Changes in structural and functional connectivity among resting-state networks across the human lifespan
Abstract
At rest, the brain's sensorimotor and higher cognitive systems engage in organized patterns of correlated activity forming resting-state networks. An important empirical question is how functional connectivity and structural connectivity within and between resting-state networks change with age. In this study we use network modeling techniques to identify significant changes in network organization across the human lifespan. The results of this study demonstrate that whole-brain functional and structural connectivity both exhibit reorganization with age. On average, functional connections within resting-state networks weaken in magnitude while connections between resting-state networks tend to increase. These changes can be localized to a small subset of functional connections that exhibit systematic changes across the lifespan. Collectively, changes in functional connectivity are also manifest at a system-wide level, as components of the control, default mode, saliency/ventral attention, dorsal attention, and visual networks become less functionally cohesive, as evidenced by decreased component modularity. Paralleling this functional reorganization is a decrease in the density and weight of anatomical white-matter connections. Hub regions are particularly affected by these changes, and the capacity of those regions to communicate with other regions exhibits a lifelong pattern of decline. Finally, the relationship between functional connectivity and structural connectivity also appears to change with age; functional connectivity along multi-step structural paths tends to be stronger in older subjects than in younger subjects. Overall, our analysis points to age-related changes in inter-regional communication unfolding within and between resting-state networks.
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Structural connectivity shapes and constrains functional networks throughout life.
“Second, structural connectivity shapes and constrains functional networks across the lifespan (Betzel et al., 2014; Hagmann et al., 2012; Vertes and Bullmore, 2015).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Betzel et al., 2014
Age-related changes in functional connectivity disproportionately impact polysynaptic connections, though the study spanned the lifespan and may reflect aging.
“Another study found that age-related changes in FC disproportionately impacts polysynaptic connections (Betzel et al., 2014), although this study was performed across the lifespan and may reflect an effect of aging.”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Betzel et al., 2014
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- Authors
- Betzel, R. F., Byrge, L., He, Y., Goñi, J., Zuo, X.-N., & Sporns, O.
- Affiliations
- Indiana University Bloomington (US)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Sporns, Olaf
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2014-11
- Volume
- 102
- Pages
- 345-357
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2090495290
- Cited by
- 807
- References
- 95
- Citations by year
- 2026: 35 · 2025: 72 · 2024: 75 · 2023: 76 · 2022: 86 · 2021: 97 · 2020: 83 · 2019: 59 · 2018: 76 · 2017: 62 · 2016: 45 · 2015: 39 · 2014: 2
- FWCI
- 27.51
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Institutional Repository of Institute of Psychology, Chinese Academy of Sciences (Institute of Psychology, Chinese Academy of Sciences) (submittedVersion)
- Funders
- National Science Foundation/Integrative Graduate Education and Research Traineeship Training Program in the Dynamics of Brain–Body–Environment Systems (0903495)
- National Science Foundation
- JS McDonnell Foundation (22002082)
- Chinese Academy of Sciences (KSZD-EW-TZ-002)
- National Natural Science Foundation of China (81171409, 81220108014)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- resting-state networks, functional connectivity, structural connectivity, aging, brain network reorganization, hub regions, white matter connections, network modularity, default mode network, dorsal attention network, control network, visual network, interregional communication
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Aging, Brain, Brain Mapping, Child, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Models, Neurological, Nerve Net, Rest, Young Adult, Diffusion Tensor Imaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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