Seizure Suppression in a Thalamocortical Computational Model of Absence Epilepsy by Linear Delayed Feedback Control

Using a thalamocortical computational model of absence epilepsy, we consider the linear delayed feedback control (LDFC) as a brain stimulation strategy for seizure suppression. The model consists of a pyramidal cell population (PY) and an interneuron population (IN) in the cortex and thalamocortical relay cells (TC) and reticular nucleus (RE) in the thalamus. Without control, the system behaves spike-and-wave discharges (SWDs). The typical LDFC with a constant feedback gain and a constant time delay, can effectively suppressed seizures only in a certain range of the parameter space. We propose to use a periodic time delay instead. The seizure can be effectively suppressed in almost the full parameter space. The underlying control mechanisms are also demonstrated. We recommend the LDFC with periodic time delays as a potential deep brain stimulation (DBS) therapy for absence epilepsy.

[1]  Theoden I. Netoff,et al.  Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation , 2013, Front. Neural Circuits.

[2]  Fabrice Wendling,et al.  Computational models of epileptiform activity , 2016, Journal of Neuroscience Methods.

[3]  U. Stephani,et al.  A Computational Study of Stimulus Driven Epileptic Seizure Abatement , 2014, PloS one.

[4]  P. Tass,et al.  Multisite Delayed Feedback for Electrical Brain Stimulation , 2018, Front. Physiol..

[5]  J. Téllez-Zenteno,et al.  Deep Brain Stimulation and Drug-Resistant Epilepsy: A Review of the Literature , 2019, Front. Neurol..

[6]  P. Tass,et al.  Closed-loop deep brain stimulation by pulsatile delayed feedback with increased gap between pulse phases , 2017, Scientific Reports.

[7]  Felice T. Sun,et al.  Responsive cortical stimulation for the treatment of epilepsy , 2011, Neurotherapeutics.

[8]  W. Lytton.  Computer modelling of epilepsy , 2008, Nature Reviews Neuroscience.

[9]  Kestutis Pyragas.  Continuous control of chaos by self-controlling feedback , 1992 .

[10]  J. V. Van Buren,et al.  Preliminary evaluation of cerebellar stimulation by double-blind stimulation and biological criteria in the treatment of epilepsy. , 1978, Journal of neurosurgery.

[11]  Chen Liu,et al.  Model Predictive Control for Seizure Suppression Based on Nonlinear Auto-Regressive Moving-Average Volterra Model , 2020, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[12]  Jiang Wang,et al.  Desynchronization in an ensemble of globally coupled chaotic bursting neuronal oscillators by dynamic delayed feedback control , 2014, 1403.1914.

[13]  F. L. D. Silva,et al.  Dynamics of non-convulsive epileptic phenomena modeled by a bistable neuronal network , 2004, Neuroscience.

[14]  R. Köhling,et al.  Voltage-gated calcium channels in the etiopathogenesis and treatment of absence epilepsy , 2010, Brain Research Reviews.

[15]  M. Morrell.  Responsive cortical stimulation for the treatment of medically intractable partial epilepsy , 2011, Neurology.

[16]  Peter A Tass,et al.  Adaptive delivery of continuous and delayed feedback deep brain stimulation - a computational study , 2019, Scientific Reports.

[17]  Jiang Wang,et al.  Robust closed-loop control of spike-and-wave discharges in a thalamocortical computational model of absence epilepsy , 2019, Scientific Reports.

[18]  Massimo Avoli,et al.  A brief history on the oscillating roles of thalamus and cortex in absence seizures , 2012, Epilepsia.