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dc.contributor.authorIllman, Mia
dc.contributor.authorLaaksonen, Kristina
dc.contributor.authorLiljeström, Mia
dc.contributor.authorJousmäki, Veikko
dc.contributor.authorPiitulainen, Harri
dc.contributor.authorFross, Nina
dc.date.accessioned2020-04-27T09:57:52Z
dc.date.available2020-04-27T09:57:52Z
dc.date.issued2020
dc.identifier.citationIllman, M., Laaksonen, K., Liljeström, M., Jousmäki, V., Piitulainen, H., & Fross, N. (2020). Comparing MEG and EEG in detecting the ~20-Hz rhythm modulation to tactile and proprioceptive stimulation. <i>NeuroImage</i>, <i>215</i>, Article 116804. <a href="https://doi.org/10.1016/j.neuroimage.2020.116804" target="_blank">https://doi.org/10.1016/j.neuroimage.2020.116804</a>
dc.identifier.otherCONVID_35298489
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/68711
dc.description.abstractModulation of the ~20-Hz brain rhythm has been used to evaluate the functional state of the sensorimotor cortex both in healthy subjects and patients, such as stroke patients. The ~20-Hz brain rhythm can be detected by both magnetoencephalography (MEG) and electroencephalography (EEG), but the comparability of these methods has not been evaluated. Here, we compare these two methods in the evaluating of ~20-Hz activity modulation to somatosensory stimuli. Rhythmic ~20-Hz activity during separate tactile and proprioceptive stimulation of the right and left index finger was recorded simultaneously with MEG and EEG in twenty-four healthy participants. Both tactile and proprioceptive stimulus produced a clear suppression at 300–350 ​ms followed by a subsequent rebound at 700–900 ​ms after stimulus onset, detected at similar latencies both with MEG and EEG. The relative amplitudes of suppression and rebound correlated strongly between MEG and EEG recordings. However, the relative strength of suppression and rebound in the contralateral hemisphere (with respect to the stimulated hand) was significantly stronger in MEG than in EEG recordings. Our results indicate that MEG recordings produced signals with higher signal-to-noise ratio than EEG, favoring MEG as an optimal tool for studies evaluating sensorimotor cortical functions. However, the strong correlation between MEG and EEG results encourages the use of EEG when translating studies to clinical practice. The clear advantage of EEG is the availability of the method in hospitals and bed-side measurements at the acute phase.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofseriesNeuroImage
dc.rightsCC BY-NC-ND 4.0
dc.subject.otherbeta rebound
dc.subject.otherbeta rhythm
dc.subject.otherbeta suppression
dc.subject.otherpassive movement
dc.subject.othersensorimotor cortex
dc.subject.othertactile stimulation
dc.titleComparing MEG and EEG in detecting the ~20-Hz rhythm modulation to tactile and proprioceptive stimulation
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202004272913
dc.contributor.laitosLiikuntatieteellinen tiedekuntafi
dc.contributor.laitosFaculty of Sport and Health Sciencesen
dc.contributor.oppiaineMonitieteinen aivotutkimuskeskusfi
dc.contributor.oppiaineHyvinvoinnin tutkimuksen yhteisöfi
dc.contributor.oppiaineCentre for Interdisciplinary Brain Researchen
dc.contributor.oppiaineSchool of Wellbeingen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn1053-8119
dc.relation.volume215
dc.type.versionpublishedVersion
dc.rights.copyright© 2020 The Authors. Published by Elsevier Inc.
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber327288
dc.relation.grantnumber326988
dc.subject.ysotuntoaisti
dc.subject.ysostimulointi
dc.subject.ysoliikeaisti
dc.subject.ysoMEG
dc.subject.ysoEEG
dc.subject.ysomotoriikka
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p3330
jyx.subject.urihttp://www.yso.fi/onto/yso/p20809
jyx.subject.urihttp://www.yso.fi/onto/yso/p23334
jyx.subject.urihttp://www.yso.fi/onto/yso/p3329
jyx.subject.urihttp://www.yso.fi/onto/yso/p3328
jyx.subject.urihttp://www.yso.fi/onto/yso/p496
dc.rights.urlhttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.relation.doi10.1016/j.neuroimage.2020.116804
dc.relation.funderResearch Council of Finlanden
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramResearch costs of Academy Research Fellow, AoFen
jyx.fundingprogramAcademy Research Fellow, AoFen
jyx.fundingprogramAkatemiatutkijan tutkimuskulut, SAfi
jyx.fundingprogramAkatemiatutkija, SAfi
jyx.fundinginformationThis work was supported by the SalWe Research Program for Mind and Body, Tekes – the Finnish Funding Agency for Technology and Innovation [grant number 1104/10]; Academy of Finland [grant numbers 296240, 307250, 326988, 327288]; Aalto NeuroImaging, Aalto Brain Centre and Jane and Aatos Erkko Foundation.
dc.type.okmA1


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