I have read a paper on functional connectivity, and in this paper with the help of SPM and DPARSFA, the author wrapped the brain into AAL atlas and then extracted the ROI signals from these regions.
My question is that how can I do the same using afni. The first thing that I need to do(after preprocessing steps like head motion correction and . . . ) is to wrap the brain into AAL atlas. But I don’t know how. The second task is to extract the average time-series of the voxels within each region.
Thank you for your time.
That atlas is popular with SPM. I looked at this a couple years ago and found, it is almost identical to the Eickhoff-Zilles Macro-label atlas based on the N27 dataset that is already included with AFNI. There are minor differences, but I’m sure they won’t be too important. You can judge for yourself with a few commands.
I’ve got the datasets I need in an old mricron directory
afni can always use this directory for atlases
the last empty line confuses the @Atlasize script, so remove that line
head -116 aal.nii.txt > fixed_aal.nii.txt
add -G if you want to make this atlas show up with all other atlases (try it first in place)
@Atlasize -space MNI -lab_file fixed_aal.nii.txt 1 0 -dset aal.nii.gz
compare with the ML macrolabel and MPM atlas from Eickhoff-Zilles
cp ~/abin/MNIa_caez_m*_18+tlrc.* .
@Shift_Volume -MNI_Anat_to_MNI -prefix MNI_caez_ml_18 -dset MNIa_caez_ml_18+tlrc.
use the GUI to compare - underlay, overlay, multiple controllers
You will notice that the shift of MNI_anat to MNI doesn’t produce exactly the same thing. There’s about a 1mm shift in two directions, and a couple regions are very slightly different. Still both the ML and AAL datasets are obviously from the same source. Consider the other atlases like the MPM and the Desai atlases made from Freesurfer segmentation. Also take a look at the other MRIcron atlases. If there’s one you want, it’s usually not more than the few steps above.
Thank you very much for your answer.
Would you please tell me how can I extract each ROI signal? (The mean time series of every voxel within the atlas)
whereami can provide a mask. Resample the mask to the time series resolution with 3dresample. Then 3dTstat -mask can provide the mean across time at each voxel limited to the mask.