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Cited by 440Functional Brain Connectivity StudiesAdvanced Neuroimaging Techniques and ApplicationsComplex Network Analysis Techniques

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Topological organization of the human brain functional connectome across the lifespan

Open access
Cao, Miao, Wang, Jin-Hui, Dai, Zheng-Jia, Cao, Xiao-Yan, Jiang, Li-Li, Fan, Feng-Mei, Song, Xiao-Wei, Xia, Ming-Rui, Shu, Ni, Dong, Qi, Milham, Michael P., Castellanos, F. Xavier, Zuo, Xi-Nian, He, Yong·2014·Developmental Cognitive Neuroscience
DOI 10.1016/j.dcn.2013.11.004PMC PMC6987957
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Abstract

Human brain function undergoes complex transformations across the lifespan. We employed resting-state functional MRI and graph-theory approaches to systematically chart the lifespan trajectory of the topological organization of human whole-brain functional networks in 126 healthy individuals ranging in age from 7 to 85 years. Brain networks were constructed by computing Pearson's correlations in blood-oxygenation-level-dependent temporal fluctuations among 1024 parcellation units followed by graph-based network analyses. We observed that the human brain functional connectome exhibited highly preserved non-random modular and rich club organization over the entire age range studied. Further quantitative analyses revealed linear decreases in modularity and inverted-U shaped trajectories of local efficiency and rich club architecture. Regionally heterogeneous age effects were mainly located in several hubs (e.g., default network, dorsal attention regions). Finally, we observed inverse trajectories of long- and short-distance functional connections, indicating that the reorganization of connectivity concentrates and distributes the brain's functional networks. Our results demonstrate topological changes in the whole-brain functional connectome across nearly the entire human lifespan, providing insights into the neural substrates underlying individual variations in behavior and cognition. These results have important implications for disease connectomics because they provide a baseline for evaluating network impairments in age-related neuropsychiatric disorders.

