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Non-Parametric Statistical Thresholding for Sparse Magnetoencephalography Source Reconstructions

Uncovering brain activity from magnetoencephalography (MEG) data requires solving an ill-posed inverse problem, greatly confounded by noise, interference, and correlated sources. Sparse reconstruction algorithms, such as Champagne, show great promise in that they provide focal brain activations robu...

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Hlavní autoři: Owen, Julia P., Sekihara, Kensuke, Nagarajan, Srikantan S.
Médium: Artigo
Jazyk:Inglês
Vydáno: Frontiers Media S.A. 2012
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC3530032/
https://ncbi.nlm.nih.gov/pubmed/23271990
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2012.00186
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