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A multiresolution framework to MEG/EEG source imaging (2001)
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BibTeX
@MISC{Gavit01amultiresolution,
author = {L. Gavit and S. Baillet and JF Mangin and Jean-françois Mangin and L Garnero and J Pescatore and Line Garnero},
title = {A multiresolution framework to MEG/EEG source imaging},
year = {2001}
}
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Abstract
A new method based on a multiresolution approach for solving the ill-posed problem of brain electrical activity reconstruction from electroencephaloram (EEG)/magnetoencephalogram (MEG) signals is proposed in a distributed source model. At each step of the algorithm, a regularized solution to the inverse problem is used to constrain the source space on the cortical surface to be scanned at higher spatial resolution. We present the iterative procedure together with an extension of the ST-maximum a posteriori method [1] that integrates spatial and temporal a priori information in an estimator of the brain electrical activity. Results from EEG in a phantom head experiment with a real human skull and from real MEG data on a healthy human subject are presented. The performances of the multiresolution method combined with a nonquadratic estimator are compared with commonly used dipolar methods, and to minimum-norm method with and without multiresolution. In all cases, the proposed approach proved to be more efficient both in terms of computational load and result quality, for the identification of sparse focal patterns of cortical current density, than the fixed scale imaging approach.
Keyphrases
meg eeg source imaging multiresolution framework cortical current density new method inverse problem dipolar method real human skull priori information result quality ill-posed problem distributed source model phantom head experiment sparse focal pattern multiresolution method cortical surface multiresolution approach real meg data regularized solution computational load source space healthy human subject brain electrical activity nonquadratic estimator fixed scale posteriori method brain electrical activity reconstruction iterative procedure spatial resolution
