Dynamic functional connectivity revealed by resting-state functional near-infrared spectroscopy.
The brain is a complex network with time-varying functional connectivity (FC) and network organization. However, it remains largely unknown whether resting-state fNIRS measurements can be used to characterize dynamic characteristics of intrinsic brain organization. In this study, for the first time, we used the whole-cortical fNIRS time series and a sliding-window correlation approach to demonstrate that fNIRS measurement can be ultimately used to quantify the dynamic characteristics of resting-state brain connectivity. Our results reveal that the fNIRS-derived FC is time-varying, and the variability strength (Q) is correlated negatively with the time-averaged, static FC. Furthermore, the Q values also show significant differences in connectivity between different spatial locations (e.g., intrahemispheric and homotopic connections). The findings are reproducible across both sliding-window lengths and different brain scanning sessions, suggesting that the dynamic characteristics in fNIRS-derived cerebral functional correlation results from true cerebral fluctuation.
['Li|Zhen|Z|', 'Liu|Hanli|H|', 'Liao|Xuhong|X|', 'Xu|Jingping|J|', 'Liu|Wenli|W|', 'Tian|Fenghua|F|', 'He|Yong|Y|', 'Niu|Haijing|H|']
(170.2655) Functional monitoring and imaging (170.3880) Medical and biological imaging (170.5380) Physiology