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Graphical abstract
Graphical abstract CC BY-NC-ND · PubMed Central
Fig. 1 Illustrations of network measures. A weighted graph composed of 18 nodes and 32 edges is shown as an example. The line thickness represents the connectional weights. (A) depicts the characteristic path length between nodes a and b. There are many ways between nodes a and b, but the shortest one (i.e., the characteristic path length) is 3, indicated by the red lines. (B) shows that the connectivity strength of node c (red color) is calculated as the average of the weights of the edges (red lines) linking with it. Node c is a highly connected hub, with a relatively highly dense connectivity level. All hubs in this graph are shown as larger dots. (C) shows the presence of a clustered module, as indicated by seven nodes (encircled in blue) being mutually strongly interconnected, but sparsely connected to the rest of the network. (D) indicates the rich-club organization (red dots and lines), which is formed by the densely inter-connected hubs c, d and e. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 1 Illustrations of network measures. A weighted graph composed of 18 nodes and 32 edges is shown as an example. The line thickness represents the connectional weights. (A) depicts the characteristic path length between nodes a and b. There are many ways between nodes a and b, but the shortest one (i.e., the characteristic path length) is 3, indicated by the red lines. (B) shows that the connectivity strength of node c (red color) is calculated as the average of the weights of the edges (red lines) linking with it. Node c is a highly connected hub, with a relatively highly dense connectivity level. All hubs in this graph are shown as larger dots. (C) shows the presence of a clustered module, as indicated by seven nodes (encircled in blue) being mutually strongly interconnected, but sparsely connected to the rest of the network. (D) indicates the rich-club organization (red dots and lines), which is formed by the densely inter-connected hubs c, d and e. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)CC BY-NC-ND · PubMed Central
Fig. 2 The lifespan trajectories of functional network efficiency and modularity. (A) The lifespan trajectory of absolute network global efficiency, local efficiency and modularity. (B) The lifespan trajectory of relative network global efficiency, local efficiency and modularity. The dark dots represent the adjusted results of each subject after regressing out sex, head motion and image quality. The curve fits are shown by the dark lines; the red pentagrams represent the peak age. The solid lines show the significant relationships, while the dotted lines show the non-significant trends.
Fig. 2 The lifespan trajectories of functional network efficiency and modularity. (A) The lifespan trajectory of absolute network global efficiency, local efficiency and modularity. (B) The lifespan trajectory of relative network global efficiency, local efficiency and modularity. The dark dots represent the adjusted results of each subject after regressing out sex, head motion and image quality. The curve fits are shown by the dark lines; the red pentagrams represent the peak age. The solid lines show the significant relationships, while the dotted lines show the non-significant trends.CC BY-NC-ND · PubMed Central
Fig. 3 Whole-brain rFCS patterns. (A) The hub probability map across all subjects. For each individual subject, the hubs were defined as the regions with an rFCS greater than 1 SD beyond the mean. (B) The group-averaged rFCS map. (C) The adjusted rFCS maps for every decade. The adjusted rFCS values for each region for different ages were obtained after regressing out sex, motion and image quality using the fitted general linear models selected by AIC.
Fig. 3 Whole-brain rFCS patterns. (A) The hub probability map across all subjects. For each individual subject, the hubs were defined as the regions with an rFCS greater than 1 SD beyond the mean. (B) The group-averaged rFCS map. (C) The adjusted rFCS maps for every decade. The adjusted rFCS values for each region for different ages were obtained after regressing out sex, motion and image quality using the fitted general linear models selected by AIC.CC BY-NC-ND · PubMed Central
Fig. 4 Rich-club organization and its lifespan trajectories. (A) The group mean rich-club coefficient curve of brain functional networks for different hub thresholds: rFCS > 0.5, 0.75, 1, 1.25, and 1.5 SD of the mean. A dark gray line indicates Φ, a light gray line for Φrandom and a red line for Φnorm. The figure shows rich-club behavior of the functional brain networks, showing an increasing normalized rich-club coefficient Φnorm for the threshold range. We show the results of the rFCS > SD of the mean threshold to represent the main results. (B) Age-related change in Φnorm. The dark dots represent the adjusted results of each subject after regressing out sex, head motion and data quality effects. The curve fits are shown by the dark lines; the red pentagram represents the peak age. (C) The rich-club origination of the group-averaged connectome. The red dots represent the hub regions, and the blue lines represent the connections between them. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 4 Rich-club organization and its lifespan trajectories. (A) The group mean rich-club coefficient curve of brain functional networks for different hub thresholds: rFCS > 0.5, 0.75, 1, 1.25, and 1.5 SD of the mean. A dark gray line indicates Φ, a light gray line for Φrandom and a red line for Φnorm. The figure shows rich-club behavior of the functional brain networks, showing an increasing normalized rich-club coefficient Φnorm for the threshold range. We show the results of the rFCS > SD of the mean threshold to represent the main results. (B) Age-related change in Φnorm. The dark dots represent the adjusted results of each subject after regressing out sex, head motion and data quality effects. The curve fits are shown by the dark lines; the red pentagram represents the peak age. (C) The rich-club origination of the group-averaged connectome. The red dots represent the hub regions, and the blue lines represent the connections between them. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)CC BY-NC-ND · PubMed Central
Fig. 5 Lifespan rFCS changes. (A) The regions showing significant linear age effects. (B) The regions showing significant quadratic age effects. p < 0.05, FDR correction was performed to correct for multiple comparisons. The bottom row shows the developmental trajectories of certain, typical regions. INS.L, left insula; MPFC.Rm right medial prefrontal cortex; HIP.L, left hippocampus; SMG.R, right supramarginal gyrus. The dark dots represent the results of each subject after adjusting for sex, head motion and data quality. The curve fits are shown by the dark lines; the red dot pentagrams represent the peak age. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 5 Lifespan rFCS changes. (A) The regions showing significant linear age effects. (B) The regions showing significant quadratic age effects. p < 0.05, FDR correction was performed to correct for multiple comparisons. The bottom row shows the developmental trajectories of certain, typical regions. INS.L, left insula; MPFC.Rm right medial prefrontal cortex; HIP.L, left hippocampus; SMG.R, right supramarginal gyrus. The dark dots represent the results of each subject after adjusting for sex, head motion and data quality. The curve fits are shown by the dark lines; the red dot pentagrams represent the peak age. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)CC BY-NC-ND · PubMed Central
Fig. 6 Lifespan trajectories of the network mean connectivity strength and network mean anatomical distance. The dark dots represent the results of each subject after adjusting for sex, head motion and data quality. The curve fits are shown by the dark lines; the red dots represent the peak age. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 6 Lifespan trajectories of the network mean connectivity strength and network mean anatomical distance. The dark dots represent the results of each subject after adjusting for sex, head motion and data quality. The curve fits are shown by the dark lines; the red dots represent the peak age. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)CC BY-NC-ND · PubMed Central
Fig. 7 Distance-dependent changes in the patterns of connectivity across the lifespan. The functional connections were divided into 17 bins based on anatomical distances (in 10-mm steps). The relationships between the numbers/strengths of the connections of each bin and age were explored. (A) The lifespan trajectories of connection numbers. (B) The lifespan trajectories of connection strengths. Color represents the significance of the age effects. Bottom row: typical lifespan trajectories of different changes. The dark dots represent the adjusted results of each subject after regressing out sex, head motion and data quality. The curve fits are shown by the dark lines; the red dots represent the peak age. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 7 Distance-dependent changes in the patterns of connectivity across the lifespan. The functional connections were divided into 17 bins based on anatomical distances (in 10-mm steps). The relationships between the numbers/strengths of the connections of each bin and age were explored. (A) The lifespan trajectories of connection numbers. (B) The lifespan trajectories of connection strengths. Color represents the significance of the age effects. Bottom row: typical lifespan trajectories of different changes. The dark dots represent the adjusted results of each subject after regressing out sex, head motion and data quality. The curve fits are shown by the dark lines; the red dots represent the peak age. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)CC BY-NC-ND · PubMed Central
Fig. 8 The lifespan trajectories of network properties under two low-resolution parcellation schemes. L-Dos, low-resolution Dosenbach et al.’s functional atlas. L-Yeo, low-resolution Yeo et al.’s functional atlas. The dark dots represent the adjusted results of each subject after regressing out sex, head motion and data quality. The curve fits are shown by the dark lines; the red dots represent the peak age. The solid lines show the significant relationships, while the dotted lines show the non-significant trends. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 8 The lifespan trajectories of network properties under two low-resolution parcellation schemes. L-Dos, low-resolution Dosenbach et al.’s functional atlas. L-Yeo, low-resolution Yeo et al.’s functional atlas. The dark dots represent the adjusted results of each subject after regressing out sex, head motion and data quality. The curve fits are shown by the dark lines; the red dots represent the peak age. The solid lines show the significant relationships, while the dotted lines show the non-significant trends. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)CC BY-NC-ND · PubMed Central

