Hi Cesar, thank you for the input! I have considered 3dlss and discussed it elsewhere on the messageboard, though for a different type of analysis.

Just to clarify, I have about 333 trials, and over 1,300 1.5s TRs. (Where stimuli are repeated ever 4.5 seconds). So there are actually about 2.5 TRs between each stimulus presentation.

Given these numbers, would you recommend sticking with 3dDeconvolve unless their is high collinearlity across regressors? For instance, in the two subjects I've run so far there are (coincidentally) six pairs of regressors with medium-severity collinearity. (In the first subject, collinearity is between 6 pairs of stimuli, but in the second subjcect three of the six collinearity warning correspond to correlations between a simulus and motion regressorss.

Considering that their are 333 total trials, I imagine this is not super concerning. Would you agree or does this make you think 3dlss might be preferable?