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Controlling epileptic seizures in a neural mass model

Author

Listed:
  • Niranjan Chakravarthy

    (Arizona State University)

  • Shivkumar Sabesan

    (Arizona State University)

  • Kostas Tsakalis

    (Arizona State University)

  • Leon Iasemidis

    (Arizona State University)

Abstract

In an effort to understand basic functional mechanisms that can produce epileptic seizures, we introduce some key features in a model of coupled neural populations that enable the generation of seizure-like events and similar dynamics with the ones observed during the route of the epileptic brain towards real seizures. In this model, modified from David and Friston’s neural mass model, an internal feedback mechanism is incorporated to maintain synchronous behavior within normal levels despite elevated coupling. Normal internal feedback quickly regulates an abnormally high coupling between the neural populations, whereas pathological internal feedback can lead to hypersynchronization and the appearance of seizure-like high amplitude oscillations. Feedback decoupling is introduced as a robust seizure control strategy. An external feedback decoupling controller is introduced to maintain normal synchronous behavior. The results from the analysis in this model have an interesting physical interpretation and specific implications for the treatment of epileptic seizures. The proposed model and control scheme are consistent with a variety of recent observations in the human and animal epileptic brain, and with theories from nonlinear systems, adaptive systems, optimization, and neurophysiology.

Suggested Citation

  • Niranjan Chakravarthy & Shivkumar Sabesan & Kostas Tsakalis & Leon Iasemidis, 2009. "Controlling epileptic seizures in a neural mass model," Journal of Combinatorial Optimization, Springer, vol. 17(1), pages 98-116, January.
  • Handle: RePEc:spr:jcomop:v:17:y:2009:i:1:d:10.1007_s10878-008-9182-9
    DOI: 10.1007/s10878-008-9182-9
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    References listed on IDEAS

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    1. Gina G. Turrigiano & Kenneth R. Leslie & Niraj S. Desai & Lana C. Rutherford & Sacha B. Nelson, 1998. "Activity-dependent scaling of quantal amplitude in neocortical neurons," Nature, Nature, vol. 391(6670), pages 892-896, February.
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    Cited by:

    1. Shan, Bonan & Wang, Jiang & Deng, Bin & Zhang, Zhen & Wei, Xile, 2017. "Estimate the effective connectivity in multi-coupled neural mass model using particle swarm optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 89-101.

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