M/EEG+FMRI BIB

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.

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

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.

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

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.

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

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.

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.

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.

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.

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

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.

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

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%. .

Keywords: Adult ; *Electrodes ; Electroencephalography/*instrumentation ; Human ; Magnetic Resonance Imaging/*instrumentation ; Male ; Support, Non-U.S. Gov't

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.

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.

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.

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.

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.

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.

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.

Keywords: Animals ; Dogs ; Electrocardiography/*methods ; Mathematics ; *Models, Cardiovascular ; *Signal Processing, Computer-Assisted ; Support, U.S. Gov't, Non-P.H.S.

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.

Keywords: Brain Mapping/*instrumentation/methods ; Electromagnetic Fields ; Human ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; Neurons/*physiology ; *Phantoms, Imaging

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.

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

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.

Keywords: Analysis of Variance ; Brain Mapping ; Cerebral Cortex/*physiology ; *Computer Simulation ; *Electroencephalography ; Electrophysiology ; Human ; *Magnetic Resonance Imaging ; *Models, Neurological

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.

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.

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

Keywords: ICP

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.

Keywords: Adult ; Brain/*physiology ; *Brain Mapping ; Human ; Magnetic Resonance Imaging/*methods ; *Magnetoencephalography ; Support, Non-U.S. Gov't

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.

Keywords: Brain/physiology ; *Cerebrovascular Circulation ; Human ; *Models, Neurological ; *Oxygen Consumption ; *Regional Blood Flow ; Tomography, Emission-Computed

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.

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

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.

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.

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.

Keywords: Electroencephalography/*methods ; Head/*radiation effects ; Human ; Models, Theoretical ; Phantoms, Imaging ; Reproducibility of Results ; Skull/*radiation effects ; Time Factors

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.

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.

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.

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

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.

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

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.

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

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.

Keywords: Adult ; Analysis of Variance ; Brain Mapping/*methods ; Female ; Fingers/*physiology ; Human ; Least-Squares Analysis ; Male ; Motor Cortex/*physiology

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.

Keywords: Brain Mapping/instrumentation ; Cerebral Cortex/*anatomy & histology ; Human ; Image Processing, Computer-Assisted/*instrumentation ; Magnetic Resonance Imaging/*instrumentation ; Reference Values ; Software

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.

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

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.

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.

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.

Keywords: Human ; Image Enhancement ; Likelihood Functions ; Magnetic Resonance Imaging/*methods ; Models, Statistical ; *Probability Theory ; Sensitivity and Specificity ; Signal Processing, Computer-Assisted ; Statistics

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.

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

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.

Keywords: Brain/*physiology ; *Brain Mapping ; Cognition/*physiology ; Human ; *Magnetic Resonance Imaging/methods

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.

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.

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.

Keywords: Brain/*physiology ; Cerebrovascular Circulation/*physiology ; Hemodynamic Processes/physiology ; *Magnetic Resonance Imaging ; *Models, Cardiovascular ; *Models, Neurological ; *Nonlinear Dynamics ; Support, Non-U.S. Gov't

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.

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

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.

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

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.

Keywords: *Brain Mapping ; *Computer Simulation ; Electroencephalography/*methods/standards ; Evoked Potentials, Somatosensory/physiology ; Head ; Human ; Image Processing, Computer-Assisted ; Magnetoencephalography/*methods/standards ; Software

Keywords: Animals ; Cats ; Cattle ; Dogs ; Electric Conductivity ; *Electrodiagnosis ; *Electrophysiology ; Guinea Pigs ; Human ; Rabbits

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.

Keywords: Algorithms ; *Artifacts ; Echo-Planar Imaging/methods ; *Electroencephalography/methods ; Human ; *Magnetic Resonance Imaging/methods ; *Signal Processing, Computer-Assisted ; Support, Non-U.S. Gov't

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.

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.

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).

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.

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.

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

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.

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

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.

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

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.

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.

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.

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.

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

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 degr