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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2012
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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. |
format | Online Article Text |
id | pubmed-3429055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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