Controlling epileptic seizures in a neural mass model

Niranjan Chakravarthy (), Shivkumar Sabesan (), Kostas Tsakalis () and Leon Iasemidis ()
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Niranjan Chakravarthy: Arizona State University
Shivkumar Sabesan: Arizona State University
Kostas Tsakalis: Arizona State University
Leon Iasemidis: Arizona State University

Journal of Combinatorial Optimization, 2009, vol. 17, issue 1, No 7, 98-116

Abstract: 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.

Keywords: Epileptic seizures modeling; Coupled neural populations; Internal feedback; Feedback decoupling control (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1007/s10878-008-9182-9

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