Abstract
EEG source reconstruction involves solving an inverse problem that is highly ill-posed and dependent on a generally fixed forward propagation model. In this contribution we compare a low and high density EEG setup’s dependence on correct forward modeling. Specifically, we examine how different forward models affect the source estimates obtained using four inverse solvers Minimum-Norm, LORETA, Minimum-Variance Adaptive Beamformer, and Sparse Bayesian Learning.
Original language | English |
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Title of host publication | 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |
Publisher | IEEE |
Publication date | 2012 |
Pages | 1538-1541 |
ISBN (Print) | 978-1-4244-4119-8 |
ISBN (Electronic) | 978-1-4244-4120-4 |
DOIs | |
Publication status | Published - 2012 |
Event | 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Hilton Bayfront Hotel, San Diego, United States Duration: 28 Aug 2012 → 1 Sept 2012 Conference number: 34 |
Conference
Conference | 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
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Number | 34 |
Location | Hilton Bayfront Hotel |
Country/Territory | United States |
City | San Diego |
Period | 28/08/2012 → 01/09/2012 |
Series | I E E E Engineering in Medicine and Biology Society. Conference Proceedings |
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ISSN | 2375-7477 |