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MEG Source Localization Using Invariance of Noise Space

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  • Junpeng Zhang
  • Tommi Raij
  • Matti Hämäläinen
  • Dezhong Yao

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.

Suggested Citation

  • Junpeng Zhang & Tommi Raij & Matti Hämäläinen & Dezhong Yao, 2013. "MEG Source Localization Using Invariance of Noise Space," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-15, March.
    • Handle: RePEc:plo:pone00:0058408
    DOI: 10.1371/journal.pone.0058408
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