compute voxel by voxel standard deviation across subjects

Hello,

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.

Thanks,
Christine

Hi, Christine-

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.

To do “A”:


3dTcat -prefix ALL_SUBJ.nii.gz  DSET_000 DSET_001 DSET_002 ...

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.

To do “B”:


3dTstat -mean -prefix STAT_mean.nii.gz ALL_SUBJ.nii.gz
3dTstat -stdev -prefix STAT_stdev.nii.gz ALL_SUBJ.nii.gz

… and see the full list of stats that can be computed in 3dTstat.

–pt

I will add on to Paul’s advice here.

  1. Consider ‘-stdevNOD’ if you do not want detrending across datasets before computing the standard deviation.

  2. 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”.


3dTstat -stdevNOD -prefix test1sdNOD.nii.gz 'mysubjs/*/PA*.nii.gz'

  1. 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.

3dMean -sd -prefix testsdsd.nii.gz mysubjs/*/PA*.nii.gz

Thank you! I think the 3dmean program is what I was looking for.

Well, I learned some interesting things here, too!

–pt