Hi Doug,

funcVol is an individual functional resting state scan. We are doing some clustering analyses and trying to visually compare the clustering across subjects (I would be a bit sketched out trying to quantify the overlap between subjects due to individual differences in anatomy, etc, but just looking at it might give us a clue on what is going on). We do all our analyses in the individual subject's native space, but it's hard to see what the similarities / differences are.

If not bbregister, what would be the correct way to align all subjects to a common space?

Thanks,

Douglas N. Greve wrote:

What is funcVol? An individual functional? If so, then use --12 (12 dof 
to account for scaling). In general, we don't recommend doing cross 
subject registration with BBR as it is really not appropriate for that 
kind of thing.

On 05/03/2018 01:30 PM, David Beeler wrote:

Hi,

I'm trying to register and transform some raw functional data (108x108x72x175, 2mm iso voxels) to MNI space, while keeping the low res dimensions.

I have tried:

bbregister --s MNI152_FS --mov funcVol --reg func2mni.lta --init-fsl --bold

mri_vol2vol --mov funcVol --reg func2mni.lta --o funcVolMNI --fstarg --no-resample --nearest

mri_vol2vol --mov funcVol --reg func2mni.lta --o funcVolMNI --fstarg --no-resample

And this looks pretty good, but not perfect... the functional data is oriented correctly but the brain seems to be a centimeter or two smaller in multiple dimensions, see:

http://web.mit.edu/dsbeeler/www/images/bbregister-mni.png

I'm not too surprised since the MNI brain is blurry and oddly round, but presumably there is a way to do this transformation more accurately. I've run mri_cvs_register for this subject using the --mni flag:

mri_cvs_register --openmp 8 --mni --mov $subjID --outdir $mniDir

And for other applications I use this m3z file to transform volumes between MNI orig.mgz and individual subject orig.mgz, but is there a way to use it to transform functional data to MNI space while keeping the functional dimensions?

I could do:

mri_vol2vol --mov funcVol --targ $SUBJECTS_DIR/$subjID/mri/orig.mgz --reg register.dof6.lta --nearest --o template-in-anat.nii.gz

mri_vol2vol --noDefM3zPath --targ $SUBJECTS_DIR/$subjID/mri/orig.mgz --mov template-in-anat.nii.gz --m3z $mniDir/final_CVSmorph_tocvs_avg35_inMNI152.m3z --o template-in-MNI-m3z.nii.gz --nearest

But not only is this unideal because it requires upsampling the functional data to 256x256x256, it also gets these funky wavy distortions:

http://web.mit.edu/dsbeeler/www/images/m3z-mni.png

Any thoughts are appreciated, thanks!

-DB