Spatio-Temporal MEG and EEG Source Estimation

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DESCRIPTION (Provided by Applicant): The purpose of this project is to develop, implement, analyze and evaluate methodologies for estimating the location, extent, and dynamic behavior of cortical neuronal populations that give rise to event-related electroencephalographic (EEG) and magnetoencephalographic (MEG) (E/MEG) signals. During the lifetime of this project we have developed Bayesian cortical imaging methods and multipolar source localization methods, both of which are able to localize focal neuronal populations in cortex. We have also developed fast, accurate forward models based on boundary element methods (BEMs). These developments are embodied in an interactive software package, BrainStorm, which is now available to the research community. Evaluation of our methods and software has been based on theoretical and Monte Carlo studies, studies using a human-skull phantom developed under this project, and applications to event-related EIMEG data. A high-resolution cortical surface, and skull, scalp, and brain surfaces for BEM calculations, are found using a series of automated processing steps applied to anatomical MRIs which are embodied in a second software package BrainSuite. For the proposed project period we plan to continue our investigations of the theoretical basis of E/MEG source estimation with the goal of better understanding the potentials and limitations of the modality. Our theoretical investigations will lead to improvements in forward and inverse methods and, importantly, a better understanding of the uncertainties implicit in these estimates. In verse methods will be based on the use of regularized signal-subspace localization of multipolar sources that can represent distributed neuronal populations. Cortical images will be obtained by re-mapping multipolar sources to cortex. We will develop tools for estimating location uncertainty directly from the measured data and estimated sources. These methods will be based on the bootstrap method in statistics and use of plug-in approximations to the Cramer Rao lower bounds. The cortical remapping methods will optionally allow the use of fMRI activation sites as prior information on possible source locations. A novel method will be developed for selection of event-related components in raw data for use in cases where stimulus-locked averaging obscures sources with highly variable latency. Improved forward models will be based on finite element methods (FEMs) applied to accurately segmented MRIs of the subjects head. For subjects for whom MRIs are not available, we will develop a generic head model based on BEM or FEM applied to an averaged head warped to a series of digitized scalp landmarks. Evaluation will be based on continued theoretical, simulation, and phantom studies. These technical developments will be incorporated in our BrainStorm and BrainSuite software packages which we will continue to maintain and enhance over the life of the project. Limited human studies of motor function using fMRI, MEG and EEG are planned for this project; broader applications of these methods in functional mapping and epilepsy will be realized through use of our software by our collaborators and other registered users.