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

  • Alla R. Kammerdiner
  • Panos M. Pardalos
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 38)

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.

Keywords

Electroencephalogram Phase synchronization Cointegrated vector autoregressive processes 

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Industrial and Systems, EngineeringUniversity of FloridaGainesvilleUSA
  2. 2.Department of Industrial and System Engineering, Center for Applied OptimizationUniversity of FloridaGainesvilleUSA

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