I’m trying to perform seed-based functional connectivity analysis, but I noticed that the grid size of the processed epi data from running afni_proc.py are different from those of my seed mask. The mask is in MNI space with dimensions of 91x109x91 2mm voxel size, but the processed epi that results from proc.py is 96x114x96 2mm.
By my understanding, the grid size of the final epi dataset is adopted from the anatomical dataset through coregistration because the anatomical dataset is inputted through the -master option. And, the grid size of the anatomical dataset uses that of the MNI152_2009_SSW template from SSWarper, which I perform before running proc.py. Is that right? Therefore, is there a MNI template for SSWarper which would have a grid size of approximately 182x218x182 1mm, which when the resolution is changed to a voxel size of 2mm for epi data would yield the desired dimensions of 91x109x91 2mm?
Or, is this a simple matter of using 3drefit to adjust the dimensions of the final epi and anat datasets?
The grid of MNI152_2009_template_SSW.nii.gz (is that the file you are using as a base for @SSwarper?) is a 193x229x193 matrix, with 1mm iso voxels; here is part of it’s 3dinfo output:
R-to-L extent: -96.000 [R] -to- 96.000 [L] -step- 1.000 mm [193 voxels]
A-to-P extent: -96.000 [A] -to- 132.000 [P] -step- 1.000 mm [229 voxels]
I-to-S extent: -78.000 [I] -to- 114.000 [S] -step- 1.000 mm [193 voxels]
Fitting 2x2x2 mm^3 voxels in that should lead to a 96x114x96 matrix, I believe, which is what you are observing.
What data set is your “mask” or seed defined in? You mentioned “MNI space”, but there are lots of files that could be. The MNI152_2009_template_SSW.nii.gz looks like MNI152_T1_2009c+tlrc.BRIK.gz or mni_icbm152_t1_tal_nlin_sym_09c.nii from here (just with different brightness scaling):
That seems to overlap precisely (same grid dimensions, unlike for example the “mni_icbm152_t1_tal_nlin_sym_09a.nii” volume, which seems to have fewer axial slices).
The mask was made in FSL with “mni152_t1_2mm_brain,” which I believe uses the MNI152 NLIN 6th Gen asymmetric template. If I want my processed EPI data to fit this template, what afni template would I use for SSwarper and input to the -tlrc base option in afni_proc.py?