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Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised

Current explanatory concepts suggest seizures emerge from ongoing dynamics of brain networks. It is unclear how brain network properties determine focal or generalised seizure onset, or how network properties can be described in a clinically-useful manner. Understanding network properties would cast...

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Autores principales: Woldman, Wessel, Schmidt, Helmut, Abela, Eugenio, Chowdhury, Fahmida A., Pawley, Adam D., Jewell, Sharon, Richardson, Mark P., Terry, John R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7184577/
https://www.ncbi.nlm.nih.gov/pubmed/32341399
http://dx.doi.org/10.1038/s41598-020-63430-9
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author Woldman, Wessel
Schmidt, Helmut
Abela, Eugenio
Chowdhury, Fahmida A.
Pawley, Adam D.
Jewell, Sharon
Richardson, Mark P.
Terry, John R.
author_facet Woldman, Wessel
Schmidt, Helmut
Abela, Eugenio
Chowdhury, Fahmida A.
Pawley, Adam D.
Jewell, Sharon
Richardson, Mark P.
Terry, John R.
author_sort Woldman, Wessel
collection PubMed
description Current explanatory concepts suggest seizures emerge from ongoing dynamics of brain networks. It is unclear how brain network properties determine focal or generalised seizure onset, or how network properties can be described in a clinically-useful manner. Understanding network properties would cast light on seizure-generating mechanisms and allow to quantify to which extent a seizure is focal or generalised. Functional brain networks were estimated in segments of scalp-EEG without interictal discharges (68 people with epilepsy, 38 controls). Simplified brain dynamics were simulated using a computer model. We introduce: Critical Coupling (C(c)), the ability of a network to generate seizures; Onset Index (OI), the tendency of a region to generate seizures; and Participation Index (PI), the tendency of a region to become involved in seizures. C(c) was lower in both patient groups compared with controls. OI and PI were more variable in focal-onset than generalised-onset cases. In focal cases, the regions with highest OI and PI corresponded to the side of seizure onset. Properties of interictal functional networks from scalp EEG can be estimated using a computer model and used to predict seizure likelihood and onset patterns. This may offer potential to enhance diagnosis through quantification of seizure type using inter-ictal recordings.
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spelling pubmed-71845772020-04-29 Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised Woldman, Wessel Schmidt, Helmut Abela, Eugenio Chowdhury, Fahmida A. Pawley, Adam D. Jewell, Sharon Richardson, Mark P. Terry, John R. Sci Rep Article Current explanatory concepts suggest seizures emerge from ongoing dynamics of brain networks. It is unclear how brain network properties determine focal or generalised seizure onset, or how network properties can be described in a clinically-useful manner. Understanding network properties would cast light on seizure-generating mechanisms and allow to quantify to which extent a seizure is focal or generalised. Functional brain networks were estimated in segments of scalp-EEG without interictal discharges (68 people with epilepsy, 38 controls). Simplified brain dynamics were simulated using a computer model. We introduce: Critical Coupling (C(c)), the ability of a network to generate seizures; Onset Index (OI), the tendency of a region to generate seizures; and Participation Index (PI), the tendency of a region to become involved in seizures. C(c) was lower in both patient groups compared with controls. OI and PI were more variable in focal-onset than generalised-onset cases. In focal cases, the regions with highest OI and PI corresponded to the side of seizure onset. Properties of interictal functional networks from scalp EEG can be estimated using a computer model and used to predict seizure likelihood and onset patterns. This may offer potential to enhance diagnosis through quantification of seizure type using inter-ictal recordings. Nature Publishing Group UK 2020-04-27 /pmc/articles/PMC7184577/ /pubmed/32341399 http://dx.doi.org/10.1038/s41598-020-63430-9 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Woldman, Wessel
Schmidt, Helmut
Abela, Eugenio
Chowdhury, Fahmida A.
Pawley, Adam D.
Jewell, Sharon
Richardson, Mark P.
Terry, John R.
Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised
title Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised
title_full Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised
title_fullStr Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised
title_full_unstemmed Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised
title_short Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised
title_sort dynamic network properties of the interictal brain determine whether seizures appear focal or generalised
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7184577/
https://www.ncbi.nlm.nih.gov/pubmed/32341399
http://dx.doi.org/10.1038/s41598-020-63430-9
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