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Network-Based Techniques in EEG Data Analysis and Epileptic Brain Modeling

In: Data Mining in Biomedicine

Author

Listed:
  • Oleg A. Prokopyev

    (University of Pittsburgh)

  • Vladimir L. Boginski

    (Florida State University)

  • Wanpracha Chaovalitwongse

    (The State University of New Jersey)

  • Panos M. Pardalos

    (University of Florida
    University of Florida)

  • J. Chris Sackellares

    (University of Florida
    University of Florida
    University of Florida)

  • Paul R. Carney

    (University of Florida
    University of Florida)

Abstract

We discuss a novel approach of modeling the behavior of the epileptic human brain, which utilizes network-based techniques in combination with statistical preprocessing of the electroencephalographic (EEG) data obtained from the electrodes located in different parts of the brain. In the constructed graphs, the vertices represent the “functional units” of the brain, where electrodes are located. Studying dynamical changes of the properties of these graphs provides valuable information about the patterns characterizing the behavior of the brain prior to, during, and after an epileptic seizure.

Suggested Citation

  • Oleg A. Prokopyev & Vladimir L. Boginski & Wanpracha Chaovalitwongse & Panos M. Pardalos & J. Chris Sackellares & Paul R. Carney, 2007. "Network-Based Techniques in EEG Data Analysis and Epileptic Brain Modeling," Springer Optimization and Its Applications, in: Panos M. Pardalos & Vladimir L. Boginski & Alkis Vazacopoulos (ed.), Data Mining in Biomedicine, pages 559-573, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-69319-4_28
    DOI: 10.1007/978-0-387-69319-4_28
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