Dear Ekaterina,

Yes, the low degrees of freedom together with the wide/flat distributions of voxel-to-voxel correlations all indicate that you are effectively attempting to remove "too many" components from your data during denoising, so no sufficient information remains to accurately estimate connectivity from the denoised timeseries. Depending on whether this is a widespread observation (happening for many subjects or just a few outlier subjects) you might want to try less conservative denoising strategies or possibly consider removing individual sessions or subjects if needed. See the following references for a bit more information regarding denoising in the context of quality control:

Morfini, F., Whitfield-Gabrieli, S., & Nieto-Castanon, A. (2023). Functional connectivity MRI Quality Control procedures in CONN. Frontiers in Neuroscience, 17:1092125. https://doi.org/10.3389/fnins.2023.1092125.

Nieto-Castanon, A. (submitted). Preparing fMRI Data for Statistical Analysis. In M. Filippi (Ed.). fMRI techniques and protocols. Springer. https://doi.org/10.48550/arXiv.2210.13564.

Best
Alfonso

Originally posted by Ekaterina Shcheglova: