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N. J. Trujillo-Barreto, E. Mart\'inez-Montes, L. Melie-Garc\'ia, P. A. Valdés-Sosa. A Symmetrical Bayesian Model for fMRI and EEG/MEG Neuroimage Fusion. Bioelectromagnetism, 3(1), 2001.


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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


N. J. Trujillo-Barreto
E. Mart\'inez-Montes
L. Melie-Garc\'ia

BibTex Reference

   Author = {Trujillo-Barreto, N. J. and Mart\'inez-Montes, E. and Melie-Garc\'ia, L. and Valdés-Sosa, P. A.},
   Title = {A Symmetrical Bayesian Model for f{MRI} and {EEG}/{MEG} {N}euroimage Fusion},
   Journal = {Bioelectromagnetism},
   Volume = {    3},
   Number = {1},
   Year = {2001}

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