Sparse Source EEG Imaging with the Variational Garrote

Sofie Therese Hansen, Carsten Stahlhut, Lars Kai Hansen

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Abstract

EEG imaging, the estimation of the cortical source distribution from scalp electrode measurements, poses an extremely ill-posed inverse problem. Recent work by Delorme et al. (2012) supports the hypothesis that distributed source solutions are sparse. We show that direct search for sparse solutions as implemented by the Variational Garrote (Kappen, 2011) provides excellent estimates compared with other widely used schemes, is computationally attractive, and by its separation of ’where’ and ’what’ degrees of freedom paves the road for the introduction of genuine prior information.
Original languageEnglish
Title of host publication2013 International Workshop on Pattern Recognition in Neuroimaging (PRNI)
PublisherIEEE
Publication date2013
Pages106-109
ISBN (Print)978-0-7695-5061-9
DOIs
Publication statusPublished - 2013
Event3rd International Workshop on Pattern Recognition in NeuroImaging (PRNI 2013) - Philadelphia, PA, United States
Duration: 22 Jun 201324 Jun 2013
http://www.prni.org/

Conference

Conference3rd International Workshop on Pattern Recognition in NeuroImaging (PRNI 2013)
CountryUnited States
CityPhiladelphia, PA
Period22/06/201324/06/2013
Internet address

Keywords

  • EEG
  • Imaging
  • Variational Garrote
  • LASSO
  • Sparse Bayesian Modeling
  • Sparsity

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