Hi!

We have an experiment where the subjects rate two different stimuli. Let's say condition A and B where each have 3 onsets of duration 10 and each onset has a rating of pleasentness connected to it.

What we have done is first to run a non-modulated GLM where we just have the onsets and durations. The gives a X.stim.no.censor file where A and B each have 3 spikes/onsets and they have a value of 5 (I guess arbitrary value since we don't limit the stimfile to values between 0-1?).

Now we want to see which regions correlate to the ratings. I.e. we want to do amplitude modulation to each onset. We use [-stim_times_AM2 k tname Rmodel] in the 3dDeconvolve. This is supposed to create 2 models/regressors:

[-stim_times_AM2 k tname Rmodel]                                       
   Similar, but generates 2 response models: one with the mean         
   amplitude and one with the differences from the mean.

This gives us, as expected, one regressor where each onset of duration 10 has the mean rating - onset rating as its value.
The other regressor is exactly the same as in the non modulated stimfile (i.e. all onsets have a value of 5). I thought that the second stimfile should have the average rating as its value?

The problem we run into is that we cannot compare condition A and B since we only get the difference from the mean. If A is rated 9/10 and B is rated 2/10 the regressors might still look the same since we only get the difference from the mean. We are also interesed in regions who differ in pleasenness across conditions, not only differences within each condition.

Do you have any suggestions?