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STATE-SPACE SOLUTIONS TO THE DYNAMIC MAGNETOENCEPHALOGRAPHY INVERSE PROBLEM USING HIGH PERFORMANCE COMPUTING.
PARAMETER ESTIMATION AND DYNAMIC SOURCE LOCALIZATION FOR THE MAGNETOENCEPHALOGRAPHY (MEG) INVERSE PROBLEM.
A spatiotemporal dynamic distributed solution to the MEG inverse problem.
A fast iterative greedy algorithm for MEG source localization.
A spatially-regularized dynamic source localization algorithm for EEG.
A Subspace Pursuit-based Iterative Greedy Hierarchical solution to the neuromagnetic inverse problem.
Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG.