Which program should I use to compute a voxel by voxel standard deviation across subjects?
I have a DTI measure similar to FA and I would like to see the mean and standard deviation (across participants) for this measure for all voxels in the brain.
You can:
A) first, concatenate all the 3D volumes of your subjects across the “time” axis, and then
B) compute the voxelwise stat (mean, stdev, etc.) for each voxel.
where DSET_* are your FA-like volumes for each subject; I’m assuming each one is just a 3D volume; if that is not the case, you could use subbrick selectors, like: DSET_000’[0]’ DSET_001’[0]’ DSET_002’[0]', there instead.
Consider ‘-stdevNOD’ if you do not want detrending across datasets before computing the standard deviation.
Catenated datasets. Many AFNI programs including 3dTstat can take quoted and wildcard datasets as a “single” input dataset. See the 3dcalc help section on “CATENATED AND WILDCARD DATASET NAMES”.
3dMean. If you have a lot of datasets to compute over, this program will do the computations more efficiently because it only loads one dataset at a time rather than all of them at the same time. The option “-sd” can be used to compute the standard deviation.
Well, I learned some interesting things here, too!
–pt
The
National Institute of Mental Health (NIMH) is part of the National Institutes of
Health (NIH), a component of the U.S. Department of Health and Human
Services.