Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy.
AJNR Am J Neuroradiol. 2012 Jan;33(1):180-7. doi: 10.3174/ajnr.A2733. Epub 2011 Oct 13.
The connectivity across brain regions can be evaluated through fMRI either by using ICA or by means of correlation analysis of time courses measured in predefined ROIs. The purpose of this study was to investigate quantitatively the correspondence between the connectivity information provided by the 2 techniques.
In this study, resting-state fMRI data from 40 healthy participants were independently analyzed by using spatial ICA and ROI-based analysis. To assess the correspondence between the results provided by the 2 methods, for all combinations of ROIs, we compared the time course correlation coefficient with the corresponding "ICA coactivation index."
A strongly significant correspondence of moderate intensity was found for 20 ICA components (r = 0.44, P < .001). Repeating the analysis with 10, 15, 25, 30, 35, and 40 components, we found that the correlation remained but was weaker (r = 0.35-0.41).
There is a significant but not complete correspondence between the results provided by ICA and ROI-based analysis of resting-state data.
可以通过 fMRI 利用 ICA 或通过测量预定义 ROI 中的时间序列的相关分析来评估脑区之间的连通性。本研究的目的是定量研究这两种技术提供的连通性信息之间的对应关系。
本研究中，使用空间独立成分分析和基于 ROI 的分析分别对 40 名健康参与者的静息态 fMRI 数据进行独立分析。为了评估这两种方法结果之间的对应关系，我们比较了所有 ROI 组合的时间序列相关系数与相应的“ICA 共激活指数”。
发现 20 个独立成分（r = 0.44，P <.001）具有很强的中等强度的对应关系。重复使用 10、15、25、30、35 和 40 个成分进行分析，我们发现相关性仍然存在，但较弱（r = 0.35-0.41）。
静息态数据的 ICA 和基于 ROI 的分析结果之间存在显著但非完全对应的关系。
