In my study, I am planing to use an experimental task which duration depends on subjects' performance. Duration can vary by as much as 6 minutes comparing good and bad performers. My question is, can I use fMRI data with unequal length (from different subjects) within one analysis (standard GLM analysis). Is it methodologically and statistically valid? Or should I somehow make the task equal in length for each subject (for example by extending inter-trial interval or adding rest period at the end)?
You certainly can allow for different lengths of time. You'll need to include the duration as a variable in your model, and perhaps an interaction term between task and duration. This will tell you if there is an effect of duration on success in performing the task
Self-paced fMRI experiments are quite rare. You need to make sure that the self pacing will not bias your ability to detect effects in one group relative to another. For example if one group has a longer ITI (say 10 seconds vs 5 seconds) you will be better able to estimate the BOLD response to those trials. Having a rest period at the end that is just dead time wouldn't buy you anything. Feel free to take behavioral data that you already have on this task and put it into FSL like you are building a single subject design. You don't have to have any real functional data. Take time series you have laying around to make a 4D file that would match your behavioral data. You aren't going to actually run the analysis. You can look at the efficiency of the design when you set up your statistics to judge how the self pacing is affecting your model.
Can you provide more information about the task? That would help clarify if you should have a fixed IT would work. Some tasks are just not optimal to transfer over to the scanner.
There are some direct tools that can handle this kind of data, but if you want to do this task in a two-step procedure, maybe Dynamic Time Warping would be adequate.
- Badges
- Science topic