Annual research review: growth connectomics--the organization and reorganization of brain networks during normal and abnormal development
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Background: We first give a brief introduction to graph theoretical analysis and its application to the study of brain network topology or connectomics. Within this framework, we review the existing empirical data on developmental changes in brain network organization across a range of experimental modalities (including structural and functional MRI , diffusion tensor imaging, magnetoencephalography and electroencephalography in humans). Synthesis: We discuss preliminary evidence and current hypotheses for how the emergence of network properties correlates with concomitant cognitive and behavioural changes associated with development. We highlight some of the technical and conceptual challenges to be addressed by future developments in this rapidly moving field. Given the parallels previously discovered between neural systems across species and over a range of spatial scales, we also review some recent advances in developmental network studies at the cellular scale. We highlight the opportunities presented by such studies and how they may complement neuroimaging in advancing our understanding of brain development. Finally, we note that many brain and mind disorders are thought to be neurodevelopmental in origin and that charting the trajectory of brain network changes associated with healthy development also sets the stage for understanding abnormal network development. Conclusions: We therefore briefly review the clinical relevance of network metrics as potential diagnostic markers and some recent efforts in computational modelling of brain networks which might contribute to a more mechanistic understanding of neurodevelopmental disorders in future.
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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 Vertes and Bullmore, 2015
Small-world organization appears across brain scales and is proposed to reflect a biological compromise between efficient integration and the expense of long-distance connections.
“This property, which is ubiquitous across vastly different scales of investigation in the brain, is thought to emerge from a biological need to balance the benefits of integration against the costs of long-range wiring (Collin et al., 2013; 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 Vertes and Bullmore, 2015
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“Past reviews have already written eloquently about the rationales for applying this approach to study development (Power et al., 2010; Vertes and Bullmore, 2015), which we will only briefly summarize and expand upon here.”
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“Using the newly emerging developmental connectomics framework, researchers are able to seek the wiring principles of brain white matter tracts [71, 72, 110, 183, 359, 501, 517, 598].”
The Multilayer Connectome of Caenorhabditis elegans
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- Authors
- Vértes, P. E., & Bullmore, E. T.
- Affiliations
- University of Cambridge (GB)
- GlaxoSmithKline (United Kingdom) (GB)
- Corresponding author
- Vértes, Petra E.
- Venue
- Journal of Child Psychology and Psychiatry
- Publisher
- Wiley
- Published
- 2014-12
- Volume
- 56
- Issue
- 3
- Pages
- 299-320
- ISSN
- 0021-9630 (ISSN-L)
- 1469-7610
- PMC
- PMC4359009
- OpenAlex
- W2049130783
- Cited by
- 197
- References
- 181
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 14 · 2023: 12 · 2022: 17 · 2021: 13 · 2020: 25 · 2019: 20 · 2018: 26 · 2017: 18 · 2016: 27 · 2015: 7
- FWCI
- 1.63
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Child Psychology and Psychiatry (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Funders
- Medical Research Council (MR/K020706/1)
- Wellcome Trust
- 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, connectomics, graph theory, brain network topology, structural connectivity, functional connectivity, neurodevelopmental disorders
- MeSH terms
- Brain, Child, Child Development, Electroencephalography, Humans, Magnetic Resonance Imaging, Magnetoencephalography, Connectome, Neurodevelopmental Disorders
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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