Dynamic functional connectivity revealed by resting-state functional near-infrared spectroscopy

被引：33
作者：
Li, Zhen [1 ,2 ,3 ]
Liu, Hanli [4 ]
Liao, Xuhong [1 ,2 ,3 ]
Xu, Jingping [1 ,2 ,3 ]
Liu, Wenli [1 ,2 ,3 ]
Tian, Fenghua [4 ]
He, Yong [1 ,2 ,3 ]
Niu, Haijing [1 ,2 ,3 ]
机构：
[1] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
[2] Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China
[3] Beijing Normal Univ, Ctr Collaborat & Innovat Brain & Learning Sci, Beijing 100875, Peoples R China
[4] Univ Texas Arlington, Dept Bioengn, Arlington, TX 76019 USA
来源：
BIOMEDICAL OPTICS EXPRESS | 2015年 / 6卷 / 07期
关键词：
STRUCTURAL CONNECTIVITY; BRAIN; NETWORKS; ARCHITECTURE; RESOLUTION; EMERGENCE; FMRI;
D O I：
10.1364/BOE.6.002337
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
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. (C) 2015 Optical Society of America
引用
收藏
页码：2337 / 2352
页数：16
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