Hi Donna, Many thanks for your thorough reply. I can see that I wasn’t very clear on explaining what we are trying to achieve – I’ll try to clarify things a little :-)
What we have done so far: Generated Conn3.dconn.nii files: 92K x 92K structural connectivity matrices from the DWI data in FSL’s matrix3 format (WM seeds, cortical surface & subcortical voxels as targets). This provides us with connectivity matrices whose nodes are (to the limit of the HCP registration pipeline) anatomically matched across subjects. What we are analyzing: Machine-learning parcellation of these connectivity matrices. What we would like to do: Compare our machine-learning parcellations with previously published / commonly-used ones. For this we would like to be able to obtain, for each atlas, a label per node of the connectivity matrices. For some atlases, e.g. Desikan-Killiany, I realise that these labels:node mappings will vary per subject as the atlas is adapted according to the individual’s gyrification patterns. For other atlases though, e.g. the Gordon 2014 atlas, the label:node mapping is fixed. It would also be great if we could compare against some MNI-based parcellation schemes, such as the Harvard-Oxford. (Other suggestions welcome!) So to my questions! :-) 1) What is the best way to get the per-subject label:node mapping from the existing *.dlabel.nii and *.label.gii files? I was thinking of using something like: wb_command -file–information 100307/MNINonLinear/fsaverage_LR32k/100307.aparc.a2009s.32k_fs_LR.dlabel.nii which gives me (with a bit of filtering) a parcel:label mapping. Then using: wb_command -nifti-information -print-matrix 100307/MNINonLinear/fsaverage_LR32k/100307.aparc.a2009s.32k_fs_LR.dlabel.nii to give me a vertex:parcel mapping. Then I need to stitch the two together somehow. Are these steps correct? Is there a better (easier) way? 2) Would I use the same method for the Gordon atlas (which I understand is provided on the standard 32K mesh)? 3) How would I do this for, e.g. the Harvard-Oxford atlas? Should I map the voxelwise parcels onto the 32K mesh first and then use the same method as for (2)? I’m still a surface-space novice, but I hope this is a bit clearer now :-) Many thanks for any help/advice! Cheers, M@ On 13/11/15 20:25 , "Donna Dierker" <[email protected]<mailto:[email protected]>> wrote: Hi Matthew, The aparc files Jenn meant are generated by Freesurfer, but we make them available in cifti (*dlabel.nii) and gifti (*.label.gii) formats: * 164k standard mesh Structural_preproc/MNINonLinear/994273.aparc.164k_fs_LR.dlabel.nii Structural_preproc/MNINonLinear/994273.aparc.a2009s.164k_fs_LR.dlabel.nii Structural_preproc/MNINonLinear/994273.L.aparc.164k_fs_LR.label.gii Structural_preproc/MNINonLinear/994273.L.aparc.a2009s.164k_fs_LR.label.gii Structural_preproc/MNINonLinear/994273.R.aparc.164k_fs_LR.label.gii Structural_preproc/MNINonLinear/994273.R.aparc.a2009s.164k_fs_LR.label.gii * 32k standard mesh Structural_preproc/MNINonLinear/fsaverage_LR32k/994273.aparc.32k_fs_LR.dlabel.nii Structural_preproc/MNINonLinear/fsaverage_LR32k/994273.aparc.a2009s.32k_fs_LR.dlabel.nii Structural_preproc/MNINonLinear/fsaverage_LR32k/994273.L.aparc.32k_fs_LR.label.gii Structural_preproc/MNINonLinear/fsaverage_LR32k/994273.L.aparc.a2009s.32k_fs_LR.label.gii Structural_preproc/MNINonLinear/fsaverage_LR32k/994273.R.aparc.32k_fs_LR.label.gii Structural_preproc/MNINonLinear/fsaverage_LR32k/994273.R.aparc.a2009s.32k_fs_LR.label.gii * native mesh Structural_preproc/MNINonLinear/Native/994273.aparc.a2009s.native.dlabel.nii Structural_preproc/MNINonLinear/Native/994273.aparc.native.dlabel.nii Structural_preproc/MNINonLinear/Native/994273.L.aparc.a2009s.native.label.gii Structural_preproc/MNINonLinear/Native/994273.L.aparc.native.label.gii Structural_preproc/MNINonLinear/Native/994273.R.aparc.a2009s.native.label.gii Structural_preproc/MNINonLinear/Native/994273.R.aparc.native.label.gii If you get the structural extended packages, you can get the original Freesurfer subject directory (e.g. Structural_preproc/T1w/994273). Note these include not only the Desikan-Killiany (aparc), but also the Destrieux (aparc.a2009s): https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation The only relation these have to the Conte69 is that they are both available in the 164k and 32k standard meshes. These are very nice parcellations Freesurfer provides in normal processing; we just make them available on different meshes/formats for the HCP subjects. I assume you are interested in anatomical parcellations only, and not functional (e.g., https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation_Yeo2011). I think you will see improved parcellations