- Authors:
-
- Stahlhut, Carsten ;
-
Mørup, Morten
;
Close
0000-0003-4985-4368
Cognitive Systems, Department of Informatics and Mathematical Modeling, Technical University of Denmark -
Winther, Ole
;
Close0000-0002-1966-3205
Cognitive Systems, Department of Informatics and Mathematical Modeling, Technical University of Denmark -
Hansen, Lars Kai
Close0000-0003-0442-5877
Cognitive Systems, Department of Informatics and Mathematical Modeling, Technical University of Denmark
- DOI:
- 10.1109/mlsp.2009.5306189
- Abstract:
- In this paper we propose an approach to handle forward model uncertainty for EEG source reconstruction. A stochastic forward model is motivated by the many uncertain contributions that form the forward propagation model including the tissue conductivity distribution, 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 model by comparison with source reconstruction methods that use fixed forward models. Simulated and real EEG data demonstrate that invoking a stochastic forward model leads to improved source estimates.
- ISBN:
- 9781424449477
- Type:
- Conference paper
- Language:
- English
- Published in:
- Ieee International Workshop on Machine Learning for Signal Processing, 2009. Mlsp 2009, 2009, p. 1-6
- Main Research Area:
- Science/technology
- Publication Status:
- Published
- Review type:
- Peer Review
- Conference:
- 2009 IEEE International Workshop on Machine Learning for Signal Processing, 2009
- Publisher:
- IEEE
- Submission year:
- 2009
- Scientific Level:
- Scientific
- ID:
- 108157781
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