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MEG Source Localization Using Invariance of Noise Space
2013
PLoS ONE
We propose INvariance of Noise (INN) space as a novel method for source localization of magnetoencephalography (MEG) data. The method is based on the fact that modulations of source strengths across time change the energy in signal subspace but leave the noise subspace invariant. We compare INN with classical MUSIC, RAP-MUSIC, and beamformer approaches using simulated data while varying signal-to-noise ratios as well as distance and temporal correlation between two sources. We also demonstrate
doi:10.1371/journal.pone.0058408
pmid:23505502
pmcid:PMC3591341
fatcat:m7dtgq23and4tj5utfrnkgjp4m