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Performance Evaluation of the Champagne Source Reconstruction Algorithm on Simulated and Real M/EEG Data

In this paper, we present an extensive performance evaluation of a novel source localization algorithm, Champagne. It is derived in an empirical Bayesian framework that yields sparse solutions to the inverse problem. It is robust to correlated sources and learn the statistics of non-stimulus-evoked...

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Bibliografische gegevens
Hoofdauteurs: Owen, Julia P., Wipf, David P., Attias, Hagai T., Sekihara, Kensuke, Nagarajan, Srikantan S.
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: 2011
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Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC4096349/
https://ncbi.nlm.nih.gov/pubmed/22209808
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2011.12.027
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