Hub Patterns-Based Detection of Dynamic Functional Network Metastates in Resting State: A Test-Retest Analysis - Zhao, Xin; Wu, Qiong; Chen, Yuanyuan; Song, Xizi; Ni, Hongyan; Ming, Dong (Frontiers in Neuroscience, 2019)
The spontaneous dynamic characteristics of resting-state functional connectivity can reflect the internal brain characteristics and reveal the physiological or pathological changes of brain. The microstate of the brain dynamic functional network is a quantitative method to characterize the essence of the dynamic functional network. However, there is a lack of easily understandable and highly reliable microstate detection method. In this study, we presented a microstate detection method based on dynamic node centrality clustering and designed a test-retest experiment. Twenty-three healthy young volunteers (ages 21–26) were recruited and retested with one week interval. The results showed high reliability between two scans in the microstate representation of spontaneous dynamic functional networks, and the microstate reflected the modularization of the intrinsic functional systems. What’s more, this study explored the coupling relationship between these states and the structural network based on fiber connection, which revealed that the spontaneous dynamic functional network were highly coupled with the structural network. We found that the brain functional networks can not only spatially but also temporally reflect the segregation and integration of intrinsic functional system.