coming out soon, so stay tuned. I am not a diffusion expert, so I don't have a good feel for what you are trying to do, though it may involve identifying where tracts terminate and seeing how often varying parcellations agree using the same tracts (???). Donna On Nov 13, 2015, at 8:35 AM, Matthew George Liptrot <[email protected]<mailto:[email protected]>> wrote: Hiya, We would like to compare several parcellation schemes with the results of structural connectivity on the HCP data (we have generated dense connectome data for several subjects). The Freesurfer parcellation (which is based upon the Conte69 atlas?) is already provided on the 32K subject mesh, but we would like to compare others, e.g. Desikan-Killiany, Harvard-Oxford, microstructure etc. In short: 1) What would be the optimal way to do this? 2) Which wb_commands should we use? 3) Which atlases would people recommend (we want to look at replication performance across subjects) 4) There seems to only be a small subset of Brodmann areas in the distributed subjects’ 32K CIFTI files (mainly the visual cortex and areas around pre- and post-central gyrus). Any reason why the rest are missing? Thanks in advance for any pointers! Cheers, M@ On 4/11/15 23:17 , "Jennifer Elam" <[email protected]<mailto:[email protected]>> wrote: Hi Vishal, Also, the FreeSurfer-generated aparc and aparc.a2009s non-overlapping parcellations for each subject are available on the 32k_fs_LR mesh and 164k mesh in the Structural preprocessed package for each subject. These are available as GIFTI label files per hemisphere and as CIFTI dlabel files (both hemispheres). Best, Jenn Jennifer Elam, Ph.D. Outreach Coordinator, Human Connectome Project Washington University School of Medicine Department of Anatomy and Neurobiology, Box 8108 660 South Euclid Avenue St. Louis, MO 63110 314-362-9387 [email protected]<mailto:[email protected]> www.humanconnectome.org From: [email protected]<mailto:[email protected]> [mailto:[email protected]] On Behalf Of Harms, Michael Sent: Wednesday, November 04, 2015 3:40 PM To: Vishal Patel; [email protected]<mailto:[email protected]> Subject: Re: [HCP-Users] Hcp Data with non-overlapping parcellations Hi Vishal, There is a version of the hard parcellation from Gordon et al. (Cerebral Cortex, 2014) available as a CIFTI 'dlabel.nii' file, if you are interested in that. cheers, -MH -- Michael Harms, Ph.D. ----------------------------------------------------------- Conte Center for the Neuroscience of Mental Disorders Washington University School of Medicine Department of Psychiatry, Box 8134 660 South Euclid Ave. Tel: 314-747-6173 St. Louis, MO 63110 Email: [email protected]<mailto:[email protected]> From: Vishal Patel <[email protected]<mailto:[email protected]>> Date: Wednesday, November 4, 2015 1:42 PM To: "[email protected]<mailto:[email protected]>" <[email protected]<mailto:[email protected]>> Subject: [HCP-Users] Hcp Data with non-overlapping parcellations Hi, Does anyone have access to HCP data that has been parcellated in non-overlapping regions or can point me in the right direction? Thanks, Vishal -- Vishal Patel Graduate Student Applied Cognition & Neuroscience University of Texas at Dallas In the depths of winter, I finally learned that within me there lay an invincible summer. -Albert Camus- _______________________________________________ HCP-Users mailing list [email protected]<mailto:[email protected]> http://lists.humanconnectome.org/mailman/listinfo/hcp-users The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ HCP-Users mailing list [email protected]<mailto:[email protected]> http://lists.humanconnectome.org/mailman/listinfo/hcp-users _______________________________________________ HCP-Users mailing list [email protected]<mailto:[email protected]> http://lists.humanconnectome.org/mailman/listinfo/hcp-users -- Matthew George Liptrot Department of Computer Science University of Copenhagen & Section for Cognitive Systems Department of Applied Mathematics and Computer Science Technical University of Denmark http://about.me/matthewliptrot _______________________________________________ HCP-Users mailing list [email protected]<mailto:[email protected]> http://lists.humanconnectome.org/mailman/listinfo/hcp-users -- Matthew George Liptrot <http://about.me/matthewliptrot> Department of Computer Science University of Copenhagen & Section for Cognitive Systems Department of Applied Mathematics and Computer Science Technical University of Denmark http://about.me/matthewliptrot <http://about.me/matthewliptrot> _______________________________________________ HCP-Users mailing list [email protected] http://lists.humanconnectome.org/mailman/listinfo/hcp-users
