MEG Source Localization Using Invariance of Noise Space

Junpeng Zhang, Tommi Raij, Matti Hämäläinen, Dezhong Yao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


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.

Original languageEnglish (US)
Article numbere58408
JournalPloS one
Issue number3
StatePublished - Mar 7 2013

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)


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