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Thank you, the ciftify was run successfully! But now I have questions to the wb-command -cifti-parcellate:
wb_command -cifti-parcellate
      <cifti-in> - the cifti file to parcellate
      <cifti-label> - a cifti label file to use for the parcellation
      <direction> - which mapping to parcellate (integer, ROW, or COLUMN)
      <cifti-out> - output - output cifti file
I understand that  <cifti-in> should be ${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.thickness.32k_fs_LR.dscalar.nii, but what should I use as label? The Q1-Q6_RelatedParcellation210.L.CorticalAreas_dil_Colors.32k_fs_LR.dlabel.nii from https://balsa.wustl.edu/WN56? And the output from the -cifty-parcellate is .pscalar.nii..how do I get from there to GIFTI?

And for the GIFTY to .annot I would do:

  mris_convert --annot lh.aparc.gii lh.white.gii lh.aparc.annot (Freesurfer example)

Thank you,

Alina

Am 14.07.2020 um 16:17 schrieb Glasser, Matthew <glasserm@wustl.edu>:

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I would find using something like ciftify (https://github.com/edickie/ciftify) potentially more straightforward (and then you can just use wb_command -cifti-parcellate on ${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.thickness.32k_fs_LR.dscalar.nii).  It is possible to go the other direction too (e.g. using this link: https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjC2IL-9szqAhWPW80KHb3gAtQQFjACegQIBhAB&url=https%3A%2F%2Fwiki.humanconnectome.org%2Fdownload%2Fattachments%2F63078513%2FResampling-FreeSurfer-HCP_5_8.pdf&usg=AOvVaw0PXEiAKfGjdiN2DJcF7nuI and then perhaps someone on the list can explain how to go from GIFTI on fsaverage to .annot on the native meshes and extract the stats.

Matt.

On 7/14/20, 8:54 AM, "freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Alina Rojas" <freesurfer-bounces@nmr.mgh.harvard.edu on behalf of alinacolora@gmail.com> wrote:

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   Hello Freesurfer support list,

   I’m attempting to map the HCP-MMP1-Atlas to the individual brains of my subjects to get the values of the parcellation, like aparc.stats but aparc being HCP-MMP1. The aim ist to compare the cortical thickness of the Parcellation given by the HCP-MMP1-Atlas between subjects. I searched the archive and didn’t find the solution. It would be so great if you could help me!

   Thank you and regards,

   Alina Rojas

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