Hello,

As suggested by my AFNI readings, I have been using the @ss_review_driver to check the accuracy of the pre-processing outputs. I have gone through these outputs and the related readings, and I have a few questions regarding what I should be specifically checking at each stage. I am attempting to ensure my outputs are correct and accurate, so I appreciate any clarifications and further reading suggestions.

SS_review_basic:
GCOR: It has been suggested that larger numbers suggest more coherence, which is likely artifactual. Is there a threshold or a value I should look out for?

Average outlier fraction: I have read that, "some outliers are expected, but if a large fraction of voxels in a volume are outliers, the data should be investigated more closely". Is there a threshold or a certain value I should flag? Relatedly, is there a threshold I should use for the number of outliers detected if I am using 0.1 as the cut-off value?

Degrees of freedom: How is this number generated? I have 16 regressors included in my 3dDeconvolve, and I also included motion parameters in my regression model.

Non-baseline Regressors in X-matrix
X.stim.xmat.1D: In this pop-up, should I just be checking to make sure all my regressors of interest are present? What does the Y-axis represent?

Sum_ideal.1D: Are these curves representing the sum of all my regressors of interest across the entire scan? It has been suggested that this output may help find mistakes in the stimulus timing files. Is there something specific I should be keeping an eye out for?

As well, I read that the @ss_review_driver is the minimal checking that should be done on each participant. Are there other "checks" that should be completed?

Thank you in advance for your assistance!

Best,
Tamara