thank you for your reply

I am inputting a T1 anatomical image and 1 run of epi data. I am preprocessing the data without any timing vectors at this point. However, during this, the data is reported as being oblique. So prior to entering the T1 into the uber_subject.py script I am performing a 3dWarp -deoblique correction, then entering in the 3dWarp.HEAD in the script. And for the epi data I am performing a 3dTshift, then using the 3dTshift.HEAD file and performing a 3dWarp -deoblique correction. Then entering the 3dWarp.HEAD file in the script.

Both the tcat and the tshift images being in original view are correct, However, the volreg image being in Talairach View is severely skewed as per the attached image. And the skewing error is only occur on about 30% of the subjects. At this point, i have looked at 49 subjects and about 18 are skewed and the others are correct. Same task and same scanner protocol.

I notice yesterday that the rmepivolreg (original view) is good and the rmepinomask image (Talairach view) is skewed. I looked at these images as the data was being populated just trying to see where in the script the error skewing the data is occurring.

So that is the background and I think it helps clears up some of your questions.

the question regarding the nonlinear alignment to template space, I am not sure to what that is referring. My experience with afni is the andys brain book tutorial and now this data. So I apologize for my lack of experience, and will greatly appreciate any help you can offer.


thank you

jef