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Public Library of Science, PLoS ONE, 3(8), p. e58408, 2013

DOI: 10.1371/journal.pone.0058408

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MEG Source Localization Using Invariance of Noise Space

Journal article published in 2013 by Junpeng Zhang, Tommi Raij, Matti Hämäläinen, Dezhong Yao ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

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 the utility of INN with actual auditory evoked MEG responses in eight subjects. In all cases, INN performed well, especially when the sources were closely spaced, highly correlated, or one source was considerably stronger than the other.