Show simple item record

dc.contributor.authorTewarie, Prejaas
dc.contributor.authorPrasse, Bastian
dc.contributor.authorMeier, Jil
dc.contributor.authorMandke, Kanad
dc.contributor.authorWarrington, Shaun
dc.contributor.authorStam, Cornelis J
dc.contributor.authorBrookes, Matthew J
dc.contributor.authorVan Mieghem, Piet
dc.contributor.authorSotiropoulos, Stamatios N
dc.contributor.authorHillebrand, Arjan
dc.date.accessioned2022-06-07T08:11:35Z
dc.date.available2022-06-07T08:11:35Z
dc.date.issued2022-10-01
dc.date.submitted2022-01-13
dc.identifier.issn1065-9471
dc.identifier.otherhbm25967
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/337759
dc.description.abstractHow temporal modulations in functional interactions are shaped by the underlying anatomical connections remains an open question. Here, we analyse the role of structural eigenmodes, in the formation and dissolution of temporally evolving functional brain networks using resting-state magnetoencephalography and diffusion magnetic resonance imaging data at the individual subject level. Our results show that even at short timescales, phase and amplitude connectivity can partly be expressed by structural eigenmodes, but hardly by direct structural connections. Albeit a stronger relationship was found between structural eigenmodes and time-resolved amplitude connectivity. Time-resolved connectivity for both phase and amplitude was mostly characterised by a stationary process, superimposed with very brief periods that showed deviations from this stationary process. For these brief periods, dynamic network states were extracted that showed different expressions of eigenmodes. Furthermore, the eigenmode expression was related to overall cognitive performance and co-occurred with fluctuations in community structure of functional networks. These results implicate that ongoing time-resolved resting-state networks, even at short timescales, can to some extent be understood in terms of activation and deactivation of structural eigenmodes and that these eigenmodes play a role in the dynamic integration and segregation of information across the cortex, subserving cognitive functions.
dc.languageen
dc.publisherWiley
dc.subjectRESEARCH ARTICLE
dc.subjectRESEARCH ARTICLES
dc.subjectdynamic functional connectivity
dc.subjecteigenmodes
dc.subjectmagnetoencephalography
dc.titlePredicting time-resolved electrophysiological brain networks from structural eigenmodes.
dc.typeArticle
dc.date.updated2022-06-07T08:11:35Z
prism.publicationNameHum Brain Mapp
dc.identifier.doi10.17863/CAM.85168
dcterms.dateAccepted2022-05-16
rioxxterms.versionofrecord10.1002/hbm.25967
rioxxterms.versionAO
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.contributor.orcidTewarie, Prejaas [0000-0002-3311-4990]
dc.contributor.orcidBrookes, Matthew J [0000-0002-8687-8185]
dc.identifier.eissn1097-0193
pubs.funder-project-idH2020 European Research Council (No 101000969)
cam.issuedOnline2022-06


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record