Age-associated reorganization of metabolic brain connectivity in Chinese children
Huang, Zhang, Zhang, Wang, Yan (2020) Age-associated reorganization of metabolic brain connectivity in Chinese children Eur J Nucl Med Mol Imaging (IF: 9.1) 47(2) 235-246Abstract
The human brain develops rapidly from infant to adolescent. Establishment of the brain developmental trajectory is important to understand cognition, behavior, and emotions, as well to evaluate the risk of neuropsychiatric disorders. 18F-FDG PET has been widely used to study brain glucose metabolism, but functional brain segregation and integration based on 18F-FDG PET remains largely unknown.Two hundred one Chinese child patients with extracranial malignancy were retrospectively enrolled as surrogates to healthy children. All images were spatially normalized into MNI space using pediatric brain template, and the 18F-FDG uptakes were calculated for 90 regions using AAL atlas. The group-level metabolic brain network was constructed by measuring Pearson correlation coefficients between each pair of brain regions in an inter-subject manner for infant (1 to 4 years), childhood (5 to 8 years), early adolescent (9 to 12 years), and adolescent (13 to 18 years) group, respectively. Global efficiency of each group was calculated, and the modular architectures were detected by a greedy algorithm.Both metabolic brain network connectivity and global efficiency increased with aging. Brain network was grouped into 4, 6, 4, and 4 modules from infant to adolescent, respectively. The modular architecture dramatically reorganized from childhood to early adolescent. The hubs spatiotemporally rewired. The ratio of the connector hub to the provincial hub increased from infant to early adolescent, but decreased during the adolescent period.The topological properties and modular reorganization of human brain network dramatically changed with age, especially from childhood to early adolescence. These findings would help understand the Chinese developmental trajectory of human brain functional integration and segregation.
Links
http://www.ncbi.nlm.nih.gov/pubmed/31520171http://dx.doi.org/10.1007/s00259-019-04508-z
