Journal article
Simultaneous EEG Source and Forward Model Reconstruction (SOFOMORE) using a Hierarchical Bayesian Approach
We present an approach to handle forward model uncertainty for EEG source reconstruction. A stochastic forward model representation is motivated by the many random contributions to the path from sources to measurements including the tissue conductivity distribution, the geometry of the cortical surface, and electrode positions.
We first present a hierarchical Bayesian framework for EEG source localization that jointly performs source and forward model reconstruction (SOFOMORE). Secondly, we evaluate the SOFOMORE approach by comparison with source reconstruction methods that use fixed forward models. Analysis of simulated and real EEG data provide evidence that reconstruction of the forward model leads to improved source estimates.
Language: | English |
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Publisher: | Springer US |
Year: | 2011 |
Pages: | 431-444 |
Journal subtitle: | For Signal, Image, and Video Technology (formerly the Journal of Vlsi Signal Processing Systems for Signal, Image, and Video Technology) |
ISSN: | 19398115 and 19398018 |
Types: | Journal article |
DOI: | 10.1007/s11265-010-0527-0 |
ORCIDs: | Mørup, Morten , Winther, Ole and Hansen, Lars Kai |