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J. C. Mosher, R. M. Leahy, P. S. Lewis. Matrix kernels for the forward problem in EEG and MEG. Research Report Los Alamos, No 0, 1997.


The explicit form of the lead field is dependent on the head modeling assumptions and sensor configuration. The lead field can be partitioned into the product of a vector dependent on sensor characteristics and a matrix kernel dependent only on head modeling assumptions. Here we review analytic solutions for the spherical head model and boundary element methods (BEMs) for arbitrary head geometries. These results are presented in a unified form in terms of their matrix kernels. Using this formulation and a recently developed approximation formula for EEG, based on the Berg parameters, we present novel reformulations of the basic EEG and MEG kernels that dispel the myth that EEG is inherently more complicated to calculate than MEG. We also present novel investigations of different BEM methods and present evidence that improvements over currently published E/MEG BEM methods can be realized using alternative error weighting methods


J. C. Mosher
R. Leahy
P. S. Lewis

BibTex Reference

   Author = {Mosher, J. C. and Leahy, R. M. and Lewis, P. S.},
   Title = {Matrix kernels for the forward problem in {EEG} and {MEG}},
   Number = {0},
   Institution = {Los Alamos},
   Year = {1997}

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