Identifying true brain interaction from EEG data using the imaginary part of coherency

Guido Nolte, Ou Bai, Lewis Wheaton, Zoltan Mari, Sherry Vorbach, Mark Hallett

Research output: Contribution to journalArticlepeer-review

967 Scopus citations


Objective: The main obstacle in interpreting EEG/MEG data in terms of brain connectivity is the fact that because of volume conduction, the activity of a single brain source can be observed in many channels. Here, we present an approach which is insensitive to false connectivity arising from volume conduction. Methods: We show that the (complex) coherency of non-interacting sources is necessarily real and, hence, the imaginary part of coherency provides an excellent candidate to study brain interactions. Although the usual magnitude and phase of coherency contain the same information as the real and imaginary parts, we argue that the Cartesian representation is far superior for studying brain interactions. The method is demonstrated for EEG measurements of voluntary finger movement. Results: We found: (a) from 5 s before to movement onset a relatively weak interaction around 20 Hz between left and right motor areas where the contralateral side leads the ipsilateral side; and (b) approximately 2-4 s after movement, a stronger interaction also at 20 Hz in the opposite direction. Conclusions: It is possible to reliably detect brain interaction during movement from EEG data. Significance: The method allows unambiguous detection of brain interaction from rhythmic EEG/MEG data.

Original languageEnglish (US)
Pages (from-to)2292-2307
Number of pages16
JournalClinical Neurophysiology
Issue number10
StatePublished - Oct 2004
Externally publishedYes


  • Coherence
  • Connectivity
  • EEG
  • Motor control
  • Time-lag
  • Volume conduction

ASJC Scopus subject areas

  • Clinical Neurology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Sensory Systems
  • Physiology (medical)


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