Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain.
Interspecies comparison
Resting-state fMRI
Structural connectivity
Structure–function relationship
Time series analysis
Journal
Network neuroscience (Cambridge, Mass.)
ISSN: 2472-1751
Titre abrégé: Netw Neurosci
Pays: United States
ID NLM: 101719149
Informations de publication
Date de publication:
2020
2020
Historique:
received:
22
11
2019
accepted:
08
06
2020
entrez:
22
2
2021
pubmed:
23
2
2021
medline:
23
2
2021
Statut:
epublish
Résumé
Intrinsic timescales of activity fluctuations vary hierarchically across the brain. This variation reflects a broad gradient of functional specialization in information storage and processing, with integrative association areas displaying slower timescales that are thought to reflect longer temporal processing windows. The organization of timescales is associated with cognitive function, distinctive between individuals, and disrupted in disease, but we do not yet understand how the temporal properties of activity dynamics are shaped by the brain's underlying structural connectivity network. Using resting-state fMRI and diffusion MRI data from 100 healthy individuals from the Human Connectome Project, here we show that the timescale of resting-state fMRI dynamics increases with structural connectivity strength, matching recent results in the mouse brain. Our results hold at the level of individuals, are robust to parcellation schemes, and are conserved across a range of different timescale- related statistics. We establish a comprehensive BOLD dynamical signature of structural connectivity strength by comparing over 6,000 time series features, highlighting a range of new temporal features for characterizing BOLD dynamics, including measures of stationarity and symbolic motif frequencies. Our findings indicate a conserved property of mouse and human brain organization in which a brain region's spontaneous activity fluctuations are closely related to their surrounding structural scaffold.
Identifiants
pubmed: 33615091
doi: 10.1162/netn_a_00151
pii: netn_a_00151
pmc: PMC7888482
doi:
Types de publication
Journal Article
Langues
eng
Pagination
788-806Informations de copyright
© 2020 Massachusetts Institute of Technology.
Déclaration de conflit d'intérêts
Competing Interests: The authors have declared that no competing interests exist.
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