Comparing MEG and high-density EEG for intrinsic functional connectivity mapping

Available online 20 January 2020.

Detalhes bibliográficos
Autores: Coquelet, N., De Tiège, Xavier, Destoky, F., Roshchupkina, L., Bourguignon, Mathieu, Goldman, S., Peigneux, Philippe, Wens, V.
Formato: artículo
Fecha de publicación:2020
País:España
Recursos:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/42215
Acesso em linha:http://hdl.handle.net/10810/42215
Access Level:acceso abierto
Palavra-chave:Connectome
State dynamics
Resting-state networks
Envelope correlation
Magnetoencephalography
Electroencephalography
id ES_2ea6b34a6092cbc365cc2b2e5a2019c2
oai_identifier_str oai:addi.ehu.eus:10810/42215
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Comparing MEG and high-density EEG for intrinsic functional connectivity mapping
title Comparing MEG and high-density EEG for intrinsic functional connectivity mapping
spellingShingle Comparing MEG and high-density EEG for intrinsic functional connectivity mapping
Coquelet, N.
Connectome
State dynamics
Resting-state networks
Envelope correlation
Magnetoencephalography
Electroencephalography
title_short Comparing MEG and high-density EEG for intrinsic functional connectivity mapping
title_full Comparing MEG and high-density EEG for intrinsic functional connectivity mapping
title_fullStr Comparing MEG and high-density EEG for intrinsic functional connectivity mapping
title_full_unstemmed Comparing MEG and high-density EEG for intrinsic functional connectivity mapping
title_sort Comparing MEG and high-density EEG for intrinsic functional connectivity mapping
dc.creator.none.fl_str_mv Coquelet, N.
De Tiège, Xavier
Destoky, F.
Roshchupkina, L.
Bourguignon, Mathieu
Goldman, S.
Peigneux, Philippe
Wens, V.
author Coquelet, N.
author_facet Coquelet, N.
De Tiège, Xavier
Destoky, F.
Roshchupkina, L.
Bourguignon, Mathieu
Goldman, S.
Peigneux, Philippe
Wens, V.
author_role author
author2 De Tiège, Xavier
Destoky, F.
Roshchupkina, L.
Bourguignon, Mathieu
Goldman, S.
Peigneux, Philippe
Wens, V.
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Connectome
State dynamics
Resting-state networks
Envelope correlation
Magnetoencephalography
Electroencephalography
topic Connectome
State dynamics
Resting-state networks
Envelope correlation
Magnetoencephalography
Electroencephalography
description Available online 20 January 2020.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/42215
url http://hdl.handle.net/10810/42215
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/EC/H2020/MC
info:eu-repo/grantAgreement/MINECO/PSI2016-77175-P/
https://www.sciencedirect.com/journal/neuroimage
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
© 2020 Published by Elsevier Inc.
eu_rights_str_mv openAccess
rights_invalid_str_mv © 2020 Published by Elsevier Inc.
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
_version_ 1869405424172662784
spelling Comparing MEG and high-density EEG for intrinsic functional connectivity mappingCoquelet, N.De Tiège, XavierDestoky, F.Roshchupkina, L.Bourguignon, MathieuGoldman, S.Peigneux, PhilippeWens, V.ConnectomeState dynamicsResting-state networksEnvelope correlationMagnetoencephalographyElectroencephalographyAvailable online 20 January 2020.Magnetoencephalography (MEG) has been used in conjunction with resting-state functional connectivity (rsFC) based on band-limited power envelope correlation to study the intrinsic human brain network organization into resting-state networks (RSNs). However, the limited availability of current MEG systems hampers the clinical applications of electrophysiological rsFC. Here, we directly compared well-known RSNs as well as the whole-brain rsFC connectome together with its state dynamics, obtained from simultaneously-recorded MEG and high-density scalp electroencephalography (EEG) resting-state data. We also examined the impact of head model precision on EEG rsFC estimation, by comparing results obtained with boundary and finite element head models. Results showed that most RSN topographies obtained with MEG and EEG are similar, except for the fronto-parietal network. At the connectome level, sensitivity was lower to frontal rsFC and higher to parieto-occipital rsFC with MEG compared to EEG. This was mostly due to inhomogeneity of MEG sensor locations relative to the scalp and significant MEG-EEG differences disappeared when taking relative MEG-EEG sensor locations into account. The default-mode network was the only RSN requiring advanced head modeling in EEG, in which gray and white matter are distinguished. Importantly, comparison of rsFC state dynamics evidenced a poor correspondence between MEG and scalp EEG, suggesting sensitivity to different components of transient neural functional integration. This study therefore shows that the investigation of static rsFC based on the human brain connectome can be performed with scalp EEG in a similar way than with MEG, opening the avenue to widespread clinical applications of rsFC analyses.This study was supported by the Action de Recherche Concert ee Consolidation (ARCC, “Characterizing the spatio-temporal dynamics and the electrophysiological bases of resting state networks”, ULB, Brussels, Belgium), the Fonds Erasme (Research Convention “Les Voies du Savoir”, Brussels, Belgium) and the Fonds de la Recherche Scientifique (Research Convention: T.0109.13, F.R.S. - FNRS, Brussels, Belgium). Nicolas Coquelet has been supported by the ARCC and is supported by the Fonds Erasme (Research Convention “Les Voies du Savoir”, Brussels, Belgium). Xavier De Ti ege is Postdoctorate Clinical Master Specialist at the FRSFNRS. Florian Destoky and Mathieu Bourguignon are supported by the program Attract of Innoviris (Research Grant 2015-BB2B-10, Brussels, Belgium). Mathieu Bourguignon is also supported by the Marie Sklodowska-Curie Action of the European Commission (Research Grant: 743562) and by the Spanish Ministery of Economy and Competitiveness (Research Grant: PSI2016-77175-P). Lillia Roshchupkina is F.R.S. - FNRS Research Fellow and was previously supported by a ULB Mini-ARC grant. The MEG project at the CUB H^opital Erasme is financially supported by the Fonds Erasme (Research Convention “Les Voies du Savoir”, Brussels, Belgium). The high-density EEG project at the CUB H^opital Erasme has been financially supported by the CUB H^opital Erasme (Medical Council Research Grant) and by the F.R.S. - FNRS. The authors would like to thank Maribel Pulgarin Montoya for her help in part of the simultaneous MEG and high-density EEG recordings.NeuroImage202020202020info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/42215reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoInglésinfo:eu-repo/grantAgreement/EC/H2020/MCinfo:eu-repo/grantAgreement/MINECO/PSI2016-77175-P/https://www.sciencedirect.com/journal/neuroimageinfo:eu-repo/semantics/openAccess© 2020 Published by Elsevier Inc.oai:addi.ehu.eus:10810/422152026-06-18T09:23:17Z
score 15,301603

Registos relacionados