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Evidence of regional associations between age-related inter-individual differences in resting-state functional connectivity and cortical thinning revealed through a multi-level analysis.
- Source :
-
NeuroImage [Neuroimage] 2020 May 01; Vol. 211, pp. 116662. Date of Electronic Publication: 2020 Feb 20. - Publication Year :
- 2020
-
Abstract
- Normal aging incurs functional and anatomical alterations in the brain. Cortical thinning, age-related alterations in resting-state functional connectivity (RSFC) and reductions in fractional amplitude of low frequency fluctuations (fALFF) are key components of brain aging that can be studied by neuroimaging. However, the level of association between these processes has not been fully established. We performed an analysis at multiple-levels, i.e. region or connection and modality, to investigate whether the evidence for the effect of aging on fALFF, RSFC and cortical thickness are associated in a large cohort. Our results show that there is a positive association between the level of evidence of age-related effects in all three in the brain. We also demonstrate that on a regional basis the association between RSFC alterations and cortical atrophy may be either positive or negative, which may relate to compensatory mechanisms predicted by the Scaffolding Theory of Aging and Cognition (STAC).<br />Competing Interests: Declaration of competing interest Authors declare that there is no conflict of interest.<br /> (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)
- Subjects :
- Adolescent
Adult
Aged
Aged, 80 and over
Atrophy pathology
Cerebral Cortical Thinning diagnostic imaging
Female
Humans
Individuality
Male
Middle Aged
Multilevel Analysis
Young Adult
Aging pathology
Aging physiology
Cerebral Cortex diagnostic imaging
Cerebral Cortex pathology
Cerebral Cortex physiopathology
Cerebral Cortical Thinning pathology
Connectome methods
Magnetic Resonance Imaging methods
Subjects
Details
- Language :
- English
- ISSN :
- 1095-9572
- Volume :
- 211
- Database :
- MEDLINE
- Journal :
- NeuroImage
- Publication Type :
- Academic Journal
- Accession number :
- 32088317
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2020.116662