Hello afni experts,
I did a resting state connectivity with amygdala subregions as seeds (basolateral amygdala, centromedial).
I would like to look at differences in BOLD activation in these regions during the task as well. However, I would like to use the same procedure as the resting state sample. For the resting state sample, the time course was probability weighted, so that the voxels most likely to be apart of each region contributed the most to the signal. Similarly, I would like the voxels most likely to be apart of each subregion contribute the most to the average (from 3dROIstats).
I am doubting it is appropriate to multiply the probability weights to either each individual's t-stats or beta coefficients (or multiplying the probabilities of an average of each individual's beta coefficients from the tents since I used a tent function).
What might be the appropriate way to do this on a task data set?
Thanks,
Emily
