Literature DB >> 32066612

The Epileptor Model: A Systematic Mathematical Analysis Linked to the Dynamics of Seizures, Refractory Status Epilepticus, and Depolarization Block.

Kenza El Houssaini1, Christophe Bernard1, Viktor K Jirsa2.   

Abstract

One characteristic of epilepsy is the variety of mechanisms leading to the epileptic state, which are still largely unknown. Refractory status epilepticus (RSE) and depolarization block (DB) are other pathological brain activities linked to epilepsy, whose patterns are different and whose mechanisms remain poorly understood. In epileptogenic network modeling, the Epileptor is a generic phenomenological model that has been recently developed to describe the dynamics of seizures. Here, we performed a detailed qualitative analysis of the Epileptor model based on dynamical systems theory and bifurcation analysis, and investigate the dynamic evolution of "normal" activity toward seizures and to the pathological RSE and DB states. The mechanisms of the transition between states are called bifurcations. Our detailed analysis demonstrates that the generic model undergoes different bifurcation types at seizure offset, when varying some selected parameters. We show that the pathological and normal activities can coexist within the same model under some conditions, and demonstrate that there are many pathways leading to and away from these activities. We here archive systematically all behaviors and dynamic regimes of the Epileptor model to serve as a resource in the development of patient-specific brain network models, and more generally in epilepsy research.
Copyright © 2020 El Houssaini et al.

Entities:  

Keywords:  bifurcation analysis; depolarization block; dynamical systems theory; epilepsy; neural mass model; refractory status epilepticus

Mesh:

Year:  2020        PMID: 32066612      PMCID: PMC7096539          DOI: 10.1523/ENEURO.0485-18.2019

Source DB:  PubMed          Journal:  eNeuro        ISSN: 2373-2822


  10 in total

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Journal:  Arch Neurol       Date:  2005-11

5.  Simulated seizures and spreading depression in a neuron model incorporating interstitial space and ion concentrations.

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6.  The influence of sodium and potassium dynamics on excitability, seizures, and the stability of persistent states. II. Network and glial dynamics.

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Review 7.  Common pathophysiologic mechanisms in migraine and epilepsy.

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Journal:  Arch Neurol       Date:  2008-06

8.  Refractory status epilepticus: a prospective observational study.

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Journal:  Epilepsia       Date:  2009-10-08       Impact factor: 5.864

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Authors:  Viktor K Jirsa; William C Stacey; Pascale P Quilichini; Anton I Ivanov; Christophe Bernard
Journal:  Brain       Date:  2014-06-11       Impact factor: 13.501

10.  The influence of sodium and potassium dynamics on excitability, seizures, and the stability of persistent states: I. Single neuron dynamics.

Authors:  John R Cressman; Ghanim Ullah; Jokubas Ziburkus; Steven J Schiff; Ernest Barreto
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  10 in total
  11 in total

1.  A taxonomy of seizure dynamotypes.

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3.  Perturbations both trigger and delay seizures due to generic properties of slow-fast relaxation oscillators.

Authors:  Alberto Pérez-Cervera; Jaroslav Hlinka
Journal:  PLoS Comput Biol       Date:  2021-03-29       Impact factor: 4.475

4.  A unified physiological framework of transitions between seizures, sustained ictal activity and depolarization block at the single neuron level.

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5.  The role of network connectivity on epileptiform activity.

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6.  Computational modeling of seizure spread on a cortical surface.

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7.  Dynamical Mechanisms of Interictal Resting-State Functional Connectivity in Epilepsy.

Authors:  Julie Courtiol; Maxime Guye; Fabrice Bartolomei; Spase Petkoski; Viktor K Jirsa
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8.  Neurostimulation stabilizes spiking neural networks by disrupting seizure-like oscillatory transitions.

Authors:  Scott Rich; Axel Hutt; Frances K Skinner; Taufik A Valiante; Jérémie Lefebvre
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Review 9.  Whole-Brain Models to Explore Altered States of Consciousness from the Bottom Up.

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10.  Adiabatic dynamic causal modelling.

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