title: Structural and Maturational Covariance in Early Childhood Brain Development.
abstract: Brain structural covariance networks (SCNs) composed of regions with correlated variation are altered in neuropsychiatric disease and change with age. Little is known about the development of SCNs in early childhood, a period of rapid cortical growth. We investigated the development of structural and maturational covariance networks, including default, dorsal attention, primary visual and sensorimotor networks in a longitudinal population of 118 children after birth to 2 years old and compared them with intrinsic functional connectivity networks. We found that structural covariance of all networks exhibit strong correlations mostly limited to their seed regions. By Age 2, default and dorsal attention structural networks are much less distributed compared with their functional maps. The maturational covariance maps, however, revealed significant couplings in rates of change between distributed regions, which partially recapitulate their functional networks. The structural and maturational covariance of the primary visual and sensorimotor networks shows similar patterns to the corresponding functional networks. Results indicate that functional networks are in place prior to structural networks, that correlated structural patterns in adult may arise in part from coordinated cortical maturation, and that regional co-activation in functional networks may guide and refine the maturation of SCNs over childhood development.
authors.affiliation: Department of Psychiatry.|State Key Lab of Brain and Cognitive Sciences, University of Hong Kong, Hong Kong, Hong Kong.|Laboratory of Neuropsychology and Laboratory of Social Cognitive and Affective Neuroscience, University of Hong Kong.
authors.forename: Xiujuan
authors.initials: X
authors.lastname: Geng
authors.affiliation: IDEA Lab, Department of Radiology and BRIC.
authors.forename: Gang
authors.initials: G
authors.lastname: Li
authors.affiliation: Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA.
authors.forename: Zhaohua
authors.initials: Z
authors.lastname: Lu
authors.affiliation: Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, NC 27514, USA.
authors.forename: Wei
authors.initials: W
authors.lastname: Gao
authors.affiliation: IDEA Lab, Department of Radiology and BRIC.
authors.forename: Li
authors.initials: L
authors.lastname: Wang
authors.affiliation: IDEA Lab, Department of Radiology and BRIC.|Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea.
authors.forename: Dinggang
authors.initials: D
authors.lastname: Shen
authors.affiliation: Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA.
authors.forename: Hongtu
authors.initials: H
authors.lastname: Zhu
authors.affiliation: Department of Psychiatry.
authors.forename: John H
authors.initials: JH
authors.lastname: Gilmore
mesh_terms: D001921:Brain / Q000000981:diagnostic imaging / Q000254:growth & development* / Q000502:physiology; D002657:Child Development; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008279:Magnetic Resonance Imaging; D008297:Male; D009434:Neural Pathways / Q000000981:diagnostic imaging / Q000254:growth & development / Q000502:physiology; D009929:Organ Size; D012727:Sex Characteristics
keywords: cortical thickness; early brain development; functional connectivity; maturational covariance; structural covariance