Back to Search Start Over

Dynamic Functional Connectivity between order and randomness and its evolution across the human adult lifespan.

Authors :
Battaglia D
Boudou T
Hansen ECA
Lombardo D
Chettouf S
Daffertshofer A
McIntosh AR
Zimmermann J
Ritter P
Jirsa V
Source :
NeuroImage [Neuroimage] 2020 Nov 15; Vol. 222, pp. 117156. Date of Electronic Publication: 2020 Jul 19.
Publication Year :
2020

Abstract

Functional Connectivity (FC) during resting-state or task conditions is not static but inherently dynamic. Yet, there is no consensus on whether fluctuations in FC may resemble isolated transitions between discrete FC states rather than continuous changes. This quarrel hampers advancing the study of dynamic FC. This is unfortunate as the structure of fluctuations in FC can certainly provide more information about developmental changes, aging, and progression of pathologies. We merge the two perspectives and consider dynamic FC as an ongoing network reconfiguration, including a stochastic exploration of the space of possible steady FC states. The statistical properties of this random walk deviate both from a purely "order-driven" dynamics, in which the mean FC is preserved, and from a purely "randomness-driven" scenario, in which fluctuations of FC remain uncorrelated over time. Instead, dynamic FC has a complex structure endowed with long-range sequential correlations that give rise to transient slowing and acceleration epochs in the continuous flow of reconfiguration. Our analysis for fMRI data in healthy elderly revealed that dynamic FC tends to slow down and becomes less complex as well as more random with increasing age. These effects appear to be strongly associated with age-related changes in behavioural and cognitive performance.<br /> (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1095-9572
Volume :
222
Database :
MEDLINE
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
32698027
Full Text :
https://doi.org/10.1016/j.neuroimage.2020.117156