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dc.contributor.authorSalmela, Viljami
dc.contributor.authorGuo, Lijing
dc.contributor.authorAlho, Kimmo
dc.contributor.authorYe, Chaoxiong
dc.date.accessioned2023-09-15T05:00:59Z
dc.date.available2023-09-15T05:00:59Z
dc.date.issued2023
dc.identifier.citationSalmela, V., Guo, L., Alho, K., & Ye, C. (2023). EEG-fMRI fusion analysis of attention and visual working memory. In <i>CCN 2023 : 2023 Conference on Cognitive Computational Neuroscience</i> (pp. 678-680). Conference Management Services, Inc.. <a href="https://doi.org/10.32470/ccn.2023.1293-0" target="_blank">https://doi.org/10.32470/ccn.2023.1293-0</a>
dc.identifier.otherCONVID_184774553
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/89108
dc.description.abstractWhile the previous fMRI studies suggest that the contents of the visual working memory (VWM) are represented in a spatially widely distributed brain network and the previous EEG studies have revealed some temporal properties of the memory processes, the exact spatio-temporal dynamics of working memory processes are not yet understood. Here we used multivariate EEG-fMRI fusion analysis to combine spatially (fMRI) and temporally (EEG) precise information, separately measured (n = 29) during a cued and delayed orientation change detection. Representational dissimilarity matrices (RDMs) from EEG responses in 10 ms time bins and fMRI responses from 360 different brain regions were correlated with each other as well as with model RDMs. Both EEG and fMRI response patterns were almost fully explained by attention (left/right cue) and only minimally by memory (set size and change magnitude). EEG-fMRI fusion showed distinct temporal profiles in different regions containing sustained information and transient peaks. The results highlight the role of attentional processes during working memory tasksen
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherConference Management Services, Inc.
dc.relation.ispartofCCN 2023 : 2023 Conference on Cognitive Computational Neuroscience
dc.rightsCC BY 3.0
dc.subject.othervisual working memory
dc.subject.otherchange detection
dc.subject.otherEEG
dc.subject.otherfMRI
dc.subject.otherrepresentational similarity analysis
dc.subject.otherRSA
dc.subject.otherEEG-fMRI fusion
dc.titleEEG-fMRI fusion analysis of attention and visual working memory
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-202309155129
dc.contributor.laitosPsykologian laitosfi
dc.contributor.laitosDepartment of Psychologyen
dc.contributor.oppiainePsykologiafi
dc.contributor.oppiainePsychologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.type.coarhttp://purl.org/coar/resource_type/c_5794
dc.description.reviewstatusnonPeerReviewed
dc.format.pagerange678-680
dc.type.versionpublishedVersion
dc.rights.copyright© Authors 2023
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceConference on Cognitive Computational Neuroscience
dc.relation.grantnumber333649
dc.subject.ysoEEG
dc.subject.ysotyömuisti
dc.subject.ysotoiminnallinen magneettikuvaus
dc.subject.ysotarkkaavaisuus
dc.subject.ysonäkömuisti
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p3328
jyx.subject.urihttp://www.yso.fi/onto/yso/p13896
jyx.subject.urihttp://www.yso.fi/onto/yso/p24211
jyx.subject.urihttp://www.yso.fi/onto/yso/p9105
jyx.subject.urihttp://www.yso.fi/onto/yso/p27025
dc.rights.urlhttps://creativecommons.org/licenses/by/3.0/
dc.relation.doi10.32470/ccn.2023.1293-0
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramPostdoctoral Researcher, AoFen
jyx.fundingprogramTutkijatohtori, SAfi
jyx.fundinginformationThis work was supported by grants from the National Natural Science Foundation of China (No. 31700948), and the Academy of Finland (No. 333649 to C.Y.).
dc.type.okmD3


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