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Hi Stefano, 

You can try the following

1) Transform from fsaverage to subject's surface
mri_surf2surf --srcsubject fsaverage --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
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. 

Thanks,
Thomas

On Fri, Mar 8, 2019 at 7:29 PM <stdp82@virgilio.it> wrote:

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Hi Doug,

my apologies, I have tried to do it with some errors. Could you suggest the command line, please?

Stefano

Il 7 marzo 2019 alle 23.57 "Greve, Douglas N.,Ph.D." <DGREVE@mgh.harvard.edu> ha scritto:

You have to convert the annotation to a volume using mri_aparc2aseg
(look at recon-all.log for an example, but note that you'll need to
specify the output so that it does not overwrite). You'll then need to
look in the output segmentation and see what the segmentation ids are

On 3/7/19 4:13 PM, stdp82@virgilio.it wrote:
>

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Hi list,

I'd like to use the regions included in Yeo 17 networks
(https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Yeo2011_fcMRI_clustering).

in FS-FAST.

Which is the command line to be used to create a segmentation in
$SUBJECTS_DIR/$subject/mri in the same format as aseg.mgz? (I'd like
to use it to run fcseed-config, specify -seg yourseg.mgz -segid).

Thanks

Stefano

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