The Transitions Between Dynamic Micro-States Reveal Age-Related Functional Network Reorganization - Chen, Yuanyuan; Liu, Ya-nan; Zhou, Peng; Zhang, Xiong; Wu, Qiong; Zhao, Xin; Ming, Dong (Frontiers in Physiology, 2019)
Normal dynamic changes in the human brain occur with age, yet much remains unknown regarding how the brain develops, matures and ages. Analysing the functional connectivity of the resting-state brain is a powerful method for revealing the intrinsic features of functional networks, and micro-states, the intrinsic patterns of functional connectivity in dynamic network courses, are suggested to be more informative of brain functional changes. The aim of this study was to explore the age-related changes in the micro-states of dynamic functional networks. In this paper, three healthy groups were included: the young (ages 21-32 years), the adult (age 41-54 years) and the old (age 60-86 years) groups. The sliding window correlation method was used to construct the dynamic connectivity networks, and then the micro-states were individually identified with a clustering analysis. The distribution of age-related connectivity variations in several intrinsic networks for each micro-state was analysed then. The micro-states showed substantial age-related changes in the transitions between states but not in the dwelling times. Also there was no age-related reorganization observed within any micro-state. These states showed various distributions of instability in the intrinsic networks, but there were some reorganizations on the transition between them. These results suggested that the identified micro-states represented underlying connectivity patterns in the functional brain system, similar to the intrinsic cognitive networks or resources. In addition, the dynamic transitions between these states were probable mechanisms of reorganization or compensation in functional brain networks with age increasing.