi preconditioned conjugate gradient method is
                  given.},
  pages = {111-157},
  url = {http://www.billingpreis.mpg.de/hbp01/wolters.pdf},
  urldate = {2004-07-05}
}
@INPROCEEDINGS{yoh03,
  author = {Halchenko, Y. O. and Pearlmutter, B. A. and Hanson,
                  S. J. and Zaimi, A.},
  title = {Fusion of Functional Brain Imaging Modalities via
                  Linear Programming},
  booktitle = {NFSI},
  keywords = {Fusion},
  year = 2003,
  address = {Chiety, Italy},
  url = {http://www.onerussian.com/Sci/pubs/lpnfsi2003.pdf}
}
@ARTICLE{zhang95,
  author = {Zhang, Z.},
  title = {A fast method to compute surface potentials
                  generated by dipoles within multilayer anisotropic
                  spheres},
  journal = {Phys. Med. Biol.},
  year = {1995},
  volume = {40},
  pages = {335-349},
  month = MAY
}

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