SOFOMORE: Combined EEG source and forward model reconstruction

Author

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

Author_Institution

Dept. of Inf. & Math. Modelling, Tech. Univ. of Denmark, Lyngby, Denmark

fYear

2009

fDate

June 28 2009-July 1 2009

Firstpage

450

Lastpage

453

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.

Keywords

Bayes methods; bioelectric phenomena; electrical conductivity; electroencephalography; medical signal processing; neurophysiology; signal reconstruction; signal representation; source separation; EEG source localization method; conductivity distribution; cortical surface representation; forward model reconstruction; hierarchical Bayesian framework; Bayesian methods; Brain modeling; Conductivity; Electrodes; Electroencephalography; Mathematical model; Sensor arrays; Solid modeling; Surface reconstruction; Uncertainty; EEG; distributed model; hierarchical Bayes; source reconstruction; uncertain forward model;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on

Conference_Location

Boston, MA

ISSN

1945-7928

Print_ISBN

978-1-4244-3931-7

Electronic_ISBN

1945-7928

Type

conf

DOI

10.1109/ISBI.2009.5193081

Filename

5193081