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Analysis of Multichannel EEG Recordings Based on Generalized Phase Synchronization and Cointegrated VAR

In: Computational Neuroscience

Author

Listed:
  • Alla R. Kammerdiner

    (University of Florida)

  • Panos M. Pardalos

    (University of Florida)

Abstract

Synchronization is shown to be a characteristic feature of electroencephalogram data collected from patients affected by neurological diseases, such as epilepsy. Phase synchronization has been applied successfully to investigate synchrony in neurophysiological signal. The classical approach to phase synchronization is inherently bivariate. We propose a novel multivariate approach to phase synchronization, by extending the bivariate case via cointegrated vector autoregression, and then apply the new concept to absence epilepsy data.

Suggested Citation

  • Alla R. Kammerdiner & Panos M. Pardalos, 2010. "Analysis of Multichannel EEG Recordings Based on Generalized Phase Synchronization and Cointegrated VAR," Springer Optimization and Its Applications, in: Wanpracha Chaovalitwongse & Panos M. Pardalos & Petros Xanthopoulos (ed.), Computational Neuroscience, chapter 0, pages 317-339, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-88630-5_18
    DOI: 10.1007/978-0-387-88630-5_18
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