The development of hub architecture in the human functional brain network
Open accessAbstract
Functional hubs are brain regions that play a crucial role in facilitating communication among parallel, distributed brain networks. The developmental emergence and stability of hubs, however, is not well understood. The current study used measures of network topology drawn from graph theory to investigate the development of functional hubs in 99 participants, 10-20 years of age. We found that hub architecture was evident in late childhood and was stable from adolescence to early adulthood. Connectivity between hub and non-hub ("spoke") regions, however, changed with development. From childhood to adolescence, the strength of connections between frontal hubs and cortical and subcortical spoke regions increased. From adolescence to adulthood, hub-spoke connections with frontal hubs were stable, whereas connectivity between cerebellar hubs and cortical spoke regions increased. Our findings suggest that a developmentally stable functional hub architecture provides the foundation of information flow in the brain, whereas connections between hubs and spokes continue to develop, possibly supporting mature cognitive function.
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There is convergent evidence that locations of high-strength and high-betweenness hub regions are stable after 5 years of age.
“Returning to the MRI literature, there is convergent evidence that the locations of high-strength and high-betweenness hub regions appear to be stable after 5 years of age (Cao et al., 2014; Grayson et al., 2014; Hwang et al., 2013; Wang et al., 2012; Wu et al., 2013; Zuo et al., 2012).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Hwang et al., 2013
Specific connections to cortical hub regions increase during childhood and adolescence, resulting in increased rich club coefficients in adulthood.
“More detailed network analyses have revealed that specific connections to cortical hub regions increase during childhood and adolescence (Grayson et al., 2014; Hwang et al., 2013) resulting in increased rich club coefficients in adulthood (Cao et al., 2014; Grayson et al., 2014).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Hwang et al., 2013
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Self-citation
- Authors
- Hwang, K., Hallquist, M. N., & Luna, B.
- Affiliations
- University of Pittsburgh (US)
- Corresponding author
- Hwang, Kai
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-08-08
- Volume
- 23
- Issue
- 10
- Pages
- 2380-2393
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- PMC
- PMC3767958
- OpenAlex
- W2163031178
- Cited by
- 226
- References
- 73
- Citations by year
- 2026: 5 · 2025: 13 · 2024: 7 · 2023: 15 · 2022: 25 · 2021: 14 · 2020: 8 · 2019: 20 · 2018: 27 · 2017: 16 · 2016: 21 · 2015: 22 · 2014: 19 · 2013: 13 · 2012: 1
- FWCI
- 8.89
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cerebral Cortex (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Mental Health (R01MH080243, F32MH090629, R01MH067924)
- National Center for Research Resources (P41RR006009)
- 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
- brain network development, network topology, graph theory, frontal cortex, cerebellum, subcortical structures, childhood, adolescence, early adulthood, distributed brain networks
- MeSH terms
- Adolescent, Brain, Child, Humans, Magnetic Resonance Imaging, Models, Neurological, Nerve Net, Neural Pathways, Rest, Young Adult
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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