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A Peri-Ictal EEG-Based Biomarker for Sudden Unexpected Death in Epilepsy (SUDEP) Derived From Brain Network Analysis
Sudden unexpected death in epilepsy (SUDEP) is the leading seizure-related cause of death in epilepsy patients. There are no validated biomarkers of SUDEP risk. Here, we explored peri-ictal differences in topological brain network properties from scalp EEG recordings of SUDEP victims. Functional con...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10013055/ https://www.ncbi.nlm.nih.gov/pubmed/36926093 http://dx.doi.org/10.3389/fnetp.2022.866540 |
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author | Tufa, Uilki Gravitis, Adam Zukotynski, Katherine Chinvarun, Yotin Devinsky, Orrin Wennberg, Richard Carlen, Peter L. Bardakjian, Berj L. |
author_facet | Tufa, Uilki Gravitis, Adam Zukotynski, Katherine Chinvarun, Yotin Devinsky, Orrin Wennberg, Richard Carlen, Peter L. Bardakjian, Berj L. |
author_sort | Tufa, Uilki |
collection | PubMed |
description | Sudden unexpected death in epilepsy (SUDEP) is the leading seizure-related cause of death in epilepsy patients. There are no validated biomarkers of SUDEP risk. Here, we explored peri-ictal differences in topological brain network properties from scalp EEG recordings of SUDEP victims. Functional connectivity networks were constructed and examined as directed graphs derived from undirected delta and high frequency oscillation (HFO) EEG coherence networks in eight SUDEP and 14 non-SUDEP epileptic patients. These networks were proxies for information flow at different spatiotemporal scales, where low frequency oscillations coordinate large-scale activity driving local HFOs. The clustering coefficient and global efficiency of the network were higher in the SUDEP group pre-ictally, ictally and post-ictally (p < 0.0001 to p < 0.001), with features characteristic of small-world networks. These results suggest that cross-frequency functional connectivity network topology may be a non-invasive biomarker of SUDEP risk. |
format | Online Article Text |
id | pubmed-10013055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100130552023-03-15 A Peri-Ictal EEG-Based Biomarker for Sudden Unexpected Death in Epilepsy (SUDEP) Derived From Brain Network Analysis Tufa, Uilki Gravitis, Adam Zukotynski, Katherine Chinvarun, Yotin Devinsky, Orrin Wennberg, Richard Carlen, Peter L. Bardakjian, Berj L. Front Netw Physiol Network Physiology Sudden unexpected death in epilepsy (SUDEP) is the leading seizure-related cause of death in epilepsy patients. There are no validated biomarkers of SUDEP risk. Here, we explored peri-ictal differences in topological brain network properties from scalp EEG recordings of SUDEP victims. Functional connectivity networks were constructed and examined as directed graphs derived from undirected delta and high frequency oscillation (HFO) EEG coherence networks in eight SUDEP and 14 non-SUDEP epileptic patients. These networks were proxies for information flow at different spatiotemporal scales, where low frequency oscillations coordinate large-scale activity driving local HFOs. The clustering coefficient and global efficiency of the network were higher in the SUDEP group pre-ictally, ictally and post-ictally (p < 0.0001 to p < 0.001), with features characteristic of small-world networks. These results suggest that cross-frequency functional connectivity network topology may be a non-invasive biomarker of SUDEP risk. Frontiers Media S.A. 2022-04-26 /pmc/articles/PMC10013055/ /pubmed/36926093 http://dx.doi.org/10.3389/fnetp.2022.866540 Text en Copyright © 2022 Tufa, Gravitis, Zukotynski, Chinvarun, Devinsky, Wennberg, Carlen and Bardakjian. https://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) and the copyright owner(s) 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 | Network Physiology Tufa, Uilki Gravitis, Adam Zukotynski, Katherine Chinvarun, Yotin Devinsky, Orrin Wennberg, Richard Carlen, Peter L. Bardakjian, Berj L. A Peri-Ictal EEG-Based Biomarker for Sudden Unexpected Death in Epilepsy (SUDEP) Derived From Brain Network Analysis |
title | A Peri-Ictal EEG-Based Biomarker for Sudden Unexpected Death in Epilepsy (SUDEP) Derived From Brain Network Analysis |
title_full | A Peri-Ictal EEG-Based Biomarker for Sudden Unexpected Death in Epilepsy (SUDEP) Derived From Brain Network Analysis |
title_fullStr | A Peri-Ictal EEG-Based Biomarker for Sudden Unexpected Death in Epilepsy (SUDEP) Derived From Brain Network Analysis |
title_full_unstemmed | A Peri-Ictal EEG-Based Biomarker for Sudden Unexpected Death in Epilepsy (SUDEP) Derived From Brain Network Analysis |
title_short | A Peri-Ictal EEG-Based Biomarker for Sudden Unexpected Death in Epilepsy (SUDEP) Derived From Brain Network Analysis |
title_sort | peri-ictal eeg-based biomarker for sudden unexpected death in epilepsy (sudep) derived from brain network analysis |
topic | Network Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10013055/ https://www.ncbi.nlm.nih.gov/pubmed/36926093 http://dx.doi.org/10.3389/fnetp.2022.866540 |
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