The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-SIPI-294

“MEG-Based Imaging of Focal Neuronal Current Sources”

by James Phillips, Richard M. Leahy and John C. Mosher

December 1995

We describe a new approach to imaging neuronal current sources from measurements of the magnetoencephalogram (MEG) associated with sensory, motor, or cognitive brain activation. Previous approaches to this problem have concentrated on the use of weighted minimum norm inverse methods. While these methods ensure a unique solution, they do not introduce information specific to the MEG inverse problem, often producing overly smoothed solutions and exhibiting severe sensitivity to noise. We describe a Bayesian formulation of the inverse problem in which a Gibbs prior is constructed to reflect the sparse focal nature of neuronal current sources associated with evoked response data. We demonstrate the method with simulated and experimental phantom data, comparing its performance with several weighted minimum norm methods.

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