Mapping function in the human brain with magnetoencephalography, anatomical magnetic resonance imaging, and functional magnetic resonance imaging.

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 neuro-imaging methods.