Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free inter...

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Autores: Andrzejak, Ralph Gregor, Chicharro Raventós, Daniel, Lehnertz, Klaus, Mormann, Florian
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2011
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositório:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/43592
Acesso em linha:http://hdl.handle.net/10230/43592
http://dx.doi.org/10.1103/PhysRevE.83.046203
Access Level:Acceso aberto
Palavra-chave:Nonlinear signal analysis
Synchronization
Surrogate
Electroencephalographic recordings
Epilepsy
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spelling Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogatesAndrzejak, Ralph GregorChicharro Raventós, DanielLehnertz, KlausMormann, FlorianNonlinear signal analysisSynchronizationSurrogateElectroencephalographic recordingsEpilepsyThe disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.American Physical Society202020202011info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/43592http://dx.doi.org/10.1103/PhysRevE.83.046203reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésPhysical Review E. 2011;83:046203.© American Physical Society. Published article available at https://doi.org/10.1103/PhysRevE.83.046203info:eu-repo/semantics/openAccessoai:recercat.cat:10230/435922026-05-29T05:05:01Z
dc.title.none.fl_str_mv Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates
title Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates
spellingShingle Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates
Andrzejak, Ralph Gregor
Nonlinear signal analysis
Synchronization
Surrogate
Electroencephalographic recordings
Epilepsy
title_short Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates
title_full Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates
title_fullStr Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates
title_full_unstemmed Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates
title_sort Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates
dc.creator.none.fl_str_mv Andrzejak, Ralph Gregor
Chicharro Raventós, Daniel
Lehnertz, Klaus
Mormann, Florian
author Andrzejak, Ralph Gregor
author_facet Andrzejak, Ralph Gregor
Chicharro Raventós, Daniel
Lehnertz, Klaus
Mormann, Florian
author_role author
author2 Chicharro Raventós, Daniel
Lehnertz, Klaus
Mormann, Florian
author2_role author
author
author
dc.subject.none.fl_str_mv Nonlinear signal analysis
Synchronization
Surrogate
Electroencephalographic recordings
Epilepsy
topic Nonlinear signal analysis
Synchronization
Surrogate
Electroencephalographic recordings
Epilepsy
description The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.
publishDate 2011
dc.date.none.fl_str_mv 2011
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/43592
http://dx.doi.org/10.1103/PhysRevE.83.046203
url http://hdl.handle.net/10230/43592
http://dx.doi.org/10.1103/PhysRevE.83.046203
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Physical Review E. 2011;83:046203.
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Physical Society
publisher.none.fl_str_mv American Physical Society
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
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