Structural and functional rich club organization of the brain in children and adults
Open accessAbstract
Recent studies using Magnetic Resonance Imaging (MRI) have proposed that the brain's white matter is organized as a rich club, whereby the most highly connected regions of the brain are also highly connected to each other. Here we use both functional and diffusion-weighted MRI in the human brain to investigate whether the rich club phenomena is present with functional connectivity, and how this organization relates to the structural phenomena. We also examine whether rich club regions serve to integrate information between distinct brain systems, and conclude with a brief investigation of the developmental trajectory of rich-club phenomena. In agreement with prior work, both adults and children showed robust structural rich club organization, comprising regions of the superior medial frontal/dACC, medial parietal/PCC, insula, and inferior temporal cortex. We also show that these regions were highly integrated across the brain's major networks. Functional brain networks were found to have rich club phenomena in a similar spatial layout, but a high level of segregation between systems. While no significant differences between adults and children were found structurally, adults showed significantly greater functional rich club organization. This difference appeared to be driven by a specific set of connections between superior parietal, insula, and supramarginal cortex. In sum, this work highlights the existence of both a structural and functional rich club in adult and child populations with some functional changes over development. It also offers a potential target in examining atypical network organization in common developmental brain disorders, such as ADHD and Autism.
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In adulthood, high strength and betweenness hubs are largely located within default mode, attentional, sensorimotor, and visual areas.
“high strength and betweenness hubs in adulthood are largely located within within the default mode, attentional, sensorimotor, and visual areas (Cao et al., 2014; Fransson et al., 2011; Grayson et al., 2014; Hwang et al., 2013)”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Grayson et al., 2014
Among cortical areas, some report increasing hubness of frontal nodes, while other lobes show mixed reports of increasing, decreasing, or stable hubness.
“Among cortical areas, some have reported increasing hubness of frontal nodes (Cao et al., 2014; Wu et al., 2013) while in other lobes there have been mixed reports of increasing (Cao et al., 2014; Grayson et al., 2014) and decreasing (Wu et al., 2013; Zuo et al., 2012), or stable (Hwang et al., 2013) hubness.”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Grayson et al., 2014
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 Grayson et al., 2014
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 Grayson et al., 2014
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- Authors
- Grayson, D. S., Ray, S., Carpenter, S., Iyer, S., Dias, T. G. C., Stevens, C., Nigg, J. T., & Fair, D. A.
- Affiliations
- Oregon Health & Science University (US)
- Corresponding author
- Grayson, David S.
- Fair, Damien A.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-02-05
- Volume
- 9
- Issue
- 2
- Pages
- e88297
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3915050
- OpenAlex
- W2063751901
- Cited by
- 187
- References
- 59
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 12 · 2023: 14 · 2022: 14 · 2021: 14 · 2020: 13 · 2019: 26 · 2018: 19 · 2017: 14 · 2016: 19 · 2015: 18 · 2014: 11
- FWCI
- 11.52
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- James S. McDonnell Foundation (R01 MH096773)
- National Institutes of Health (MH091238, MH086654)
- Oregon Clinical and Translational Research Institute
- National Institute of Mental Health (MH086654, MH091238, R01MH115357, R00MH091238, R01MH096773, MH096773, R01MH086654)
- 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
- rich club, brain network organization, functional connectivity, structural connectivity, white matter, brain development, children, adults, default mode network, dorsal anterior cingulate cortex, posterior cingulate cortex, insula, inferior temporal cortex, supramarginal cortex, functional segregation, attention deficit hyperactivity disorder, autism spectrum disorder
- MeSH terms
- Adult, Brain, Brain Mapping, Child, Female, Humans, Magnetic Resonance Imaging, Male, Models, Anatomic, Models, Neurological, Nerve Net, Neural Pathways, Young Adult, Diffusion Tensor Imaging
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