> we are satisfied with the results of 3dRegAna, but our struggle is that we cannot
> use all of our subjects because they all do not have a sufficient number of trials
> to generate a reliable beta for each of the three conditions.

My question is, even though some of effect estimates are not reliable due to the meager number of trials, how does the result look like if you just include all the betas regardless of their reliability?

> My suggestion was to code a 3dDeconvolve vector that is zeros for all TRs, except
> when conditions 1, 2, or 3 occur. In that case, the vector would code condition 3 as
> "3", condition 2 as "2", and condition 1 as "1".

I see! However, the weighting set of 1, 2, and 3 would not work. The reason is that, even if there is no trend at all (for example, three random betas), you would get something at a voxel where the region responds to at least one condition.

Nevertheless, I think that you can try the following! It's essentially the amplitude modulation approach that is implemented in option -stim_times_AM2, which requires that you code all the trials via the stimulus onset timing (instead of 0s and 1s). If you insist that you code the stimuli in the old fashion, do this: 1) for the first regressor, code each TR with 1 if one of the conditions occurred, and 0 otherwise; 2) code the second regressor with -1 for condition 1, 0 for condition 2, and 1 for condition 1. I believe you would be able to extract the linear trend from the second regressor, and bring the corresponding beta and its t-value to 3dMEMA!

Gang



Edited 2 time(s). Last edit at 04/14/2014 04:25PM by Gang.