Seizure onset zone lateralization using a non-linear analysis of micro vs. macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patients

The application of non-linear signal analysis techniques to biomedical data is key to improve our knowledge about complex physiological and pathological processes. In particular, the use of non-linear techniques to study electroencephalographic (EEG) recordings can provide an advanced characterizati...

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Autores: Martínez, Cristina G. B., Niediek, Johannes, Mormann, Florian, Andrzejak, Ralph Gregor
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/46087
Acceso en línea:http://hdl.handle.net/10230/46087
http://dx.doi.org/10.3389/fneur.2020.553885
Access Level:acceso abierto
Palabra clave:Epilepsy
Quantitative EEG analysis
Seizure onset zone lateralization
EEG
Hybrid electrodes
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spelling Seizure onset zone lateralization using a non-linear analysis of micro vs. macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patientsMartínez, Cristina G. B.Niediek, JohannesMormann, FlorianAndrzejak, Ralph GregorEpilepsyQuantitative EEG analysisSeizure onset zone lateralizationEEGHybrid electrodesThe application of non-linear signal analysis techniques to biomedical data is key to improve our knowledge about complex physiological and pathological processes. In particular, the use of non-linear techniques to study electroencephalographic (EEG) recordings can provide an advanced characterization of brain dynamics. In epilepsy these dynamics are altered at different spatial scales of neuronal organization. We therefore apply non-linear signal analysis to EEG recordings from epilepsy patients derived with intracranial hybrid electrodes, which are composed of classical macro contacts and micro wires. Thereby, these electrodes record EEG at two different spatial scales. Our aim is to test the degree to which the analysis of the EEG recorded at these different scales allows us to characterize the neuronal dynamics affected by epilepsy. For this purpose, we retrospectively analyzed long-term recordings performed during five nights in three patients during which no seizures took place. As a benchmark we used the accuracy with which this analysis allows determining the hemisphere that contains the seizure onset zone, which is the brain area where clinical seizures originate. We applied the surrogate-corrected non-linear predictability score (ψ), a non-linear signal analysis technique which was shown previously to be useful for the lateralization of the seizure onset zone from classical intracranial EEG macro contact recordings. Higher values of ψ were found predominantly for signals recorded from the hemisphere containing the seizure onset zone as compared to signals recorded from the opposite hemisphere. These differences were found not only for the EEG signals recorded with macro contacts, but also for those recorded with micro wires. In conclusion, the information obtained from the analysis of classical macro EEG contacts can be complemented by the one of micro wire EEG recordings. This combined approach may therefore help to further improve the degree to which quantitative EEG analysis can contribute to the diagnostics in epilepsy patients.The authors acknowledge funding from the Spanish Ministry of Economy and Competitiveness, Grant No. FIS2014-54177-R (CM and RA) and by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme, MDM-2015-0502 (CM), from the Volkswagen foundation (FM), from the German Research Council (DFG MO 930/8-1, DFG SFB 1089 to FM).Frontiers202020202020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/46087http://dx.doi.org/10.3389/fneur.2020.553885reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésFrontiers in Neurology. 2020 Sep 17;11:553885http://hdl.handle.net/10230/45317info:eu-repo/grantAgreement/ES/1PE/FIS2014-54177-Rinfo:eu-repo/grantAgreement/ES/1PE/MDM-2015-0502© 2020 Martínez, Niediek, Mormann and Andrzejak. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/). 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.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/460872026-06-12T07:21:37Z
dc.title.none.fl_str_mv Seizure onset zone lateralization using a non-linear analysis of micro vs. macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patients
title Seizure onset zone lateralization using a non-linear analysis of micro vs. macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patients
spellingShingle Seizure onset zone lateralization using a non-linear analysis of micro vs. macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patients
Martínez, Cristina G. B.
Epilepsy
Quantitative EEG analysis
Seizure onset zone lateralization
EEG
Hybrid electrodes
title_short Seizure onset zone lateralization using a non-linear analysis of micro vs. macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patients
title_full Seizure onset zone lateralization using a non-linear analysis of micro vs. macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patients
title_fullStr Seizure onset zone lateralization using a non-linear analysis of micro vs. macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patients
title_full_unstemmed Seizure onset zone lateralization using a non-linear analysis of micro vs. macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patients
title_sort Seizure onset zone lateralization using a non-linear analysis of micro vs. macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patients
dc.creator.none.fl_str_mv Martínez, Cristina G. B.
Niediek, Johannes
Mormann, Florian
Andrzejak, Ralph Gregor
author Martínez, Cristina G. B.
author_facet Martínez, Cristina G. B.
Niediek, Johannes
Mormann, Florian
Andrzejak, Ralph Gregor
author_role author
author2 Niediek, Johannes
Mormann, Florian
Andrzejak, Ralph Gregor
author2_role author
author
author
dc.subject.none.fl_str_mv Epilepsy
Quantitative EEG analysis
Seizure onset zone lateralization
EEG
Hybrid electrodes
topic Epilepsy
Quantitative EEG analysis
Seizure onset zone lateralization
EEG
Hybrid electrodes
description The application of non-linear signal analysis techniques to biomedical data is key to improve our knowledge about complex physiological and pathological processes. In particular, the use of non-linear techniques to study electroencephalographic (EEG) recordings can provide an advanced characterization of brain dynamics. In epilepsy these dynamics are altered at different spatial scales of neuronal organization. We therefore apply non-linear signal analysis to EEG recordings from epilepsy patients derived with intracranial hybrid electrodes, which are composed of classical macro contacts and micro wires. Thereby, these electrodes record EEG at two different spatial scales. Our aim is to test the degree to which the analysis of the EEG recorded at these different scales allows us to characterize the neuronal dynamics affected by epilepsy. For this purpose, we retrospectively analyzed long-term recordings performed during five nights in three patients during which no seizures took place. As a benchmark we used the accuracy with which this analysis allows determining the hemisphere that contains the seizure onset zone, which is the brain area where clinical seizures originate. We applied the surrogate-corrected non-linear predictability score (ψ), a non-linear signal analysis technique which was shown previously to be useful for the lateralization of the seizure onset zone from classical intracranial EEG macro contact recordings. Higher values of ψ were found predominantly for signals recorded from the hemisphere containing the seizure onset zone as compared to signals recorded from the opposite hemisphere. These differences were found not only for the EEG signals recorded with macro contacts, but also for those recorded with micro wires. In conclusion, the information obtained from the analysis of classical macro EEG contacts can be complemented by the one of micro wire EEG recordings. This combined approach may therefore help to further improve the degree to which quantitative EEG analysis can contribute to the diagnostics in epilepsy patients.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/46087
http://dx.doi.org/10.3389/fneur.2020.553885
url http://hdl.handle.net/10230/46087
http://dx.doi.org/10.3389/fneur.2020.553885
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Frontiers in Neurology. 2020 Sep 17;11:553885
http://hdl.handle.net/10230/45317
info:eu-repo/grantAgreement/ES/1PE/FIS2014-54177-R
info:eu-repo/grantAgreement/ES/1PE/MDM-2015-0502
dc.rights.none.fl_str_mv https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Frontiers
publisher.none.fl_str_mv Frontiers
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
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