Thanks for the X-matrix.

Perhaps this is not a truncation issue, which would have been bad, given that all the times were nice multiples of 1.1. A truncation issue might be found if some regressors had very small maximums. But that is not the case here, they are all basically 1.

There might be near multicollinearity in the system, making the solution unstable. The main warning of this would come from 3dDeconvolve (and therefore afni_proc.py -> @ss_review_driver or the QC HTML pages). There should be screen output and a file called 3dDeconvolve.err that should complain about the condition number of the matrix (the ratio of the largest to smallest eigenvalue).

One thing you could try is changing TENT to TENTzero. Instead of having 27 regressors per class, you would drop to 25, with the assumption that the endpoints are zero. If this changes the results a lot, then multicollinearity is a concern.

Can you give that a try?

- rick