Hi experts,

I am running a resting state analysis in an older clinical sample. For preprocessing, I applied SSWarper and the recon-all pipeline to the anatomical images and stuck closely to example 11 for proc.py. I used slightly higher censor (0.3mm) and outlier fraction (0.10) limits because I am working with a special population.

Rick mentioned in the "Start to Finish Hands-On" video from your YouTube channel that when viewing the radcor images in the HTML output you may see some effects of motion in the radcor*tcat image but that this motion is hopefully corrected in the radcor*volreg image. When viewing my data, I saw in some participants that the radcor*tcat image looks just as noisy as the radcor*tcat image, mostly with voxels rimming the edge of the brain suggesting effects of motion. I've attached an image here for reference. For context, the summary motion parameters in this participant are:
average motion per TR = 0.14
average censored motion = 0.13
max motion displacement = 0.59

Is there anything I can do in AFNI to adjust these particularly noisy datasets?

Thank you!
Jenna