Dear FSL ninjas, I am writing with a question about model fit and be very grateful for any help.

I have three conditions of different durations (slow = long duration, comf = medium duration, fast = short duration).  Not good, I know.  I am trying

to pull apart whether the difference we see for fast > slow (greater activation in short duration as compared to long duration condition) contrast is due to (a) a true difference in activation between conditions, or (b) differing model fit between the two conditions.

I have tried to get a feel for this by visualizing the raw data and model for each condition (from the peak voxel in a contrast of short duration condition > long duration condition).  As such in the pdf at:
http://dl.dropbox.com/u/6155913/duration_psps.pdf
I have–
- plotted out the peristimulus data for each condition (averaged across all subjects/sessions);
- taken the full model data for the same period
- Used the maxima and the minima from each model to normalize the actual data in that condition

And then plotted these (see pdf, left side of page).

Looking at this, it looks as though there is not a drastic difference in fit in the different conditions – esp. for slow and fast conditions, which is the key point I think.  In each case, the raw data’s peak is about 60% of the value for the model’s peak.

To investigate further, I took the same data and
- normalized all graphs by the maxima and minima for the slow model
- plotted this out (pdf, right side of page)

I am trying to determine now what the exact effect on the beta weights will be, and how to determine the finding of significantly greater betas in the fast as compared to slow condition.  Clarification would be very helpful.

Thanks people

Christopher

- Note: the data used was extracted from tsplot/tsplot_zstat1.txt columns one (data) and three (full model fit).