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Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone
The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have pr...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5563307/ https://www.ncbi.nlm.nih.gov/pubmed/28867999 http://dx.doi.org/10.3389/fncom.2017.00077 |
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author | Zhang, Luyan Liang, Yi Li, Fali Sun, Hongbin Peng, Wenjing Du, Peishan Si, Yajing Song, Limeng Yu, Liang Xu, Peng |
author_facet | Zhang, Luyan Liang, Yi Li, Fali Sun, Hongbin Peng, Wenjing Du, Peishan Si, Yajing Song, Limeng Yu, Liang Xu, Peng |
author_sort | Zhang, Luyan |
collection | PubMed |
description | The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging. |
format | Online Article Text |
id | pubmed-5563307 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-55633072017-09-01 Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone Zhang, Luyan Liang, Yi Li, Fali Sun, Hongbin Peng, Wenjing Du, Peishan Si, Yajing Song, Limeng Yu, Liang Xu, Peng Front Comput Neurosci Neuroscience The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging. Frontiers Media S.A. 2017-08-18 /pmc/articles/PMC5563307/ /pubmed/28867999 http://dx.doi.org/10.3389/fncom.2017.00077 Text en Copyright © 2017 Zhang, Liang, Li, Sun, Peng, Du, Si, Song, Yu and Xu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Zhang, Luyan Liang, Yi Li, Fali Sun, Hongbin Peng, Wenjing Du, Peishan Si, Yajing Song, Limeng Yu, Liang Xu, Peng Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone |
title | Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone |
title_full | Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone |
title_fullStr | Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone |
title_full_unstemmed | Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone |
title_short | Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone |
title_sort | time-varying networks of inter-ictal discharging reveal epileptogenic zone |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5563307/ https://www.ncbi.nlm.nih.gov/pubmed/28867999 http://dx.doi.org/10.3389/fncom.2017.00077 |
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