Optimizing Jittered ISI and ITI in AFNI for fMRI Experiment

Hello AFNI community!

I am currently in the process of designing an fMRI experiment, and would greatly appreciate your guidance in generating optimal jittered Inter-Stimulus Interval (ISI) and Inter-Trial Interval (ITI) times. My planned task trials include a 2.5-second decision phase, followed by a jittered ISI, a 1-second feedback phase, and then a jittered ITI.

I currently plan to have 60 trials per run. Within each run, there are two conditions for the decision phase (30 trials of each type). Additionally, there are three possible feedback options (20 trials of positive feedback, 20 trials of neutral feedback, and 20 trials of negative feedback) during the feedback phase.

Initially, I was advised to use optseq2 from Freesurfer to achieve this optimization. However, I wanted to ask if there is an AFNI program that can accomplish this task. I kindly request any insights, suggestions, or recommended tools within AFNI that can assist me in efficiently and accurately optimizing the ISI and ITI timings for my study.

Thank you all in advance for your expertise and support!

With gratitude,
Camille

Hi, Camille-

Rick will be back soon to comment more on this, but in the meantime, make_random_timing.py is probably a good thing to check out:
make_random_timing.py online help

And then there is timing_tool.py for working with and evaluating timing:
timing_tool.py online help

--pt

Wonderful! Thank you both so much :)

I'll look into this documentation in the meantime!