title: The convergence of maturational change and structural covariance in human cortical networks.
abstract: Large-scale covariance of cortical thickness or volume in distributed brain regions has been consistently reported by human neuroimaging studies. The mechanism of this population covariance of regional cortical anatomy has been hypothetically related to synchronized maturational changes in anatomically connected neuronal populations. Brain regions that grow together, i.e., increase or decrease in volume at the same rate over the course of years in the same individual, are thus expected to demonstrate strong structural covariance or anatomical connectivity across individuals. To test this prediction, we used a structural MRI dataset on healthy young people (N = 108; aged 9-22 years at enrollment), comprising 3-6 longitudinal scans on each participant over 6-12 years of follow-up. At each of 360 regional nodes, and for each participant, we estimated the following: (1) the cortical thickness in the median scan and (2) the linear rate of change in cortical thickness over years of serial scanning. We constructed structural and maturational association matrices and networks from these measurements. Both structural and maturational networks shared similar global and nodal topological properties, as well as mesoscopic features including a modular community structure, a relatively small number of highly connected hub regions, and a bias toward short distance connections. Using resting-state functional magnetic resonance imaging data on a subset of the sample (N = 32), we also demonstrated that functional connectivity and network organization was somewhat predictable by structural/maturational networks but demonstrated a stronger bias toward short distance connections and greater topological segregation. Brain structural covariance networks are likely to reflect synchronized developmental change in distributed cortical regions.
authors: Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge CB2 3EB, United Kingdom. jgiedd@mail.nih.gov
authors: Aaron
authors: A
authors: Alexander-Bloch
authors: Armin
authors: A
authors: Raznahan
authors: Ed
authors: E
authors: Bullmore
authors: Jay
authors: J
authors: Giedd
mesh_terms: D000293:Adolescent; D000375:Aging / Q000502:physiology; D000465:Algorithms; D016477:Artifacts; D002540:Cerebral Cortex / Q000166:cytology / Q000254:growth & development* / Q000502:physiology*; D002560:Cerebrovascular Circulation / Q000502:physiology; D002648:Child; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D009415:Nerve Net / Q000166:cytology / Q000254:growth & development* / Q000502:physiology*; D055815:Young Adult