Hello,

I was wondering about the best strategies for modeling the hemodynamic response in my task.

We are using a traditional fear conditioning paradigm, with two stimuli (a CS+ paired with a shock and a CS- not paired with a shock). The stimuli are presented for 8 secs and are followed by a jittered 12-20 sec ITI. Our TR is 2sec.

In our lab, we generally use tent functions. We have previously used TENT (0, 14, 8). Does this seem appropriate for this paradigm?

However, I have seen others use mean IRF (which would be GAM in afni proc py). What numbers would I specify for this? Then they used the first 6 images starting from stimulus onset to calculate percent area under the curve? How would I go about doing that?

I have also seen the SIN function. I heard that this function is best suited for paradigm that have few trials. This would fit my paradigm as I only have 5 cs+ and 5 cs-. Would this be a useful approach and what 3 numbers would you recommend in terms of timing and number of sin functions?

Sorry for the lengthy questions....I would appreciate any guidance.

Thanks,

Emily