3dLSS with multiple experimental conditions


I am trying to implement 3dDeconvolve and 3dLSS to model individual trials for MVPA (following Mumford et al. 2012 suggestions). I’ve read the 3dLSS documentation page and other questions on this message board, but I’d like to clarify a step in this process.

The documentation for 3dLSS states for the ‘matrix’ option: “Read the matrix ‘mmm’, which should have been output from 3dDeconvolve via the ‘-x1D’ option, and should have included exactly one ‘-stim_times_IM’ option.”

Regarding the instructions ‘exactly one -stim_times_IM option’ - suppose I have 3 conditions of interest in my experiment. Does this mean that when running 3dDeconvolve, that I can only specify -stim_times_IM for one of those conditions? Would this mean that I would have to run 3dDeconvolve three separate times and each time specify -stim_times_IM for one of the conditions?

Alternatively, I was thinking I can merge all the stim times for my conditions into one .1D stim times file. Then I could run 3dDeconvolve and specify -stim_times_IM for that one merged condition, and proceed with using 3dLSS from there.

Please advise what approach would be best. Thank you so much for the help and clarification.

The approach with 3 separate runs is more faithful to the modeling idea of finding differences between/among the varying stimuli. In the 1 big run approach, the separate stimuli that are glued together will get fit with 1 beta, except for the left-out individual stimulus. In the 3 run approach, the different stimuli (again, except the left-out one) will get 3 different betas, which should be slightly better.

Of course, you could try both methods, and see if your results are markedly different. I don’t think they would be, since in the end you are mostly interested in the betas that come from the left-out stimuli, and the other betas are background piffle. So perhaps estimating background piffle slightly more correctly won’t really matter. Perhaps.