Nonparametric Statistical Thresholding for Sparse Magnetoencephalography Source Reconstructions

Nonparametric Statistical Thresholding for Sparse Magnetoencephalography Source Reconstructions

Uncovering brain activity from 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 robust to these confounds. I...

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Bibliographic Details
Main Authors: Julia Parsons Owen, Kensuke eSekihara, Srikantan S. Nagarajan
Format: Article
Language:English
Published: Frontiers Media S.A. 2012-12-01
Series:Frontiers in Neuroscience
Subjects:
Magnetoencephalography
nonparametric statistics
sparse source reconstructions
maximal stastic
noninvasive brain imaging
maximal statistic
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2012.00186/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fnins.2012.00186/full

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