Resting-State Functional Brain Connectivity: Lessons from Functional Near-Infrared Spectroscopy
Resting-State Functional Brain Connectivity: Lessons from Functional Near-Infrared Spectroscopy
复制标题
静息态功能性大脑连接：功能性近红外光谱的经验教训
DOI：
10.1177/1073858413502707
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发表时间：
2014-04-01
期刊：
影响因子：
5.6
通讯作者：
He, Yong
中科院分区：
文献类型：
--
作者：
Niu, Haijing;He, Yong
静息态功能近红外光谱（R-fNIRS）是一个活跃的领域的兴趣，目前吸引了相当大的关注作为一种新的成像工具，用于研究静息态脑功能。利用血流动力学浓度信号的变化，R-fNIRS测量大脑的低频自发神经活动，结合了便携性，低成本，高时间采样率和参与者身体负担少的优点。在解剖学上分离的区域中自发神经元活动的时间同步被称为静息态功能连接（RSFC）。在过去的几年里，越来越多的机构R-fNIRS RSFC研究导致了许多重要的发现，局部或全脑区域之间的功能整合，通过测量区域间的时间同步。在这里，我们总结了R-fNIRS RSFC方法学的最新进展，从RSFC的检测（例如，基于种子的相关性分析、独立成分分析、全脑相关性分析和图论拓扑分析），到RSFC性能的评估（例如，可靠性，可重复性和有效性），RSFC在研究正常发育和大脑疾病中的应用。本文综述的文献表明，基于R-fNIRS数据的RSFC分析对于健康和患病人群的脑功能研究是有效和可靠的，从而为认知科学和临床提供了一种有前途的成像工具。
Resting-state functional near-infrared spectroscopy (R-fNIRS) is an active area of interest and is currently attracting considerable attention as a new imaging tool for the study of resting-state brain function. Using variations in hemodynamic concentration signals, R-fNIRS measures the brain's low-frequency spontaneous neural activity, combining the advantages of portability, low-cost, high temporal sampling rate and less physical burden to participants. The temporal synchronization of spontaneous neuronal activity in anatomically separated regions is referred to as resting-state functional connectivity (RSFC). In the past several years, an increasing body of R-fNIRS RSFC studies has led to many important findings about functional integration among local or whole-brain regions by measuring inter-regional temporal synchronization. Here, we summarize recent advances made in the R-fNIRS RSFC methodologies, from the detection of RSFC (e.g., seed-based correlation analysis, independent component analysis, whole-brain correlation analysis, and graph-theoretical topological analysis), to the assessment of RSFC performance (e.g., reliability, repeatability, and validity), to the application of RSFC in studying normal development and brain disorders. The literature reviewed here suggests that RSFC analyses based on R-fNIRS data are valid and reliable for the study of brain function in healthy and diseased populations, thus providing a promising imaging tool for cognitive science and clinics.