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Metadata

Authors
Cao, M., Wang, J.-H., Dai, Z.-J., Cao, X.-Y., Jiang, L.-L., Fan, F.-M., Song, X.-W., Xia, M.-R., Shu, N., Dong, Q., Milham, M. P., Castellanos, F. X., Zuo, X.-N., & He, Y.
Affiliations
  • Beijing Normal University (CN)
  • Nathan Kline Institute for Psychiatric Research (US)
  • Chinese Academy of Sciences (CN)
Corresponding author
Zuo, Xi-Nian
ORCID
Venue
Developmental Cognitive Neuroscience
Publisher
Elsevier BV
Published
2014-01
Volume
7
Pages
76-93
ISSN
1878-9293 (ISSN-L)
DOI
10.1016/j.dcn.2013.11.004
PMC
PMC6987957
OpenAlex
W2093597642
Cited by
440
References
102
Citations by year
2026: 18 · 2025: 30 · 2024: 39 · 2023: 28 · 2022: 33 · 2021: 41 · 2020: 38 · 2019: 51 · 2018: 41 · 2017: 41 · 2016: 32 · 2015: 30 · 2014: 17
FWCI
14.39
Type
journal article
Language
en
Open access
Licence
Locations
  • Developmental Cognitive Neuroscience (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Institutional Repository of Institute of Psychology, Chinese Academy of Sciences (Institute of Psychology, Chinese Academy of Sciences) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Natural Science Foundation (81030028, 31221003, 81171409)
  • National Science Fund for Distinguished Young Scholars (81225012)
  • Major Joint Fund for International Cooperation and Exchange of the National Natural Science Foundation (81220108014)
  • Open Research Fund of the Key Laboratory of Behavioral Science, the Startup Foundation for Distinguished Research Professor (Y0CX492S03)
  • Institute of Psychology, the Hundred Talents Program and the Key Research Program (KSZD-EW-TZ-002)
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
lifespan development, network topology, modularity, rich club, local efficiency, brain network hubs, default mode network, dorsal attention network, resting-state fMRI, graph theory
MeSH terms
Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Aging, Brain, Brain Mapping, Child, Cognition, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Sex Factors, Connectome

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