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Epileptic foci localization based on mapping the synchronization of dynamic brain network

BACKGROUND: Characterizing the synchronous changes of epileptic seizures in different stages between different regions is profound to understand the transmission pathways of epileptic brain network and epileptogenic foci. There is currently no adequate quantitative calculation method for describing...

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Autores principales: Mei, Tian, Wei, Xiaoyan, Chen, Ziyi, Tian, Xianghua, Dong, Nan, Li, Dongmei, Zhou, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6354332/
https://www.ncbi.nlm.nih.gov/pubmed/30700279
http://dx.doi.org/10.1186/s12911-019-0737-8
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author Mei, Tian
Wei, Xiaoyan
Chen, Ziyi
Tian, Xianghua
Dong, Nan
Li, Dongmei
Zhou, Yi
author_facet Mei, Tian
Wei, Xiaoyan
Chen, Ziyi
Tian, Xianghua
Dong, Nan
Li, Dongmei
Zhou, Yi
author_sort Mei, Tian
collection PubMed
description BACKGROUND: Characterizing the synchronous changes of epileptic seizures in different stages between different regions is profound to understand the transmission pathways of epileptic brain network and epileptogenic foci. There is currently no adequate quantitative calculation method for describing the propagation pathways of electroencephalogram (EEG) signals in the brain network from the short and long term. The goal of this study is to explore the innovative method to locate epileptic foci, mapping synchronization in the brain networks based on EEG. METHODS: Mutual information was used to analyze the short-term synchronization in the full electrodes; while nonlinear dynamics quantifies the statistical independencies in the long –term among all electrodes. Then graph theory based on the complex network was employed to construct a dynamic brain network for epilepsy patients when they were awake, asleep and in seizure, analyzing the changing topology indexes. RESULTS: Epileptic network achieved a high degree of nonlinear synchronization compared to awake time. and the main path of epileptiform activity was revealed by searching core nodes. The core nodes of the brain network were in connection with the onset zone. Seizures always happened with a high degree of distribution. CONCLUSIONS: This study indicated the path of EEG synchronous propagation in seizures, and core nodes could locate the epileptic foci accurately in some epileptic patients.
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spelling pubmed-63543322019-02-06 Epileptic foci localization based on mapping the synchronization of dynamic brain network Mei, Tian Wei, Xiaoyan Chen, Ziyi Tian, Xianghua Dong, Nan Li, Dongmei Zhou, Yi BMC Med Inform Decis Mak Research BACKGROUND: Characterizing the synchronous changes of epileptic seizures in different stages between different regions is profound to understand the transmission pathways of epileptic brain network and epileptogenic foci. There is currently no adequate quantitative calculation method for describing the propagation pathways of electroencephalogram (EEG) signals in the brain network from the short and long term. The goal of this study is to explore the innovative method to locate epileptic foci, mapping synchronization in the brain networks based on EEG. METHODS: Mutual information was used to analyze the short-term synchronization in the full electrodes; while nonlinear dynamics quantifies the statistical independencies in the long –term among all electrodes. Then graph theory based on the complex network was employed to construct a dynamic brain network for epilepsy patients when they were awake, asleep and in seizure, analyzing the changing topology indexes. RESULTS: Epileptic network achieved a high degree of nonlinear synchronization compared to awake time. and the main path of epileptiform activity was revealed by searching core nodes. The core nodes of the brain network were in connection with the onset zone. Seizures always happened with a high degree of distribution. CONCLUSIONS: This study indicated the path of EEG synchronous propagation in seizures, and core nodes could locate the epileptic foci accurately in some epileptic patients. BioMed Central 2019-01-31 /pmc/articles/PMC6354332/ /pubmed/30700279 http://dx.doi.org/10.1186/s12911-019-0737-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Mei, Tian
Wei, Xiaoyan
Chen, Ziyi
Tian, Xianghua
Dong, Nan
Li, Dongmei
Zhou, Yi
Epileptic foci localization based on mapping the synchronization of dynamic brain network
title Epileptic foci localization based on mapping the synchronization of dynamic brain network
title_full Epileptic foci localization based on mapping the synchronization of dynamic brain network
title_fullStr Epileptic foci localization based on mapping the synchronization of dynamic brain network
title_full_unstemmed Epileptic foci localization based on mapping the synchronization of dynamic brain network
title_short Epileptic foci localization based on mapping the synchronization of dynamic brain network
title_sort epileptic foci localization based on mapping the synchronization of dynamic brain network
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6354332/
https://www.ncbi.nlm.nih.gov/pubmed/30700279
http://dx.doi.org/10.1186/s12911-019-0737-8
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