Hi all,

I've run my preprocessing steps and about to move on to denoising, but I've noticed something strange. The distribution of connectivity values in the original looks very similar to the distribution predicted for after denoising. Whereas in the tutorial videos, the distributions are hugely skewed before denoising, the distributions of my original data already all have roughly a mean value of zero before denoising (see attached plots).

Does this indicated an error in the preprocessing steps somewhere, or a problem with my scans? Or is it nothing to worry about?

Note: I didn't use the default preprocessing pipeline. My analysis is volume-based but calls for subject-space, unsmoothed data, with confounds covaried out. We're preprocessing and denoising in CONN but using FSL and R for the rest. My pipeline was as follows:

• Functional realignment and unwarp (subject motion estimation and correction)
• Functional slice-timing correction
• Functional outlier detection (ART-based identification of outlier scans for scrubbing)
• Functional Direct Coregistration to structural without reslicing (rigid body transformation)
• Functional Segmentation (Grey/White/CSF segmentation)
• Structural Segmentation (Grey/White/CSF estimation)

Many thanks in advance!

Best,

Willem