I go t this comments from a reviewer who I think is not too familiar with Conn. What do you think of my replies?

Reviewer: Further analysis is required to confirm that the results are not an artifact of differential motion between groups.

Me: CONN, the toolbox we used for the study, implements the CompCor algorithm which takes into account of head motion reducing the likelihood for artifacts.
The tCompCor approach is based on the identification of voxel time series with high temporal standard deviations, it also identifies voxels with large signal components due to subject motion.


Reviewer: It would also be helpful to conduct a secondary analysis in which global signal regression is included to see if this substantially alters results.

Me: CONN implements a CompCor strategy for physiological noise source reduction, first level General Linear Model for correlation and regression connectivity estimation, and second level random-effect analyses (this is now specified in lines 203-205) in the new version of the manuscript.
Also, as explained in lines 242-247, compared with methods that rely on global signal regression, the component-based noise reduction method allows for interpretation of anticorrelations because there is no regression of the global signal within this method. This approach may enhance the sensitivity and specificity of positive correlations and produce comparable negative correlations (8). This regression procedure removes fluctuations unlikely to be involved in specific regional correlations.