MAPPING FUNCTION IN THE HUMAN BRAIN WITH MAGNETOENCEPHALOGRAPHY, ANATOMICAL MAGNETIC-RESONANCE-IMAGING, AND FUNCTIONAL MAGNETIC-RESONANCE-IMAGING

Integrated analyses of human anatomical and functional measurements of fer a powerful paradigm for human brain mapping, Magnetoencephalograph y (MEG) and EEG provide excellent temporal resolution of neural popula tion dynamics as well as capabilities for source localization. Anatomi cal magnetic resonance imaging (MRI) provides excellent spatial resolu tion of head and brain anatomy, whereas functional MRI (fMRI) techniqu es provide an alternative measure of neural activation based on associ ated hemodynamic changes. These methodologies constrain and complement each other and can thereby improve our interpretation of functional n eural organization. We have developed a number of computational tools and techniques for the visualization, comparison, and integrated analy sis of multiple neuroimaging techniques. Construction of geometric ana tomical 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 enh ance the accuracy of source-localization procedures. We have begun to apply these techniques for studies of the functional organization of t he human visual system. Such studies have demonstrated multiple, funct ionally distinct visual areas that can be resolved on the basis of the ir locations, temporal dynamics, and differential sensitivity to stimu lus parameters. Our studies have also produced evidence of internal re tinotopic organization in both striate and extrastriate visual areas b ut have disclosed organizational departures from classical models. Com parative studies of MEG and fMRI suggest a reasonable but imperfect co rrelation between electrophysiological and hemodynamic responses. We h ave demonstrated a method for the integrated analysis of fMRI and MEG, and we outline strategies for improvement of these methods. By combin ing multiple measurement techniques, we can exploit the complementary strengths and transcend the limitations of the individual neuroimaging methods.