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dc.contributor.authorZhang, Chi
dc.contributor.authorSun, Lina
dc.contributor.authorCong, Fengyi
dc.contributor.authorRistaniemi, Tapani
dc.date.accessioned2020-02-28T09:41:46Z
dc.date.available2020-02-28T09:41:46Z
dc.date.issued2021
dc.identifier.citationZhang, C., Sun, L., Cong, F., & Ristaniemi, T. (2021). Spatio-temporal Dynamical Analysis of Brain Activity during Mental Fatigue Process. <i>IEEE Transactions on Cognitive and Developmental Systems</i>, <i>13</i>(3), 593-606. <a href="https://doi.org/10.1109/TCDS.2020.2976610" target="_blank">https://doi.org/10.1109/TCDS.2020.2976610</a>
dc.identifier.otherCONVID_34761427
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/68002
dc.description.abstractMental fatigue is a common phenomenon with implicit and multidimensional properties. It brings dynamic changes of functional brain networks. However, the challenging problem of false positives appears when the connectivity is estimated by Electroencephalography (EEG). In this paper, we propose a novel framework based on spatial clustering to explore the sources of mental fatigue and functional activity changes caused by them. To suppress the false positive observations, spatial clustering is implemented in brain networks. The nodes extracted by spatial clustering are registered back to functional magnetic resonance imaging (fMRI) source space to determined the sources of mental fatigue. The wavelet entropy of EEG in a sliding window is calculated to find the temporal features of mental fatigue. Our experimental results show that the extracted nodes correspond to the fMRI sources across different subjects and different tasks. The entropy values on the extracted nodes demonstrate clearer staged decreasing changes (deactivation). Additionally, the synchronization among the extracted nodes is stronger than that among all the nodes in the deactivation stage. The initial time of the strong synchronized deactivation is consistent with the subjective fatigue time reported by the subjects themselves. It means the synchronization and deactivation corresponds to the subjective feelings of fatigue. Therefore, this functional activity pattern may be caused by the sources of mental fatigue. The proposed framework is useful for a wide range of prolonged functional imaging and fatigue detection studies.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartofseriesIEEE Transactions on Cognitive and Developmental Systems
dc.rightsIn Copyright
dc.subject.otherhenkinen väsymys
dc.subject.otheraivosähkökäyrä
dc.subject.otherelektroenkefalografia
dc.subject.otherspatiotemporaalinen analyysi
dc.subject.othermental fatigue
dc.subject.otherEEG
dc.subject.otherspatiotemporal imaging
dc.subject.otherfunctional connectivity
dc.subject.otherspatial clustering
dc.titleSpatio-temporal Dynamical Analysis of Brain Activity during Mental Fatigue Process
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202002282225
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.description.reviewstatuspeerReviewed
dc.format.pagerange593-606
dc.relation.issn2379-8920
dc.relation.numberinseries3
dc.relation.volume13
dc.type.versionacceptedVersion
dc.rights.copyright© Copyright 2020 IEEE
dc.rights.accesslevelopenAccessfi
dc.subject.ysohermoverkot (biologia)
dc.subject.ysoklusterianalyysi
dc.subject.ysokuvantaminen
dc.subject.ysotoiminnallinen magneettikuvaus
dc.subject.ysoväsymys
dc.subject.ysoEEG
dc.subject.ysosignaalinkäsittely
dc.subject.ysosignaalianalyysi
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p38811
jyx.subject.urihttp://www.yso.fi/onto/yso/p27558
jyx.subject.urihttp://www.yso.fi/onto/yso/p3532
jyx.subject.urihttp://www.yso.fi/onto/yso/p24211
jyx.subject.urihttp://www.yso.fi/onto/yso/p128
jyx.subject.urihttp://www.yso.fi/onto/yso/p3328
jyx.subject.urihttp://www.yso.fi/onto/yso/p12266
jyx.subject.urihttp://www.yso.fi/onto/yso/p26805
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1109/TCDS.2020.2976610
jyx.fundinginformationWe gratefully acknowledge the financial support from the National Natural Science Foundation of China (grant number: 61703069) and the Fundamental Research Funds for the Central Universities (grant number: DUT18RC(4)035).


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