Dear AFNI Community,
So, I currently have an fMRI scan using a rapid adaptation paradigm in which pairs of stimuli are presented during a silent period following an acquisition. Each TR is 3.18s long and the delay is 1.5 so the TA is 1.68s.
I’m wondering how do I tell 3dDeconvolve that the scans are discontinuous, and if it is important to do so. Ultimately what I’d like to do is capture the peak of the bold response associated with each event type (same stimulus presented twice vs. two different stimuli presented).
I read somewhere on the listserve that one strategy was creating dummy trials and then censoring them, but that won’t work here since the TA is not half of the TR. Any advice or previous posts that I may have missed would be very helpful. Thanks!
Dear AFNI community,
just checking in to see if anybody had any advice or needed any additional details. Thank you!
I’ve used these “sparse sampling” designs (where the stimuli are presented in silent gaps between scans) for a couple of studies, and I’ve always just specified the stimulus onset times (using the stim_times flag in 3dDeconvolve) and the HRF function I want to use – that is, you don’t have to tell 3dDeconvolve explicitly that you had a sparse sampling design. For instance, here’s an excerpt from a 3dDeconvolve command I ran recently, where the onset times for three conditions (between, target, and within) are convolved with a gamma function to estimate the HRF.
-stim_times 1 stimuli/between.1D ‘GAM’
-stim_label 1 between
-stim_times 2 stimuli/target.1D ‘GAM’
-stim_label 2 target
-stim_times 3 stimuli/within.1D ‘GAM’
-stim_label 3 within
This is also consistent with the approach used in the literature that I’ve read – here are a couple of references that might be helpful:
Guediche, S., Salvata, C., & Blumstein, S. E. (2013). Temporal cortex reflects effects of sentence context on phonetic processing. Journal of Cognitive Neuroscience, 25(5), 706-718.
Myers, E. B. (2007). Dissociable effects of phonetic competition and category typicality in a phonetic categorization task: An fMRI investigation. Neuropsychologia, 45(7), 1463-1473.
thank you for your help! I had a follow up question then. I may not understand how AFNI performs the regression, but won’t the timing file refer to time points that don’t exist in the functional data (if afni treats the funcitonal data as continuous). Thanks!