Simultaneous EEG Source and Forward Model Reconstruction (SOFOMORE) Using a Hierarchical Bayesian Approach |
| |
Authors: | Carsten Stahlhut Morten Mørup Ole Winther Lars Kai Hansen |
| |
Affiliation: | (1) Department of Informatics and Mathematical Modelling, Technical University of Denmark, Richard Petersens Plads, 2800 Kgs. Lyngby, Denmark |
| |
Abstract: | 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. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|