title: Predicting individual brain maturity using dynamic functional connectivity.
abstract: Neuroimaging-based functional connectivity (FC) analyses have revealed significant developmental trends in specific intrinsic connectivity networks linked to cognitive and behavioral maturation. However, knowledge of how brain functional maturation is associated with FC dynamics at rest is limited. Here, we examined age-related differences in the temporal variability of FC dynamics with data publicly released by the Nathan Kline Institute (NKI; n = 183, ages 7-30) and showed that dynamic inter-region interactions can be used to accurately predict individual brain maturity across development. Furthermore, we identified a significant age-dependent trend underlying dynamic inter-network FC, including increasing variability of the connections between the visual network, default mode network (DMN) and cerebellum as well as within the cerebellum and DMN and decreasing variability within the cerebellum and between the cerebellum and DMN as well as the cingulo-opercular network. Overall, the results suggested significant developmental changes in dynamic inter-network interaction, which may shed new light on the functional organization of typical developmental brains.
authors.affiliation: College of Mechatronics and Automation, National University of Defense Technology, Changsha China.
authors.forename: Jian
authors.initials: J
authors.lastname: Qin
authors.affiliation: National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing China.
authors.forename: Shan-Guang
authors.initials: SG
authors.lastname: Chen
authors.affiliation: College of Mechatronics and Automation, National University of Defense Technology, Changsha China.
authors.forename: Dewen
authors.initials: D
authors.lastname: Hu
authors.affiliation: College of Mechatronics and Automation, National University of Defense Technology, Changsha China.
authors.forename: Ling-Li
authors.initials: LL
authors.lastname: Zeng
authors.affiliation: College of Mechatronics and Automation, National University of Defense Technology, Changsha China.
authors.forename: Yi-Ming
authors.initials: YM
authors.lastname: Fan
authors.affiliation: National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing China.
authors.forename: Xiao-Ping
authors.initials: XP
authors.lastname: Chen
authors.affiliation: College of Mechatronics and Automation, National University of Defense Technology, Changsha China.
authors.forename: Hui
authors.initials: H
authors.lastname: Shen
keywords: development; fMRI; functional connectivity; low-frequency fluctuation; multivariate pattern analysis