Hi Rick,

Thanks for checking that!
I was wondering if you could help potentially give me starting point for how I might go about doing the following in afni.

I would like to use Roy's (2009) tactic for parcellating the amygdala with resting state data into superficial, centromedial, and basolateral subdivisions.

The following steps are:
1.) Include only voxels with a probability of at least 50% of belonging to each subdivision
2.) Each voxel should only be assigned to one subdivision, in cases where there is overlap,such voxels were assigned to the region for which they had the highest probability of inclusion.
3.)Probability weight the voxels, so that those voxels that most reliably belong to each subdivision, contribute the most to the signal of that subivision. (i.e...to minimize effects due to interindividual anatomic variability, each voxels time series was weighted by the probability of inclusion in a given amygdala subdivision, based on the individual variability of the 10 subjects used to construct the orginal anatomical atlas, Amunts 2005)
4.) In each subject, extract the mean time series by averaging across all voxels' probability-weighted time series within each subdivision.

* I am assuming this will involve a lot of 3dcalc functions.....but I was not sure exactly where to start. I would appreciate any guidance you are willing to give!

Thanks,

Emily