Dear AFNI-users,

I have concatenated two sessions from a functional imaging experiment (Session_1 and Session_2). Each session has four different conditions (A, B, C, D). I have modeled each condition separately and estimated coefficients and T-statistics for these conditions using 3dDeconvolve, for which I specified the -concat option. All data were written to an appropriate bucket-file.

The results for the first 8 sub-bricks of this bucket are coefficients and T-statistics for both baseline and linear drift of the two concatenated sessions separately. The next sub-bricks contain coefficients and T-statistics for every condition that I specified.

I'd like to perform a linear test (i.e. define a new contrast) to find out whether there is a difference in brain activation between Session 1 and Session 2 for the contrast D > B. To do this, I could use the -glt option of 3dDeconvolve to assign appropriate weights to the various conditions.

However, for this I need to specify the sub-bricks on which this operation will be performed. I think I have to specify those sub-bricks containing the estimated coefficients for each condition, but I'm not sure whether these coeffs have already been corrected for baseline and linear drift. If for example the coeffs of conditions D and B for Session_1 and Session_2 equal 200 > 100 and 20 > 10 respectively, we will find a difference between both sessions while percentually, there should be none.

I suspect the -concat option has something to do with this, but its exact function is unclear to me. Should I still manually correct for baseline and linear drift while comparing between contrasts from concatenated sessions?

Kind regards,

Rutger Goekoop