Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope

Available online 8 September 2018.

Detalles Bibliográficos
Autores: Destoky, Florian, Philippe, Morgane, Bertels, Julie, Verhasselt, Marie, Coquelet, Nicolas, Vander Ghinst, Marc, Wens, Vincent, De Tiège, Xavier, Bourguignon, Mathieu
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/28833
Acceso en línea:http://hdl.handle.net/10810/28833
Access Level:acceso embargado
Palabra clave:Coherence
EEG
MEG
Reconstruction accuracy
Speech brain tracking
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spelling Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelopeDestoky, FlorianPhilippe, MorganeBertels, JulieVerhasselt, MarieCoquelet, NicolasVander Ghinst, MarcWens, VincentDe Tiège, XavierBourguignon, MathieuCoherenceEEGMEGReconstruction accuracySpeech brain trackingAvailable online 8 September 2018.During connected speech listening, brain activity tracks speech rhythmicity at delta (∼0.5 Hz) and theta (4–8 Hz) frequencies. Here, we compared the potential of magnetoencephalography (MEG) and high-density electroencephalography (EEG) to uncover such speech brain tracking. Ten healthy right-handed adults listened to two different 5-min audio recordings, either without noise or mixed with a cocktail-party noise of equal loudness. Their brain activity was simultaneously recorded with MEG and EEG. We quantified speech brain tracking channel-by-channel using coherence, and with all channels at once by speech temporal envelope reconstruction accuracy. In both conditions, speech brain tracking was significant at delta and theta frequencies and peaked in the temporal regions with both modalities (MEG and EEG). However, in the absence of noise, speech brain tracking estimated from MEG data was significantly higher than that obtained from EEG. Furthemore, to uncover significant speech brain tracking, recordings needed to be ∼3 times longer in EEG than MEG, depending on the frequency considered (delta or theta) and the estimation method. In the presence of noise, both EEG and MEG recordings replicated the previous finding that speech brain tracking at delta frequencies is stronger with attended speech (i.e., the sound subjects are attending to) than with the global sound (i.e., the attended speech and the noise combined). Other previously reported MEG findings were replicated based on MEG but not EEG recordings: 1) speech brain tracking at theta frequencies is stronger with attended speech than with the global sound, 2) speech brain tracking at delta frequencies is stronger in noiseless than noisy conditions, and 3) when noise is added, speech brain tracking at delta frequencies dampens less in the left hemisphere than in the right hemisphere. Finally, sources of speech brain tracking reconstructed from EEG data were systematically deeper and more posterior than those derived from MEG. The present study demonstrates that speech brain tracking is better seen with MEG than EEG. Quantitatively, EEG recordings need to be ∼3 times longer than MEG recordings to uncover significant speech brain tracking. As a consequence, MEG appears more suited than EEG to pinpoint subtle effects related to speech brain tracking in a given recording time.Florian Destoky, Julie Bertels, and Mathieu Bourguignon are supported by the program Attract of Innoviris (grant 2015-BB2B-10). Marc Vander Ghinst was supported by a research grant from the Fonds Erasme (Brussels, Belgium). Xavier De Tiège is Post-doctorate Clinical Master Specialist at the FRS-FNRS. Mathieu Bourguignon is supported by the Marie Skłodowska-Curie Action of the European Commission (grant 743562) and by the Spanish Ministry of Economy and Competitiveness (grant PSI2016-77175-P). This research project and the MEG project at the CUB Hôpital Erasme are financially supported by the Fonds Erasme (Research convention “Les Voies du Savoir”, Fonds Erasme, Brussels, Belgium).NeuroImage201820182019info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/28833reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoInglésinfo:eu-repo/grantAgreement/EC/H2020/743562info:eu-repo/grantAgreement/MINECO/PSI2016-77175-P/https://www.sciencedirect.com/journal/neuroimageinfo:eu-repo/semantics/embargoedAccess© 2018 Elsevier Inc. All rights reserved.oai:addi.ehu.eus:10810/288332026-06-18T09:23:17Z
dc.title.none.fl_str_mv Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope
title Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope
spellingShingle Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope
Destoky, Florian
Coherence
EEG
MEG
Reconstruction accuracy
Speech brain tracking
title_short Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope
title_full Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope
title_fullStr Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope
title_full_unstemmed Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope
title_sort Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope
dc.creator.none.fl_str_mv Destoky, Florian
Philippe, Morgane
Bertels, Julie
Verhasselt, Marie
Coquelet, Nicolas
Vander Ghinst, Marc
Wens, Vincent
De Tiège, Xavier
Bourguignon, Mathieu
author Destoky, Florian
author_facet Destoky, Florian
Philippe, Morgane
Bertels, Julie
Verhasselt, Marie
Coquelet, Nicolas
Vander Ghinst, Marc
Wens, Vincent
De Tiège, Xavier
Bourguignon, Mathieu
author_role author
author2 Philippe, Morgane
Bertels, Julie
Verhasselt, Marie
Coquelet, Nicolas
Vander Ghinst, Marc
Wens, Vincent
De Tiège, Xavier
Bourguignon, Mathieu
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv
dc.subject.none.fl_str_mv Coherence
EEG
MEG
Reconstruction accuracy
Speech brain tracking
topic Coherence
EEG
MEG
Reconstruction accuracy
Speech brain tracking
description Available online 8 September 2018.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018
2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/28833
url http://hdl.handle.net/10810/28833
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/EC/H2020/743562
info:eu-repo/grantAgreement/MINECO/PSI2016-77175-P/
https://www.sciencedirect.com/journal/neuroimage
dc.rights.none.fl_str_mv info:eu-repo/semantics/embargoedAccess
© 2018 Elsevier Inc. All rights reserved.
eu_rights_str_mv embargoedAccess
rights_invalid_str_mv © 2018 Elsevier Inc. All rights reserved.
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv NeuroImage
publisher.none.fl_str_mv NeuroImage
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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score 15,300719

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