Transient states of network connectivity are atypical in autism: A dynamic functional connectivity study.
autism spectrum disorder
default mode network
dynamic functional connectivity
functional MRI
resting state
Journal
Human brain mapping
ISSN: 1097-0193
Titre abrégé: Hum Brain Mapp
Pays: United States
ID NLM: 9419065
Informations de publication
Date de publication:
01 06 2019
01 06 2019
Historique:
received:
12
02
2018
accepted:
09
01
2019
pubmed:
27
1
2019
medline:
14
4
2020
entrez:
26
1
2019
Statut:
ppublish
Résumé
There is ample evidence of atypical functional connectivity (FC) in autism spectrum disorders (ASDs). However, transient relationships between neural networks cannot be captured by conventional static FC analyses. Dynamic FC (dFC) approaches have been used to identify repeating, transient connectivity patterns ("states"), revealing spatiotemporal network properties not observable in static FC. Recent studies have found atypical dFC in ASDs, but questions remain about the nature of group differences in transient connectivity, and the degree to which states persist or change over time. This study aimed to: (a) describe and relate static and dynamic FC in typical development and ASDs, (b) describe group differences in transient states and compare them with static FC patterns, and (c) examine temporal stability and flexibility between identified states. Resting-state functional magnetic resonance imaging (fMRI) data were collected from 62 ASD and 57 typically developing (TD) children and adolescents. Whole-brain, data-driven regions of interest were derived from group independent component analysis. Sliding window analysis and k-means clustering were used to explore dFC and identify transient states. Across all regions, static overconnnectivity and increased variability over time in ASDs predominated. Furthermore, significant patterns of group differences emerged in two transient states that were not observed in the static FC matrix, with group differences in one state primarily involving sensory and motor networks, and in the other involving higher-order cognition networks. Default mode network segregation was significantly reduced in ASDs in both states. Results highlight that dynamic approaches may reveal more nuanced transient patterns of atypical FC in ASDs.
Identifiants
pubmed: 30681228
doi: 10.1002/hbm.24529
pmc: PMC6549695
mid: NIHMS1013499
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
2377-2389Subventions
Organisme : NIMH NIH HHS
ID : K01 MH097972
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH101173
Pays : United States
Organisme : National Science Foundation
ID : GRFP 1321850
Pays : International
Organisme : NIMH NIH HHS
ID : R01 MH081023
Pays : United States
Organisme : NIMH NIH HHS
ID : R21 MH102578
Pays : United States
Informations de copyright
© 2019 Wiley Periodicals, Inc.
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