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Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients
Resection of the seizure generating tissue can be highly beneficial in patients with drug‐resistant epilepsy. However, only about half of all patients undergoing surgery get permanently and completely seizure free. Investigating the dependences between intracranial EEG signals adds a multivariate pe...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268049/ https://www.ncbi.nlm.nih.gov/pubmed/31625670 http://dx.doi.org/10.1002/hbm.24816 |
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author | Müller, Michael Caporro, Matteo Gast, Heidemarie Pollo, Claudio Wiest, Roland Schindler, Kaspar Rummel, Christian |
author_facet | Müller, Michael Caporro, Matteo Gast, Heidemarie Pollo, Claudio Wiest, Roland Schindler, Kaspar Rummel, Christian |
author_sort | Müller, Michael |
collection | PubMed |
description | Resection of the seizure generating tissue can be highly beneficial in patients with drug‐resistant epilepsy. However, only about half of all patients undergoing surgery get permanently and completely seizure free. Investigating the dependences between intracranial EEG signals adds a multivariate perspective largely unavailable to visual EEG analysis, which is the current clinical practice. We examined linear and nonlinear interrelations between intracranial EEG signals regarding their spatial distribution and network characteristics. The analyzed signals were recorded immediately before clinical seizure onset in epilepsy patients who received a standardized electrode implantation targeting the mesiotemporal structures. The linear interrelation networks were predominantly locally connected and highly reproducible between patients. In contrast, the nonlinear networks had a clearly centralized structure, which was specific for the individual pathology. The nonlinear interrelations were overrepresented in the focal hemisphere and in patients with no or only rare seizures after surgery specifically in the resected tissue. Connections to the outside were predominantly nonlinear. In all patients without worthwhile improvement after resective treatment, tissue producing strong nonlinear interrelations was left untouched by surgery. Our findings indicate that linear and nonlinear interrelations play fundamentally different roles in preictal intracranial EEG. Moreover, they suggest nonlinear signal interrelations to be a marker of epileptogenic tissue and not a characteristic of the mesiotemporal structures. Our results corroborate the network‐based nature of epilepsy and suggest the application of network analysis to support the planning of resective epilepsy surgery. |
format | Online Article Text |
id | pubmed-7268049 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72680492020-06-12 Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients Müller, Michael Caporro, Matteo Gast, Heidemarie Pollo, Claudio Wiest, Roland Schindler, Kaspar Rummel, Christian Hum Brain Mapp Research Articles Resection of the seizure generating tissue can be highly beneficial in patients with drug‐resistant epilepsy. However, only about half of all patients undergoing surgery get permanently and completely seizure free. Investigating the dependences between intracranial EEG signals adds a multivariate perspective largely unavailable to visual EEG analysis, which is the current clinical practice. We examined linear and nonlinear interrelations between intracranial EEG signals regarding their spatial distribution and network characteristics. The analyzed signals were recorded immediately before clinical seizure onset in epilepsy patients who received a standardized electrode implantation targeting the mesiotemporal structures. The linear interrelation networks were predominantly locally connected and highly reproducible between patients. In contrast, the nonlinear networks had a clearly centralized structure, which was specific for the individual pathology. The nonlinear interrelations were overrepresented in the focal hemisphere and in patients with no or only rare seizures after surgery specifically in the resected tissue. Connections to the outside were predominantly nonlinear. In all patients without worthwhile improvement after resective treatment, tissue producing strong nonlinear interrelations was left untouched by surgery. Our findings indicate that linear and nonlinear interrelations play fundamentally different roles in preictal intracranial EEG. Moreover, they suggest nonlinear signal interrelations to be a marker of epileptogenic tissue and not a characteristic of the mesiotemporal structures. Our results corroborate the network‐based nature of epilepsy and suggest the application of network analysis to support the planning of resective epilepsy surgery. John Wiley & Sons, Inc. 2019-10-18 /pmc/articles/PMC7268049/ /pubmed/31625670 http://dx.doi.org/10.1002/hbm.24816 Text en © 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Müller, Michael Caporro, Matteo Gast, Heidemarie Pollo, Claudio Wiest, Roland Schindler, Kaspar Rummel, Christian Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients |
title | Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients |
title_full | Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients |
title_fullStr | Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients |
title_full_unstemmed | Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients |
title_short | Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients |
title_sort | linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial eeg of epilepsy patients |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268049/ https://www.ncbi.nlm.nih.gov/pubmed/31625670 http://dx.doi.org/10.1002/hbm.24816 |
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