MEG and Complex Systems

  • Gareth R. Barnes
  • Michael I. G. Simpson
  • Arjan Hillebrand
  • Avgis Hadjipapas
  • Caroline Witton
  • Paul L. Furlong


MEG beamformer algorithms work by making the assumption that correlated and spatially distinct local field potentials do not develop in the human brain. Despite this assumption, images produced by such algorithms concur with those from other non-invasive and invasive estimates of brain function. In this paper we set out to develop a method that could be applied to raw MEG data to explicitly test his assumption. We show that a promax rotation of MEG channel data can be used as an approximate estimator of the number of spatially distinct correlated sources in any frequency band.

Key Words

MEG beamformer promax factor 


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Copyright information

© Springer 2007

Authors and Affiliations

  • Gareth R. Barnes
    • 1
  • Michael I. G. Simpson
    • 1
  • Arjan Hillebrand
    • 1
  • Avgis Hadjipapas
    • 1
  • Caroline Witton
    • 1
  • Paul L. Furlong
    • 1
  1. 1.Neurosciences Research InstituteAston UniversityBirminghamUK

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