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Hi Bronwyn,

I know it's been a long time, but my RA recently explored this and we think that mri_aparc2aseg might be a better option that mri_label2vol. Anyway, here's the updated process for mapping the Yeo2011 networks from fsaverage5 to individual volumetric space:

1) Transform from fsaverage to subject's surface
mri_surf2surf --srcsubject fsaverage5 --trgsubject yoursubject --hemi lh --sval-annot path_to/lh.Yeo2011_17Networks_N1000.annot –tval $SUBJECTS_DIR/yoursubject/label/lh.Yeo_17Network_native.annot
(repeat for rh)

2) Transform from subject's surface into your subject's volume
Instead of using "mri_label2vol", we now recommend using "mri_aparc2aseg". This will give you ROIs that fully cover subject's grey matter.

mri_aparc2aseg --s yoursubject --annot Yeo_17Network_native --o $SUBJECTS_DIR/yoursubject/mri/outputfile.mgz

One thing to note: "mri_aparc2aseg" will automatically add 1000 for left cerebral cortex voxels and add 2000 for right cerebral cortex voxels. Therefore, for example, a left hemisphere voxel in network 5 will have a value of 1005 in your outputfile.mgz. Here is our suggestion:
a) Find the indices of left/right cerebral cortex by extracting the voxels with a value of 3 or 42 in the subject's aseg.
b) Use those indices to mask out the voxels that are not cerebral cortex in your outputfile.mgz file (i.e. set non cerebral cortical voxels to be 0).
c) For the cortical voxels, you may subtract 1000 for those between 1000 and 2000; and subtract 2000 for those greater than 2000.

Thanks,
Thomas

On Thu, Jun 23, 2016 at 2:26 PM Bronwyn Overs <b.overs@neura.edu.au> wrote:

Thanks very much Thomas.

Kind regards,

Bronwyn Overs
Research Assistant

Neuroscience Research Australia
Margarete Ainsworth Building
Barker Street Randwick Sydney NSW 2031 Australia
M 0411 308 769 T +61 2 9399 1883

neura.edu.au

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On 23/06/2016 4:20 pm, Thomas Yeo wrote:
You should be able to use the 5.3 version.

Regards,
Thomas

On Thu, Jun 23, 2016 at 2:16 PM, Bronwyn Overs <b.overs@neura.edu.au> wrote:

Hi Thomas,

Thanks for your reply.

The fsaverage directory I have for fs v 5.1 does not include the lh and rh Yeo2011_7Networks_N1000.annot files. I only have this in the 5.3 version of fsaverage. Can I still use the 5.3 version annot files or would I need a seperate set processed with version 5.1?

Kind regards,

Bronwyn Overs
Research Assistant

Neuroscience Research Australia

Neuroscience Research Australia
Margarete Ainsworth Building
Barker Street Randwick Sydney NSW 2031 Australia
M 0411 308 769 T +61 2 9399 1883
On 23/06/2016 3:17 pm, Thomas Yeo wrote:
Hi Bronwyn,

You raise a good point. You can consider creating a cortical mask using aparc+aseg.mgz and use that to mask the networks. 

However, another approach (which might be more accurate) is to take cortical networks in fsaverage space and transform to your subject's surface and then transform into your subject's volume:

# Transform from fsaverage to subject's surface
>> mri_surf2surf --srcsubject fsaverage --trgsubject yoursubject --hemi lh --sval-annot lh.Yeo2011_17Networks_N1000.annot  --tval $SUBJECTS_DIR/yoursubject/label/lh.Yeo_17Network_native.annot

# Transform from subject's surface into your subject's volume (I am not super sure about this. You probably want to double check the output is correct)
>> mri_label2vol --annot lh.Yeo2011_17Networks_N1000.HS_001.annot --o outfile.nii.gz --hemi lh --subject HS_001 --regheader

--Thomas

On Wed, Jun 22, 2016 at 8:25 AM, Bronwyn Overs <b.overs@neura.edu.au> wrote:

Hi Mailing List,

I am attempting to apply the Yeo 2011 7-network fucntional parcellations to a set of fs MRIs processed with v5.1.0. Below are listed the first three steps I plan to take and I am seeking advice as to:

A) Whether this approach is valid.
B) Steps to take next.


Steps 1-3:

1. Run MNI152 1mm template through recon-all
recon-all -i FSL_MNI152_FreeSurferConformed_1mm.nii -subjid Yeo2011_MNI152_FS
recon-all -all -subjid Yeo2011_MNI152_FS

2. Warp the Yeo_atlas1mm.nii.gz to freesurfer nonlinear volumetric space
mri_vol2vol --mov Yeo2011_7Networks_MNI152_FreeSurferConformed1mm_LiberalMask.nii --s Yeo2011_MNI152_FS --targ $FREESURFER_HOME/average/mni305.cor.mgz --m3z talairach.m3z --o Yeo2011_atlas_FSI.nii.gz --nearest

3. warp the Yeo_atlas_freesurfer_internal_space.nii.gz to each subject:
mri_vol2vol --mov $SUBJECTS_DIR/subjID/mri/norm.mgz --s subjID --targ Yeo2011_atlas_FSI.nii.gz --m3z talairach.m3z --o Yeo2011_atlas_subjID.nii.gz --nearest --inv-morph


When previously mapping the Choi 2012 straital parcellations, steps 4 and 5 were: 

4. Creating a striatal mask in the native subject's space from freesurfer segmented Caudate (11 & 50), Putamen (12 & 51), and Accumbens (26 & 58):
mri_binarize --i subjID/mri/aparc+aseg.mgz --match 11 --match 12 --match 26 --match 50 --match 51 --match 58 --o striatum_mask.nii.gz

5. Using this mask to mask the choi striatal parcellations
fslmaths Choi2012_atlas_subjID.nii.gz -mas striatum_mask_subjID.nii.gz Yeo_atlas_subjID_mask.nii.gz


Do I need to do a similar thing for the Yeo cortical parcellations and if so what regions should I include in the cortical mask?

--

Kind regards,

Bronwyn Overs
Research Assistant

Neuroscience Research Australia

Neuroscience Research Australia
Margarete Ainsworth Building
Barker Street Randwick Sydney NSW 2031 Australia
M 0411 308 769 T +61 2 9399 1883


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