Hierarchical Bayesian inference for the EEG inverse problem using realistic FE head models: Depth localization and source separation for focal primary currents

Volume: 61, Issue: 4, Pages: 1364 - 1382
Published: Jul 1, 2012
Abstract
The estimation of the activity-related ion currents by measuring the induced electromagnetic fields at the head surface is a challenging and severely ill-posed inverse problem. This is especially true in the recovery of brain networks involving deep-lying sources by means of EEG/MEG recordings which is still a challenging task for any inverse method. Recently, hierarchical Bayesian modeling (HBM) emerged as a unifying framework for current...
Paper Details
Title
Hierarchical Bayesian inference for the EEG inverse problem using realistic FE head models: Depth localization and source separation for focal primary currents
Published Date
Jul 1, 2012
Journal
Volume
61
Issue
4
Pages
1364 - 1382
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