Functional connectivity during resting-state FMRI: study of the correspondence between independent component analysis (ICA) and region-of-interest (ROI)-based methods

Background and purpose: 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. Materials and methods: 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." Results: 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). Conclusions: There is a significant but not complete correspondence between the results provided by ICA and ROI-based analysis of resting-state data