Discovering dynamic task-modulated functional networks with specific spectral modes using MEG
Publiceringsår
2020
Upphovspersoner
Zhu, Yongjie; Liu, Jia; Ye, Chaoxiong; Mathiak, Klaus; Astikainen, Piia; Ristaniemi, Tapani; Cong, Fengyu
Abstrakt
Efficient neuronal communication between brain regions through oscillatory synchronization at certain frequencies is necessary for cognition. Such synchronized networks are transient and dynamic, established on the timescale of milliseconds in order to support ongoing cognitive operations. However, few studies characterizing dynamic electrophysiological brain networks have simultaneously accounted for temporal non-stationarity, spectral structure, and spatial properties. Here, we propose an analysis framework for characterizing the large-scale phase-coupling network dynamics during task performance using magnetoencephalography (MEG). We exploit the high spatiotemporal resolution of MEG to measure time-frequency dynamics of connectivity between parcellated brain regions, yielding data in tensor format. We then use a tensor component analysis (TCA)-based procedure to identify the spatio-temporal-spectral modes of covariation among separate regions in the human brain. We validate our pipeline using MEG data recorded during a hand movement task, extracting a transient motor network with beta-dominant spectral mode, which is significantly modulated by the movement task. Next, we apply the proposed pipeline to explore brain networks that support cognitive operations during a working memory task. The derived results demonstrate the temporal formation and dissolution of multiple phase-coupled networks with specific spectral modes, which are associated with face recognition, vision, and movement. The proposed pipeline can characterize the spectro-temporal dynamics of functional connectivity in the brain on the subsecond timescale, commensurate with that of cognitive performance.
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Publikationstyp
Publikationsform
Artikel
Moderpublikationens typ
Tidning
Artikelstyp
En originalartikel
Målgrupp
VetenskapligKollegialt utvärderad
Kollegialt utvärderadUKM:s publikationstyp
A1 Originalartikel i en vetenskaplig tidskriftPublikationskanalens uppgifter
Journal
Förläggare
Volym
218
Artikelnummer
116924
ISSN
Publikationsforum
Publikationsforumsnivå
2
Öppen tillgång
Öppen tillgänglighet i förläggarens tjänst
Ja
Öppen tillgång till publikationskanalen
Delvis öppen publikationskanal
Parallellsparad
Ja
Publiceringsavgift för öppen tillgång €
1424
Betalningsår för den öppen tillgång publiceringsavgiften
2020
Övriga uppgifter
Vetenskapsområden
Data- och informationsvetenskap; Neurovetenskaper; Psykologi
Nyckelord
[object Object],[object Object],[object Object],[object Object]
Publiceringsland
Nederländerna
Förlagets internationalitet
Internationell
Språk
engelska
Internationell sampublikation
Ja
Sampublikation med ett företag
Nej
DOI
10.1016/j.neuroimage.2020.116924
Publikationen ingår i undervisnings- och kulturministeriets datainsamling
Ja