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Computational Neuroscience pp 317–339Cite as

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

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Part of the book series: Springer Optimization and Its Applications ((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.

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Author information

Authors and Affiliations

  1. Department of Industrial and Systems, Engineering, University of Florida, Gainesville, FL, USA

    Alla R. Kammerdiner

  2. Department of Industrial and System Engineering, Center for Applied Optimization, University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

Authors
  1. Alla R. Kammerdiner
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  2. Panos M. Pardalos
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Corresponding authors

Correspondence to Alla R. Kammerdiner or Panos M. Pardalos .

Editor information

Editors and Affiliations

  1. Department of Industrial and Systems, Engineering, Rutgers State University of New Jersey, Frelinghuysen Rd. 96, Piscataway, 08854, New Jersey, USA

    Wanpracha Chaovalitwongse

  2. Dept. Industrial & Systems, Engineering, University of Florida, Weil Hall 303, Gainesville, 32611-6595, Florida, USA

    Panos M. Pardalos

  3. , Dept. of Industrial & Systems Eng., University of Florida, Weil Hall 303, Gainesville, 32611, Florida, USA

    Petros Xanthopoulos

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Kammerdiner, A.R., Pardalos, P.M. (2010). Analysis of Multichannel EEG Recordings Based on Generalized Phase Synchronization and Cointegrated VAR. In: Chaovalitwongse, W., Pardalos, P., Xanthopoulos, P. (eds) Computational Neuroscience. Springer Optimization and Its Applications(), vol 38. Springer, New York, NY. https://doi.org/10.1007/978-0-387-88630-5_18

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