Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing

Idiopathic epilepsy is characterized by generalized seizures with no apparent cause. One of its main problems is the lack of biomarkers to monitor the evolution of patients. The only tools they can use are limited to inspecting the amount of seizures during previous periods of time and assessing the...

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Autores: Urigüen Garaizabal, José Antonio, García Zapirain, María Begoña, Artieda, Julio, Iriarte, Jorge, Valencia, Miguel
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/71364
Acceso en línea:http://hdl.handle.net/10810/71364
Access Level:acceso abierto
Palabra clave:EEG
epilepsy
Shannon spectral entropy
cluster-based permutation statistical testing
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spelling Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testingUrigüen Garaizabal, José AntonioGarcía Zapirain, María BegoñaArtieda, JulioIriarte, JorgeValencia, MiguelEEGepilepsyShannon spectral entropycluster-based permutation statistical testingIdiopathic epilepsy is characterized by generalized seizures with no apparent cause. One of its main problems is the lack of biomarkers to monitor the evolution of patients. The only tools they can use are limited to inspecting the amount of seizures during previous periods of time and assessing the existence of interictal discharges. As a result, there is a need for improving the tools to assist the diagnosis and follow up of these patients. The goal of the present study is to compare and find a way to differentiate between two groups of patients suffering from idiopathic epilepsy, one group that could be followed-up by means of specific electroencephalographic (EEG) signatures (intercritical activity present), and another one that could not due to the absence of these markers. To do that, we analyzed the background EEG activity of each in the absence of seizures and epileptic intercritical activity. We used the Shannon spectral entropy (SSE) as a metric to discriminate between the two groups and performed permutation-based statistical tests to detect the set of frequencies that show significant differences. By constraining the spectral entropy estimation to the [6.25–12.89) Hz range, we detect statistical differences (at below 0.05 alpha-level) between both types of epileptic patients at all available recording channels. Interestingly, entropy values follow a trend that is inversely related to the elapsed time from the last seizure. Indeed, this trend shows asymptotical convergence to the SSE values measured in a group of healthy subjects, which present SSE values lower than any of the two groups of patients. All these results suggest that the SSE, measured in a specific range of frequencies, could serve to follow up the evolution of patients suffering from idiopathic epilepsy. Future studies remain to be conducted in order to assess the predictive value of this approach for the anticipation of seizures.Jose Antonio Urigüen was in part funded by Bizkaia:Talent and the European Union’s Seventh Framework Programme. Marie Curie Actions - People. Co-funding of Regional, National and International Programmes. Grant agreement n. 267230. Julio Artieda and Miguel Valencia acknowledged support from the Departamento de Salud, Gobierno de Navarra (114/2014).PLOSEuropean Commission202520252017info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/71364reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoInglésinfo:eu-repo/grantAgreement/EC/H2020/267230https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0184044info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/© 2017 Urigu¨en et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.oai:addi.ehu.eus:10810/713642026-06-18T09:23:17Z
dc.title.none.fl_str_mv Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing
title Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing
spellingShingle Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing
Urigüen Garaizabal, José Antonio
EEG
epilepsy
Shannon spectral entropy
cluster-based permutation statistical testing
title_short Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing
title_full Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing
title_fullStr Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing
title_full_unstemmed Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing
title_sort Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing
dc.creator.none.fl_str_mv Urigüen Garaizabal, José Antonio
García Zapirain, María Begoña
Artieda, Julio
Iriarte, Jorge
Valencia, Miguel
author Urigüen Garaizabal, José Antonio
author_facet Urigüen Garaizabal, José Antonio
García Zapirain, María Begoña
Artieda, Julio
Iriarte, Jorge
Valencia, Miguel
author_role author
author2 García Zapirain, María Begoña
Artieda, Julio
Iriarte, Jorge
Valencia, Miguel
author2_role author
author
author
author
dc.contributor.none.fl_str_mv European Commission
dc.subject.none.fl_str_mv EEG
epilepsy
Shannon spectral entropy
cluster-based permutation statistical testing
topic EEG
epilepsy
Shannon spectral entropy
cluster-based permutation statistical testing
description Idiopathic epilepsy is characterized by generalized seizures with no apparent cause. One of its main problems is the lack of biomarkers to monitor the evolution of patients. The only tools they can use are limited to inspecting the amount of seizures during previous periods of time and assessing the existence of interictal discharges. As a result, there is a need for improving the tools to assist the diagnosis and follow up of these patients. The goal of the present study is to compare and find a way to differentiate between two groups of patients suffering from idiopathic epilepsy, one group that could be followed-up by means of specific electroencephalographic (EEG) signatures (intercritical activity present), and another one that could not due to the absence of these markers. To do that, we analyzed the background EEG activity of each in the absence of seizures and epileptic intercritical activity. We used the Shannon spectral entropy (SSE) as a metric to discriminate between the two groups and performed permutation-based statistical tests to detect the set of frequencies that show significant differences. By constraining the spectral entropy estimation to the [6.25–12.89) Hz range, we detect statistical differences (at below 0.05 alpha-level) between both types of epileptic patients at all available recording channels. Interestingly, entropy values follow a trend that is inversely related to the elapsed time from the last seizure. Indeed, this trend shows asymptotical convergence to the SSE values measured in a group of healthy subjects, which present SSE values lower than any of the two groups of patients. All these results suggest that the SSE, measured in a specific range of frequencies, could serve to follow up the evolution of patients suffering from idiopathic epilepsy. Future studies remain to be conducted in order to assess the predictive value of this approach for the anticipation of seizures.
publishDate 2017
dc.date.none.fl_str_mv 2017
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/71364
url http://hdl.handle.net/10810/71364
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/EC/H2020/267230
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0184044
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv PLOS
publisher.none.fl_str_mv PLOS
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
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