Key Points
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Inter-individual differences in a local measure of brain structure — for example, cortical thickness — often co-vary with inter-individual differences in the structure of other brain regions.
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Neuroimaging studies have demonstrated that complex networks of structural co-variance are an important aspect of large-scale human brain organization.
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The mechanisms underlying structural co-variance are unclear, but they are likely to be related to coordinated rates of developmental change in co-varying regions.
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Structural co-variance networks are influenced by genetic, cognitive and behavioural factors and partially recapitulate networks of white matter connections and networks of synchronized brain activity.
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Imaging markers of structural co-variance change dynamically over the course of normal development and are altered by neurological and psychiatric disease.
Abstract
Brain structure varies between people in a markedly organized fashion. Communities of brain regions co-vary in their morphological properties. For example, cortical thickness in one region influences the thickness of structurally and functionally connected regions. Such networks of structural co-variance partially recapitulate the functional networks of healthy individuals and the foci of grey matter loss in neurodegenerative disease. This architecture is genetically heritable, is associated with behavioural and cognitive abilities and is changed systematically across the lifespan. The biological meaning of this structural co-variance remains controversial, but it appears to reflect developmental coordination or synchronized maturation between areas of the brain. This Review discusses the state of current research into brain structural co-variance, its underlying mechanisms and its potential value in the understanding of various neurological and psychiatric conditions.
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Acknowledgements
The Child Psychiatry Branch, US National Institute of Mental Health, is supported by the US National Institutes of Health (NIH) Intramural Research Program. The Behavioural and Clinical Neuroscience Institute, University of Cambridge, is supported by the Wellcome Trust and the Medical Research Council (UK). A.A.-B. is supported by the NIH-Oxford-Cambridge Scholarship Program, the NIH MD/PhD Partnership Program and the UCLA Caltech Medical Scientist Training Program.
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E.B. is employed half-time by the University of Cambridge, UK, and half-time by GlaxoSmithKline (GSK); he holds stock in GSK.
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Glossary
- Correlation
-
When two sets of data are statistically inter-dependent or mutually predictive.
- Topology
-
The pattern of connections or relations between nodes within a network.
- Segregation
-
The existence, in the brain, of relatively distinct anatomical, physiological or functional units.
- Modularity
-
The concept that a network has a community structure and can be decomposed into a set of modules, with each module comprising nodes (brain regions) that are densely connected to each other and sparsely connected to nodes in other modules.
- Integration
-
The capacity of the brain to act as single, unified entity.
- Hubs
-
Topologically important or central nodes.
- Efficiency
-
A measure that is inversely proportional to the lengths of the shortest paths between nodes. In brain networks, the global efficiency is often used as a measure of the overall capacity for parallel information transfer and integrated processing.
- Pleiotropy
-
When a single gene influences many phenotypic traits.
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Alexander-Bloch, A., Giedd, J. & Bullmore, E. Imaging structural co-variance between human brain regions. Nat Rev Neurosci 14, 322–336 (2013). https://doi.org/10.1038/nrn3465
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DOI: https://doi.org/10.1038/nrn3465
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