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The importance of modeling epileptic seizure dynamics as spatio-temporal patterns

The occurrence of seizures is the common feature across the spectrum of epileptic disorders. We describe how the use of mechanistic neural population models leads to novel insight into the dynamic mechanisms underlying two important types of epileptic seizures. We specifically stress the need for a...

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Detalles Bibliográficos
Autores principales: Baier, Gerold, Goodfellow, Marc, Taylor, Peter N., Wang, Yujiang, Garry, Daniel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3429055/
https://www.ncbi.nlm.nih.gov/pubmed/22934035
http://dx.doi.org/10.3389/fphys.2012.00281
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author Baier, Gerold
Goodfellow, Marc
Taylor, Peter N.
Wang, Yujiang
Garry, Daniel J.
author_facet Baier, Gerold
Goodfellow, Marc
Taylor, Peter N.
Wang, Yujiang
Garry, Daniel J.
author_sort Baier, Gerold
collection PubMed
description The occurrence of seizures is the common feature across the spectrum of epileptic disorders. We describe how the use of mechanistic neural population models leads to novel insight into the dynamic mechanisms underlying two important types of epileptic seizures. We specifically stress the need for a spatio-temporal description of the rhythms to deal with the complexity of the pathophenotype. Adapted to functional and structural patient data, the macroscopic models may allow a patient-specific description of seizures and prediction of treatment outcome.
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spelling pubmed-34290552012-08-29 The importance of modeling epileptic seizure dynamics as spatio-temporal patterns Baier, Gerold Goodfellow, Marc Taylor, Peter N. Wang, Yujiang Garry, Daniel J. Front Physiol Physiology The occurrence of seizures is the common feature across the spectrum of epileptic disorders. We describe how the use of mechanistic neural population models leads to novel insight into the dynamic mechanisms underlying two important types of epileptic seizures. We specifically stress the need for a spatio-temporal description of the rhythms to deal with the complexity of the pathophenotype. Adapted to functional and structural patient data, the macroscopic models may allow a patient-specific description of seizures and prediction of treatment outcome. Frontiers Media S.A. 2012-07-17 /pmc/articles/PMC3429055/ /pubmed/22934035 http://dx.doi.org/10.3389/fphys.2012.00281 Text en Copyright © 2012 Baier, Goodfellow, Taylor, Wang and Garry. http://www.frontiersin.org/licenseagreement This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
spellingShingle Physiology
Baier, Gerold
Goodfellow, Marc
Taylor, Peter N.
Wang, Yujiang
Garry, Daniel J.
The importance of modeling epileptic seizure dynamics as spatio-temporal patterns
title The importance of modeling epileptic seizure dynamics as spatio-temporal patterns
title_full The importance of modeling epileptic seizure dynamics as spatio-temporal patterns
title_fullStr The importance of modeling epileptic seizure dynamics as spatio-temporal patterns
title_full_unstemmed The importance of modeling epileptic seizure dynamics as spatio-temporal patterns
title_short The importance of modeling epileptic seizure dynamics as spatio-temporal patterns
title_sort importance of modeling epileptic seizure dynamics as spatio-temporal patterns
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3429055/
https://www.ncbi.nlm.nih.gov/pubmed/22934035
http://dx.doi.org/10.3389/fphys.2012.00281
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