Domino-like transient dynamics at seizure onset in epilepsy
dc.contributor.author | Creaser, J | |
dc.contributor.author | Lin, C | |
dc.contributor.author | Ridler, T | |
dc.contributor.author | Brown, JT | |
dc.contributor.author | D’Souza, W | |
dc.contributor.author | Seneviratne, U | |
dc.contributor.author | Cook, M | |
dc.contributor.author | Terry, JR | |
dc.contributor.author | Tsaneva-Atanasova, K | |
dc.date.accessioned | 2020-09-28T09:22:59Z | |
dc.date.issued | 2020-09-28 | |
dc.description.abstract | 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. | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.description.sponsorship | Medical Research Council (MRC) | en_GB |
dc.identifier.citation | Vol. 16 (9), article e1008206 | en_GB |
dc.identifier.doi | 10.1371/journal.pcbi.1008206 | |
dc.identifier.grantnumber | MR/S019499/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/123010 | |
dc.language.iso | en | en_GB |
dc.publisher | Public Library of Science (PLoS) | en_GB |
dc.relation.url | https://doi.org/10.17605/OSF.IO/G2EXK | |
dc.rights | © 2020 Creaser et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |
dc.title | Domino-like transient dynamics at seizure onset in epilepsy | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-09-28T09:22:59Z | |
dc.identifier.issn | 1553-734X | |
dc.description | This is the final version. Available on open access from Public Library of Science via the DOI in this record | en_GB |
dc.description | Data Availability: We have made publicly available the 15 epochs of human EEG data containing generalized paroxysms classified as focal onset, and all 15 epochs containing seizures from one individual used in the manuscript, 1252 EEG epochs containing seizures classified as generalized onset and the 6 mouse mEC recordings. All data and the code used for the data analysis and model simulations they can be accessed via DOI 10.17605/OSF.IO/G2EXK. | |
dc.identifier.journal | PLoS Computational Biology | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2020-07-29 | |
exeter.funder | ::Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
exeter.funder | ::Medical Research Council (MRC) | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2020-07-29 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-09-25T16:21:55Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-10-09T14:25:00Z | |
refterms.panel | B | en_GB |
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Except where otherwise noted, this item's licence is described as © 2020 Creaser et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.