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Mechanisms of Intermittent State Transitions in a Coupled Heterogeneous Oscillator Model of Epilepsy

We investigate the dynamic mechanisms underlying intermittent state transitions in a recently proposed neural mass model of epilepsy. A low dimensional model is constructed, which preserves two key features of the neural mass model, namely (i) coupling between oscillators and (ii) heterogeneous prox...

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Detalles Bibliográficos
Autores principales: Goodfellow, Marc, Glendinning, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4177386/
https://www.ncbi.nlm.nih.gov/pubmed/23945016
http://dx.doi.org/10.1186/2190-8567-3-17
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author Goodfellow, Marc
Glendinning, Paul
author_facet Goodfellow, Marc
Glendinning, Paul
author_sort Goodfellow, Marc
collection PubMed
description We investigate the dynamic mechanisms underlying intermittent state transitions in a recently proposed neural mass model of epilepsy. A low dimensional model is constructed, which preserves two key features of the neural mass model, namely (i) coupling between oscillators and (ii) heterogeneous proximity of these oscillators to a bifurcation between distinct limit cycles. We demonstrate that state transitions due to intermittency occur in the abstract model. This suggests that there is a general bifurcation mechanism responsible for this behaviour and that this is independent of the precise form of the evolution equations. Such abstractions of neural mass models allow a deeper insight into underlying dynamic and physiological mechanisms, and also allow the more efficient exploration of large scale brain dynamics in disease.
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spelling pubmed-41773862014-09-30 Mechanisms of Intermittent State Transitions in a Coupled Heterogeneous Oscillator Model of Epilepsy Goodfellow, Marc Glendinning, Paul J Math Neurosci Research We investigate the dynamic mechanisms underlying intermittent state transitions in a recently proposed neural mass model of epilepsy. A low dimensional model is constructed, which preserves two key features of the neural mass model, namely (i) coupling between oscillators and (ii) heterogeneous proximity of these oscillators to a bifurcation between distinct limit cycles. We demonstrate that state transitions due to intermittency occur in the abstract model. This suggests that there is a general bifurcation mechanism responsible for this behaviour and that this is independent of the precise form of the evolution equations. Such abstractions of neural mass models allow a deeper insight into underlying dynamic and physiological mechanisms, and also allow the more efficient exploration of large scale brain dynamics in disease. Springer 2013-08-14 /pmc/articles/PMC4177386/ /pubmed/23945016 http://dx.doi.org/10.1186/2190-8567-3-17 Text en Copyright © 2013 M. Goodfellow, P. Glendinning; licensee Springer http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Goodfellow, Marc
Glendinning, Paul
Mechanisms of Intermittent State Transitions in a Coupled Heterogeneous Oscillator Model of Epilepsy
title Mechanisms of Intermittent State Transitions in a Coupled Heterogeneous Oscillator Model of Epilepsy
title_full Mechanisms of Intermittent State Transitions in a Coupled Heterogeneous Oscillator Model of Epilepsy
title_fullStr Mechanisms of Intermittent State Transitions in a Coupled Heterogeneous Oscillator Model of Epilepsy
title_full_unstemmed Mechanisms of Intermittent State Transitions in a Coupled Heterogeneous Oscillator Model of Epilepsy
title_short Mechanisms of Intermittent State Transitions in a Coupled Heterogeneous Oscillator Model of Epilepsy
title_sort mechanisms of intermittent state transitions in a coupled heterogeneous oscillator model of epilepsy
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4177386/
https://www.ncbi.nlm.nih.gov/pubmed/23945016
http://dx.doi.org/10.1186/2190-8567-3-17
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