SOFOMORE: combined EEG source and forward model reconstruction

  • Authors:

  • Carsten Stahlhut;Morten Mørup;Ole Winther;Lars Kai Hansen

  • Affiliations:

  • Technical University of Denmark, Department of Informatics and Mathematical Modelling, Lyngby, Denmark;Technical University of Denmark, Department of Informatics and Mathematical Modelling, Lyngby, Denmark;Technical University of Denmark, Department of Informatics and Mathematical Modelling, Lyngby, Denmark;Technical University of Denmark, Department of Informatics and Mathematical Modelling, Lyngby, Denmark

  • Venue:
  • ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
  • Year:
  • 2009

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Abstract

We propose a new EEG source localization method that simultaneously performs SOurce and FOrward MOdel REconstruction (SOFOMORE) in a hierarchical Bayesian framework. Reconstruction of the forward model is motivated by the many uncertainties involved in the forward model, including the representation of the cortical surface, conductivity distribution, and electrode positions. We demonstrate in both simulated and real EEG data that reconstruction of the forward model improves localization of the underlying sources.