Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation

Detalhes bibliográficos
Autor(a) principal: Felix, Leonardo Bonato
Data de Publicação: 2007
Outros Autores: Sá, Antonio Mauricio Ferreira Leite Miranda de, Infantosi, Antonio Fernando Catelli, Yehia, Hani Camille
Tipo de documento: Artigo
Idioma: eng
Título da fonte: LOCUS Repositório Institucional da UFV
Texto Completo: https://doi.org/10.1007/s10439-006-9231-4
http://www.locus.ufv.br/handle/123456789/23477
Resumo: The presence of cerebral evoked responses can be tested by using objective response detectors. They are statistical tests that provide a threshold above which responses can be assumed to have occurred. The detection power depends on the signal-to-noise ratio (SNR) of the response and the amount of data available. However, the correlation within the background noise could also affect the power of such detectors. For a fixed SNR, the detection can only be improved at the expense of using a longer stretch of signal. This can constitute a limitation, for instance, in monitored surgeries. Alternatively, multivariate objective response detection (MORD) could be used. This work applies two MORD techniques (multiple coherence and multiple component synchrony measure) to EEG data collected during intermittent photic stimulation. They were evaluated throughout Monte Carlo simulations, which also allowed verifying that correlation in the background reduces the detection rate. Considering the N EEG derivations as close as possible to the primary visual cortex, if N = 4, 6 or 8, multiple coherence leads to a statistically significant higher detection rate in comparison with multiple component synchrony measure. With the former, the best performance was obtained with six signals (O1, O2, T5, T6, P3 and P4).
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spelling Felix, Leonardo BonatoSá, Antonio Mauricio Ferreira Leite Miranda deInfantosi, Antonio Fernando CatelliYehia, Hani Camille2019-02-11T16:11:10Z2019-02-11T16:11:10Z2007-031573-9686https://doi.org/10.1007/s10439-006-9231-4http://www.locus.ufv.br/handle/123456789/23477The presence of cerebral evoked responses can be tested by using objective response detectors. They are statistical tests that provide a threshold above which responses can be assumed to have occurred. The detection power depends on the signal-to-noise ratio (SNR) of the response and the amount of data available. However, the correlation within the background noise could also affect the power of such detectors. For a fixed SNR, the detection can only be improved at the expense of using a longer stretch of signal. This can constitute a limitation, for instance, in monitored surgeries. Alternatively, multivariate objective response detection (MORD) could be used. This work applies two MORD techniques (multiple coherence and multiple component synchrony measure) to EEG data collected during intermittent photic stimulation. They were evaluated throughout Monte Carlo simulations, which also allowed verifying that correlation in the background reduces the detection rate. Considering the N EEG derivations as close as possible to the primary visual cortex, if N = 4, 6 or 8, multiple coherence leads to a statistically significant higher detection rate in comparison with multiple component synchrony measure. With the former, the best performance was obtained with six signals (O1, O2, T5, T6, P3 and P4).engAnnals of Biomedical EngineeringVolume 35, Issue 3, Pages 443–452, March 2007Biomedical Engineering Societyinfo:eu-repo/semantics/openAccessEEGEvoked responseObjective detectionMultivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdfTexto completoapplication/pdf526893https://locus.ufv.br//bitstream/123456789/23477/1/artigo.pdf0e74b8150fc278f0f254ac84673bcd24MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/23477/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52123456789/234772019-02-11 13:18:34.37oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452019-02-11T16:18:34LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.en.fl_str_mv Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation
title Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation
spellingShingle Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation
Felix, Leonardo Bonato
EEG
Evoked response
Objective detection
title_short Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation
title_full Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation
title_fullStr Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation
title_full_unstemmed Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation
title_sort Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation
author Felix, Leonardo Bonato
author_facet Felix, Leonardo Bonato
Sá, Antonio Mauricio Ferreira Leite Miranda de
Infantosi, Antonio Fernando Catelli
Yehia, Hani Camille
author_role author
author2 Sá, Antonio Mauricio Ferreira Leite Miranda de
Infantosi, Antonio Fernando Catelli
Yehia, Hani Camille
author2_role author
author
author
dc.contributor.author.fl_str_mv Felix, Leonardo Bonato
Sá, Antonio Mauricio Ferreira Leite Miranda de
Infantosi, Antonio Fernando Catelli
Yehia, Hani Camille
dc.subject.pt-BR.fl_str_mv EEG
Evoked response
Objective detection
topic EEG
Evoked response
Objective detection
description The presence of cerebral evoked responses can be tested by using objective response detectors. They are statistical tests that provide a threshold above which responses can be assumed to have occurred. The detection power depends on the signal-to-noise ratio (SNR) of the response and the amount of data available. However, the correlation within the background noise could also affect the power of such detectors. For a fixed SNR, the detection can only be improved at the expense of using a longer stretch of signal. This can constitute a limitation, for instance, in monitored surgeries. Alternatively, multivariate objective response detection (MORD) could be used. This work applies two MORD techniques (multiple coherence and multiple component synchrony measure) to EEG data collected during intermittent photic stimulation. They were evaluated throughout Monte Carlo simulations, which also allowed verifying that correlation in the background reduces the detection rate. Considering the N EEG derivations as close as possible to the primary visual cortex, if N = 4, 6 or 8, multiple coherence leads to a statistically significant higher detection rate in comparison with multiple component synchrony measure. With the former, the best performance was obtained with six signals (O1, O2, T5, T6, P3 and P4).
publishDate 2007
dc.date.issued.fl_str_mv 2007-03
dc.date.accessioned.fl_str_mv 2019-02-11T16:11:10Z
dc.date.available.fl_str_mv 2019-02-11T16:11:10Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.1007/s10439-006-9231-4
http://www.locus.ufv.br/handle/123456789/23477
dc.identifier.issn.none.fl_str_mv 1573-9686
identifier_str_mv 1573-9686
url https://doi.org/10.1007/s10439-006-9231-4
http://www.locus.ufv.br/handle/123456789/23477
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartofseries.pt-BR.fl_str_mv Volume 35, Issue 3, Pages 443–452, March 2007
dc.rights.driver.fl_str_mv Biomedical Engineering Society
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Biomedical Engineering Society
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Annals of Biomedical Engineering
publisher.none.fl_str_mv Annals of Biomedical Engineering
dc.source.none.fl_str_mv reponame:LOCUS Repositório Institucional da UFV
instname:Universidade Federal de Viçosa (UFV)
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reponame_str LOCUS Repositório Institucional da UFV
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