Development of human brain cortical network architecture during infancy.
The brain's mature functional network architecture has been extensively studied but the early emergence of the brain's network organization remains largely unknown. In this study, leveraging a large sample (143 subjects) with longitudinal rsfMRI scans (333 datasets), we aimed to characterize the important developmental process of the brain's functional network architecture during the first 2 years of life. Based on spatial independent component analysis and longitudinal linear mixed effect modeling, our results unveiled the detailed topology and growth trajectories of nine cortical functional networks. Within networks, our findings clearly separated the brains networks into two categories: primary networks were topologically adult-like in neonates while higher-order networks were topologically incomplete and isolated in neonates but demonstrated consistent synchronization during the first 2 years of life (connectivity increases 0.13-0.35). Between networks, our results demonstrated both network-level connectivity decreases (-0.02 to -0.64) and increases (0.05-0.18) but decreasing connections (n = 14) dominated increasing ones (n = 5). Finally, significant sex differences were observed with boys demonstrating faster network-level connectivity increases among the two frontoparietal networks (growth rate was 1.63e-4 per day for girls and 2.69e-4 per day for boys, p < 1e-4). Overall, our study delineated the development of the whole brain functional architecture during the first 2 years of life featuring significant changes of both within- and between-network interactions.
Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Rm 3105, Bioinformatics Building, Chapel Hill, NC, 27599, USA, wgao@email.unc.edu.
Wei
W
Gao
Sarael
S
Alcauter
J Keith
JK
Smith
John H
JH
Gilmore
Weili
W
Lin
D000328:Adult; D000367:Age Factors; D001931:Brain Mapping / Q000379:methods; D002540:Cerebral Cortex / Q000254:growth & development*; D002657:Child Development; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D016014:Linear Models; D008279:Magnetic Resonance Imaging; D008297:Male; D008959:Models, Neurological; D009415:Nerve Net / Q000254:growth & development*; D012189:Retrospective Studies; D012737:Sex Factors