dc.contributor.author | Zhu, Yongjie | |
dc.contributor.author | Li, Xueqiao | |
dc.contributor.author | Ristaniemi, Tapani | |
dc.contributor.author | Cong, Fengyu | |
dc.date.accessioned | 2020-01-07T16:24:41Z | |
dc.date.available | 2020-01-07T16:24:41Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Zhu, Y., Li, X., Ristaniemi, T., & Cong, F. (2019). Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition. In <i>ICASSP 2019 : Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing</i> (pp. 8593-8597). IEEE. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing. <a href="https://doi.org/10.1109/ICASSP.2019.8682355" target="_blank">https://doi.org/10.1109/ICASSP.2019.8682355</a> | |
dc.identifier.other | CONVID_30533510 | |
dc.identifier.other | TUTKAID_81244 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/67146 | |
dc.description.abstract | The characterization of dynamic electrophysiological brain
activity, which form and dissolve in order to support ongoing
cognitive function, is one of the most important goals in
neuroscience. Here, we introduce a method with tensor
decomposition for measuring the task-induced oscillations in
the human brain using electroencephalography (EEG). The
time frequency representation of source-reconstructed singletrail EEG data constructed a third-order tensor with three
factors of time ∗ trails, frequency and source points. We then
used a non-negative Canonical Polyadic decomposition
(NCPD) to identify the temporal, spectral and spatial changes
in electrophysiological brain activity. We validate this
method using both simulation EEG data and real EEG data
recorded during a task of irony comprehension. The results
demonstrated that proposed method can track dynamics of the
temporal-spectral modes of the rhythm in the brain on a
timescale commensurate to the task they are undertaking. | fi |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | IEEE | |
dc.relation.ispartof | ICASSP 2019 : Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing | |
dc.relation.ispartofseries | Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing | |
dc.rights | In Copyright | |
dc.subject.other | electroencephalography | |
dc.subject.other | task analysis | |
dc.subject.other | brain modeling | |
dc.subject.other | source localization | |
dc.subject.other | neural oscillations | |
dc.subject.other | tensor decomposition | |
dc.title | Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition | |
dc.type | conferenceObject | |
dc.identifier.urn | URN:NBN:fi:jyu-202001071059 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Psykologian laitos | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.laitos | Department of Psychology | en |
dc.contributor.oppiaine | Tietotekniikka | fi |
dc.contributor.oppiaine | Psykologia | fi |
dc.contributor.oppiaine | Mathematical Information Technology | en |
dc.contributor.oppiaine | Psychology | en |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | |
dc.date.updated | 2020-01-07T10:15:18Z | |
dc.relation.isbn | 978-1-4799-8131-1 | |
dc.type.coar | http://purl.org/coar/resource_type/c_5794 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 8593-8597 | |
dc.relation.issn | 1520-6149 | |
dc.type.version | acceptedVersion | |
dc.rights.copyright | © 2019 IEEE | |
dc.rights.accesslevel | openAccess | fi |
dc.relation.conference | IEEE International Conference on Acoustics, Speech and Signal Processing | |
dc.subject.yso | tietomallit | |
dc.subject.yso | oskillaattorit | |
dc.subject.yso | EEG | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p25167 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p6393 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p3328 | |
dc.rights.url | http://rightsstatements.org/page/InC/1.0/?language=en | |
dc.relation.doi | 10.1109/ICASSP.2019.8682355 | |
dc.type.okm | A4 | |