Journal of Computational Neuroscience

, Volume 34, Issue 3, pp 411–432 | Cite as

Testing for significance of phase synchronisation dynamics in the EEG

  • Ian DalyEmail author
  • Catherine M. Sweeney-Reed
  • Slawomir J. Nasuto


A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.


Phase synchronisation Statistical significance testing EEG HMM SMM 



The authors would like to thank Dr Peter beim Graben for his many helpful comments and input throughout this work and Dr Brendan Z. Allison for proof-reading.


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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Ian Daly
    • 1
    Email author
  • Catherine M. Sweeney-Reed
    • 2
  • Slawomir J. Nasuto
    • 3
  1. 1.Institute for Knowledge Discovery, Laboratory of Brain-Computer InterfacesGraz University of TechnologyGrazAustria
  2. 2.Memory and Consciousness Research GroupUniversity Clinic for Neurology and Stereotactic Neurosurgery, Medical Faculty, Otto-von-Guericke UniversityMagdeburgGermany
  3. 3.School of Systems Engineering and Centre for Integrative Neuroscience and NeurodynamicsUniversity of ReadingReadingUK

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