Adolescent Tuning of Association Cortex in Human Structural Brain Networks
Oxford University Press
MetadataShow full item record
Vasa, F., Seidlitz, J., Romero Garcia, R., Whitaker, K., Rosenthal, G., Vertes, P., Shinn, M., et al. (2017). Adolescent Tuning of Association Cortex in Human Structural Brain Networks. Cerebral Cortex https://doi.org/10.1093/cercor/bhx249
Motivated by prior data on local cortical shrinkage and intracortical myelination, we predicted age-related changes in topological organization of cortical structural networks during adolescence. We estimated structural correlation from magnetic resonance imaging measures of cortical thickness at 308 regions in a sample of N = 297 healthy participants, aged 14–24 years. We used a novel sliding-window analysis to measure age-related changes in network attributes globally, locally and in the context of several community partitions of the network. We found that the strength of structural correlation generally decreased as a function of age. Association cortical regions demonstrated a sharp decrease in nodal degree (hubness) from 14 years, reaching a minimum at approximately 19 years, and then levelling off or even slightly increasing until 24 years. Greater and more prolonged age-related changes in degree of cortical regions within the brain network were associated with faster rates of adolescent cortical myelination and shrinkage. The brain regions that demonstrated the greatest age-related changes were concentrated within prefrontal modules. We conclude that human adolescence is associated with biologically plausible changes in structural imaging markers of brain network organization, consistent with the concept of tuning or consolidating anatomical connectivity between frontal cortex and the rest of the connectome.
adolescence, connectome, development, graph theory, MRI
Is supplemented by: https://doi.org/10.17863/CAM.8856
This work was supported by the Neuroscience in Psychiatry Network, a strategic award by the Wellcome Trust to the University of Cambridge and University College London (Grant no. 095844/Z/11/Z to E.T.B., I.M.G., P.B.J., P.F., and R.J.D.). Additional support was provided by the National Institute for Health Research Cambridge Biomedical Research Centre and the Medical Research Council (MRC)/Wellcome Trust Behavioural and Clinical Neuroscience Institute. F.V. was supported by the Gates Cambridge Trust. J.S. was supported by the National Institutes of Health (NIH)-Oxford/Cambridge Scholars Program. K.J.W. was supported by a Mozilla Science Lab Fellowship and the Alan Turing Institute under an Engineering and Physical Research Council (EPSRC) grant (EP/N510129/1). P.E.V. was supported by a Medical Research Council (MRC) Bioinformatics Research Fellowship (MR/K020706/1). M.S. was supported by the Winston Churchill Foundation of the United States. A.A.B. was supported by National Institutes of Mental Health (NIMH) Integrated Mentored Patient-Oriented Research Training (IMPORT) in Psychiatry (R25 MH071584).
Wellcome Trust (095844/Z/11/Z)
MEDICAL RESEARCH COUNCIL (G0001354)
External DOI: https://doi.org/10.1093/cercor/bhx249
This record's URL: https://www.repository.cam.ac.uk/handle/1810/268173
Recommended or similar items
The following licence files are associated with this item: