Hi all,

I am so sorry for neglecting to include which image this is! I thought I had it in there but seemed to overlook it. This is a result from a GLT of a verb generation condition minus a noise condition (beta as overlay and t-stat as threshold) with blue (low)-red (high) coloring. I can see that I sounded like a bit of a novice in the post and I apologize. I have experience with this type of analysis but it has been about 6 years so I am trying to catch back up. In my old scripts, I never used afni_proc.py but saw the option for automatic TR rejection for motion and outliers. Is there a way to implement this without afni_proc.py?

As for the original issue, I am now getting what I expect after all of your wonderful advice. I think the despiking and additional motion parameters were causing truncation of our effect and overfitting of irrelevant voxels, respectively. When I reran without these options and looked at the full F-stat for the contrast, everything looks great. It does still seem like the largest betas are outside of the brain, but this makes complete sense now with Paul's explanation and the respective paper. Everything within the brain is right in the middle of the color bar (close to 0) compared to the betas outside. Additionally, I was originally told that there was no masking in the SPM script that was used but after digging into it myself, I see that the default was never changed so it indeed was applied. I do like the idea of plotting a voxel's activity against the design. Is there an interface for this type of summary figure?

Thank you again for all of your help,
Brady