Concatenating runs vs. testing for habituation effects

Hi All,

This is a very basic question.

  1. The AFNI22_Indiana PDF states that you can use AFNI to look across runs to look for habituation effects.
  2. How is this done? Is there an example of how to do use? I am assuming this is a simple command in 3dDeconvolve?
    2b. Would this then require creating separate stimulus timing files for each run and condition. For example:


Currently, we have 4 runs with 3 different conditions. Runs are concatenated and contrasts are analyzed on the group level. Stimulus timing files are one text file with columns referring to events and rows indicating runs.


Within what time frame do you want to capture the habituation effect? With each run, across runs, or from beginning to end (with all runs combined)?

Hi Gang,

Thanks for replying and that is a good question. I guess across runs and from beginning to end (with all runs combined). My data has already been preprocessed and run through 3dMVM, however, we would just like to test for habituation effects over time.

I guess across runs and from beginning to end (with all runs combined).

For habituation effect across runs, you need to analyze the data by treating a separate effect for each run, which means you would have to arrange the stimulus timing files or regressors. Then test the habituation effect across runs with weights discussed here:

For habituation effect from beginning to end, use the weights from the website as modulation values using -stim_times_AM2 in 3dDeconvolve