Assessing Brain Networks by Resting-State Dynamic Functional Connectivity: An fNIRS-EEG Study

doi:10.3389/fnins.2019.01430

	Assessing Brain Networks by Resting-State Dynamic Functional Connectivity: An fNIRS-EEG Study
	Zhang, Yujin 1,3; Zhu, Chaozhe 2
刊名	FRONTIERS IN NEUROSCIENCE
	2020-01-24
卷号	13 页码:12
关键词	functional connectivity resting state dynamic functional near-infrared spectroscopy electroencephalogram
DOI	10.3389/fnins.2019.01430
通讯作者	Zhu, Chaozhe(czzhu@bnu.edu.cn)
英文摘要	The coordination of brain activity between disparate neural populations is highly dynamic. Investigations into intrinsic brain organization by evaluating dynamic resting-state functional connectivity (dRSFC) have attracted great attention in recent years. However, there are few dRSFC studies based on functional near-infrared spectroscopy (fNIRS) even though it has some advantages for studying the temporal evolution of brain function. In this research, we recruited 20 young adults and measured their resting-state brain fluctuations in several areas of the frontal, parietal, temporal, and occipital lobes using fNIRS-electroencephalography (EEG) simultaneous recording. Based on a sliding-window approach, we found that the variability of the dRSFC within any region of interest was significantly lower than the connections between region of interests but noticeably greater than the correlation between the channels with a short interoptode distance, which mainly consist of physiological fluctuations occurring in the superficial layers. Furthermore, based on a time-resolved k-means clustering analysis, the temporal evolution was extracted for three dominant functional networks. These networks were roughly consistent between different subject subgroups and in varying sliding time window lengths of 20, 30, and 60 s. Between these three functional networks, there were obvious time-varied and system-specific synchronous relationships. In addition, the oscillation of the frontal-parietal-temporal network showed significant correlation with the switching of one EEG microstate, a finding which is consistent with a previous functional MRI-EEG study. All this evidence implies the functional significance of fNIRS-dRSFC and demonstrates the feasibility of fNIRS for extracting the dominant functional networks based on RSFC dynamics.
资助项目	National Key Research and Development Program of China[2017YFB1002502] ; National Natural Science Foundation of China[81871398] ; National Natural Science Foundation of China[61431002] ; Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning
WOS关键词	SPATIOTEMPORAL DYNAMICS ; EYES OPEN ; VARIABILITY ; CONSCIOUSNESS ; FMRI
WOS研究方向	Neurosciences & Neurology
语种	英语
出版者	FRONTIERS MEDIA SA
WOS记录号	WOS:000512174700001
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/28626]
专题	自动化研究所_类脑智能研究中心
通讯作者	Zhu, Chaozhe
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 2.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China 3.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Yujin,Zhu, Chaozhe. Assessing Brain Networks by Resting-State Dynamic Functional Connectivity: An fNIRS-EEG Study[J]. FRONTIERS IN NEUROSCIENCE,2020,13:12.
APA	Zhang, Yujin,&Zhu, Chaozhe.(2020).Assessing Brain Networks by Resting-State Dynamic Functional Connectivity: An fNIRS-EEG Study.FRONTIERS IN NEUROSCIENCE,13,12.
MLA	Zhang, Yujin,et al."Assessing Brain Networks by Resting-State Dynamic Functional Connectivity: An fNIRS-EEG Study".FRONTIERS IN NEUROSCIENCE 13(2020):12.