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Separation of phase-locked sources in pseudo-real MEG data

Miguel S. B. Almeida,J. Bioucas-Dias,Ricardo Vigário

Published 2013 in EURASIP Journal on Advances in Signal Processing

ABSTRACT

This article addresses the blind separation of linear mixtures of synchronous signals (i.e., signals with locked phases), which is a relevant problem, e.g., in the analysis of electrophysiological signals of the brain such as the electroencephalogram and the magnetoencephalogram (MEG). Popular separation techniques such as independent component analysis are not adequate for phase-locked signals, because such signals have strong mutual dependency. Aiming at unmixing this class of signals, we have recently introduced the independent phase analysis (IPA) algorithm, which can be used to separate synchronous sources. Here, we apply IPA to pseudo-real MEG data. The results show that this algorithm is able to separate phase-locked MEG sources in situations where the phase jitter (i.e., the deviation from the perfectly synchronized case) is moderate. This represents a significant step towards performing phase-based source separation on real data.

PUBLICATION RECORD

  • Publication year

    2013

  • Venue

    EURASIP Journal on Advances in Signal Processing

  • Publication date

    2013-02-22

  • Fields of study

    Computer Science, Engineering

  • Identifiers
    DOI 10.1186/1687-6180-2013-32
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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