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Domino-like transient dynamics at seizure onset in epilepsy
The International League Against Epilepsy (ILAE) groups seizures into “focal”, “generalized” and “unknown” based on whether the seizure onset is confined to a brain region in one hemisphere, arises in several brain region simultaneously, or is not known, respectively. This separation fails to accoun...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7544071/ https://www.ncbi.nlm.nih.gov/pubmed/32986695 http://dx.doi.org/10.1371/journal.pcbi.1008206 |
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author | Creaser, Jennifer Lin, Congping Ridler, Thomas Brown, Jonathan T. D’Souza, Wendyl Seneviratne, Udaya Cook, Mark Terry, John R. Tsaneva-Atanasova, Krasimira |
author_facet | Creaser, Jennifer Lin, Congping Ridler, Thomas Brown, Jonathan T. D’Souza, Wendyl Seneviratne, Udaya Cook, Mark Terry, John R. Tsaneva-Atanasova, Krasimira |
author_sort | Creaser, Jennifer |
collection | PubMed |
description | The International League Against Epilepsy (ILAE) groups seizures into “focal”, “generalized” and “unknown” based on whether the seizure onset is confined to a brain region in one hemisphere, arises in several brain region simultaneously, or is not known, respectively. This separation fails to account for the rich diversity of clinically and experimentally observed spatiotemporal patterns of seizure onset and even less so for the properties of the brain networks generating them. We consider three different patterns of domino-like seizure onset in Idiopathic Generalized Epilepsy (IGE) and present a novel approach to classification of seizures. To understand how these patterns are generated on networks requires understanding of the relationship between intrinsic node dynamics and coupling between nodes in the presence of noise, which currently is unknown. We investigate this interplay here in the framework of domino-like recruitment across a network. In particular, we use a phenomenological model of seizure onset with heterogeneous coupling and node properties, and show that in combination they generate a range of domino-like onset patterns observed in the IGE seizures. We further explore the individual contribution of heterogeneous node dynamics and coupling by interpreting in-vitro experimental data in which the speed of onset can be chemically modulated. This work contributes to a better understanding of possible drivers for the spatiotemporal patterns observed at seizure onset and may ultimately contribute to a more personalized approach to classification of seizure types in clinical practice. |
format | Online Article Text |
id | pubmed-7544071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-75440712020-10-19 Domino-like transient dynamics at seizure onset in epilepsy Creaser, Jennifer Lin, Congping Ridler, Thomas Brown, Jonathan T. D’Souza, Wendyl Seneviratne, Udaya Cook, Mark Terry, John R. Tsaneva-Atanasova, Krasimira PLoS Comput Biol Research Article The International League Against Epilepsy (ILAE) groups seizures into “focal”, “generalized” and “unknown” based on whether the seizure onset is confined to a brain region in one hemisphere, arises in several brain region simultaneously, or is not known, respectively. This separation fails to account for the rich diversity of clinically and experimentally observed spatiotemporal patterns of seizure onset and even less so for the properties of the brain networks generating them. We consider three different patterns of domino-like seizure onset in Idiopathic Generalized Epilepsy (IGE) and present a novel approach to classification of seizures. To understand how these patterns are generated on networks requires understanding of the relationship between intrinsic node dynamics and coupling between nodes in the presence of noise, which currently is unknown. We investigate this interplay here in the framework of domino-like recruitment across a network. In particular, we use a phenomenological model of seizure onset with heterogeneous coupling and node properties, and show that in combination they generate a range of domino-like onset patterns observed in the IGE seizures. We further explore the individual contribution of heterogeneous node dynamics and coupling by interpreting in-vitro experimental data in which the speed of onset can be chemically modulated. This work contributes to a better understanding of possible drivers for the spatiotemporal patterns observed at seizure onset and may ultimately contribute to a more personalized approach to classification of seizure types in clinical practice. Public Library of Science 2020-09-28 /pmc/articles/PMC7544071/ /pubmed/32986695 http://dx.doi.org/10.1371/journal.pcbi.1008206 Text en © 2020 Creaser et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Creaser, Jennifer Lin, Congping Ridler, Thomas Brown, Jonathan T. D’Souza, Wendyl Seneviratne, Udaya Cook, Mark Terry, John R. Tsaneva-Atanasova, Krasimira Domino-like transient dynamics at seizure onset in epilepsy |
title | Domino-like transient dynamics at seizure onset in epilepsy |
title_full | Domino-like transient dynamics at seizure onset in epilepsy |
title_fullStr | Domino-like transient dynamics at seizure onset in epilepsy |
title_full_unstemmed | Domino-like transient dynamics at seizure onset in epilepsy |
title_short | Domino-like transient dynamics at seizure onset in epilepsy |
title_sort | domino-like transient dynamics at seizure onset in epilepsy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7544071/ https://www.ncbi.nlm.nih.gov/pubmed/32986695 http://dx.doi.org/10.1371/journal.pcbi.1008206 |
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