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基于近红外功能光谱的独立成分分析衍生的静息态功能连接的重测评估。

Test-retest assessment of independent component analysis-derived resting-state functional connectivity based on functional near-infrared spectroscopy.

机构信息

State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, PR China.

出版信息

Neuroimage. 2011 Mar 15;55(2):607-15. doi: 10.1016/j.neuroimage.2010.12.007. Epub 2010 Dec 10.

Abstract

Recent studies of resting-state functional near-infrared spectroscopy (fNIRS) have emerged as a hot topic and revealed that resting-state functional connectivity (RSFC) is an inherent characteristic of the resting brain. However, it is currently unclear if fNIRS-based RSFC is test-retest reliable. In this study, we utilized independent component analysis (ICA) as an effective RSFC detection tool to address the reliability question. Sixteen subjects participated in two resting-state fNIRS recording sessions held 1week (6.88±1.09 days) apart. Then, RSFC in the sensorimotor regions was extracted using ICA. Test-retest reliability was assessed for intra- and inter-sessions, at both individual and group levels, and for different hemoglobin concentration signals. Our results clearly demonstrated that map-wise reliability was excellent at the group level (with Pearson's r coefficients up to 0.88) and generally fair at the individual level. Cluster-wise reliability was better at the group level (having reproducibility indices of up to 0.97 for the size and up to 0.80 for the location of the detected RSFC) and was weaker but still fair at the individual level (0.56 and 0.46 for intra- and inter-session reliabilities, respectively). Cluster-wise intra-class correlation coefficients (ICCs) also exhibited fair-to-good reliability (with single-measure ICC up to 0.56), while channel-wise single-measure ICCs indicated lower reliability. We conclude that fNIRS-based, ICA-derived RSFC is an essential and reliable biomarker at the individual and group levels if interpreted in map- and cluster-wise manners. Our results also suggested that channel-wise individual-level RSFC results should be interpreted with caution if no optode co-registration procedure had been conducted and indicated that "cluster" should be treated as a minimal analytical unit in further RSFC studies using fNIRS.

摘要

最近的静息态近红外光谱功能磁共振(fNIRS)研究成为一个热点,揭示了静息态功能连接(RSFC)是静息态大脑的固有特征。然而,目前还不清楚基于 fNIRS 的 RSFC 是否具有测试-重测可靠性。在这项研究中,我们利用独立成分分析(ICA)作为有效的 RSFC 检测工具来解决可靠性问题。16 名被试者参加了两次静息态 fNIRS 记录,两次记录间隔 1 周(6.88±1.09 天)。然后,使用 ICA 提取感觉运动区域的 RSFC。在个体和组水平上,以及在不同的血红蛋白浓度信号上,评估了 intra-和 inter-sessions 的测试-重测可靠性。我们的结果清楚地表明,在组水平上,图谱的可靠性非常好(Pearson's r 系数高达 0.88),而在个体水平上通常是公平的。在组水平上,聚类的可靠性更好(检测到的 RSFC 的大小可达 0.97,位置可达 0.80),在个体水平上稍弱但仍然公平( intra-和 inter-sessions 的可重复性指数分别为 0.56 和 0.46)。聚类内类间相关系数(ICC)也表现出良好的可靠性(单测量 ICC 高达 0.56),而通道单测量 ICC 则显示出较低的可靠性。我们得出结论,如果以图谱和聚类的方式进行解释,基于 fNIRS 的、ICA 衍生的 RSFC 是个体和组水平上的重要且可靠的生物标志物。我们的结果还表明,如果没有进行光极配准程序,应该谨慎解释通道水平上的个体水平 RSFC 结果,并表明在使用 fNIRS 的进一步 RSFC 研究中,“聚类”应被视为最小的分析单位。

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