Hi Matthew,

I was able to replicate what you are seeing.  The label.gii is encoding the 
medial wall as -1, while the dlabel.nii is encoding it as 0.  The more 
substantive differences are due to the fact that the dlabel.nii has a more 
generous medial wall than the label.gii files do:

http://brainmap.wustl.edu/pub/donna/WUSTL/HCP/Misc/
login pub
password download

I would not have expected this.  I vote for the dlabel.nii route.

Donna


On Nov 19, 2015, at 3:13 AM, Matthew George Liptrot <matthew.lipt...@di.ku.dk> 
wrote:

> Hi again,
> 
> The -file–information on the files generated with method (A) and (B) below 
> give the same key value for “???”:
> 
> # (A) (Changed output of first line to include *.label.*, otherwise the 
> -file–information command does not recognise the file format correctly.)
> > wb_command -cifti-separate 100307.aparc.32k_fs_LR.dlabel.nii COLUMN -label 
> > CORTEX_LEFT aparc32k_fs_LR_dlabel_Separated_CortexLeft.label.gii
> > wb_command -gifti-convert ASCII 
> > aparc32k_fs_LR_dlabel_Separated_CortexLeft.label.gii 
> > aparc32k_fs_LR_dlabel_Separated_GiftiConvert_CortexLeft.txt
> > cp aparc32k_fs_LR_dlabel_Separated_GiftiConvert_CortexLeft.txt 
> > aparc32k_fs_LR_dlabel_Separated_GiftiConvert_CortexLeft_LabelsOnly.txt
> # Strip away all header/footer XML codes from 
> aparc32k_fs_LR_dlabel_Separated_GiftiConvert_CortexLeft_LabelsOnly.txt using 
> emacs
> > wc -l aparc32k_fs_LR_dlabel_Separated_GiftiConvert_CortexLeft_LabelsOnly.txt
> 32492
> 
> # (B)
> > wb_command -gifti-convert ASCII 100307.L.aparc.32k_fs_LR.label.gii 
> > L_aparc32k_fs_LR_label_GiftiConvert_CortexLeft.txt
> > cp L_aparc32k_fs_LR_label_GiftiConvert_CortexLeft.txt 
> > L_aparc32k_fs_LR_label_GiftiConvert_CortexLeft_LabelsOnly.txt
> # Strip away all header/footer XML codes from 
> L_aparc32k_fs_LR_label_GiftiConvert_CortexLeft_LabelsOnly.txt using emacs
> > wc -l L_aparc32k_fs_LR_label_GiftiConvert_CortexLeft_LabelsOnly.txt
> 32492
> 
> # (A)
> > wb_command -file-information 
> > aparc32k_fs_LR_dlabel_Separated_CortexLeft.label.gii
> Name:                   aparc32k_fs_LR_dlabel_Separated_CortexLeft.label.gii
> Type:                   Label
> Structure:              CortexLeft 
> Data Size:              129.97 Kilobytes
> Maps to Surface:        true
> Maps to Volume:         false
> Maps with LabelTable:   true
> Maps with Palette:      false
> Number of Maps:         1
> Number of Vertices:     32492
> 
> Map   Map Name       
>   1   100307_aparc   
> 
> Label table for ALL maps
>        KEY   NAME                           RED   GREEN    BLUE   ALPHA   
>          0   ???                          0.000   0.000   0.000   0.000   
>          1   L_bankssts                   0.098   0.392   0.157   1.000   
>          2   L_caudalanteriorcingulate    0.490   0.392   0.627   1.000   
>          3   L_caudalmiddlefrontal        0.392   0.098   0.000   1.000   
>          4   L_corpuscallosum             0.471   0.275   0.196   1.000   
>          5   L_cuneus                     0.863   0.078   0.392   1.000   
> ...
> 
> 
> # (B)
> > wb_command -file-information 100307.L.aparc.32k_fs_LR.label.gii
> Name:                   100307.L.aparc.32k_fs_LR.label.gii
> Type:                   Label
> Structure:              CortexLeft 
> Data Size:              129.97 Kilobytes
> Maps to Surface:        true
> Maps to Volume:         false
> Maps with LabelTable:   true
> Maps with Palette:      false
> Number of Maps:         1
> Number of Vertices:     32492
> 
> Map   Map Name         
>   1   100307_L_aparc   
> 
> Label table for ALL maps
>        KEY   NAME                           RED   GREEN    BLUE   ALPHA   
>          0   ???                          0.000   0.000   0.000   0.000   
>          1   L_bankssts                   0.098   0.392   0.157   1.000   
>          2   L_caudalanteriorcingulate    0.490   0.392   0.627   1.000   
>          3   L_caudalmiddlefrontal        0.392   0.098   0.000   1.000   
>          4   L_corpuscallosum             0.471   0.275   0.196   1.000   
>          5   L_cuneus                     0.863   0.078   0.392   1.000   
> ...
> 
> However, what I’m more concerned about is not so much the labels for Key=0, 
> but that some of the other vertices have different labels – see lines 22-27 
> below:
> 
>  A   B 
> 10  10  
> 29  29  
> 24  24   
> 28  28   
> 11  11   
> 31  31  
> 27  27   
>  0  -1  
> 13  13   
> 15  15   
> 35  35   
> 35  35   
> 10  10   
> 10  10   
> 10  10   
> 10  10   
> 10  10   
> 10  10   
> 10  10   
> 10  10   
> 10  10   
>  0  10   
>  0  10   
>  0  10   
>  0  10   
>  0  10   
>  0  10   
>  0  -1   
>  0  -1   
>  0  -1   
>  0  -1  
>  0  -1   
>  0  -1   
>  0  -1   
>  0  -1   
> …
> 
> This is just the first few lines, and there are many more differences 
> throughout the files. Is this simply a vertex-ordering issue, or is there a 
> conversion error?
> (Key 10 is “L_isthmuscingulate” in both).
> 
> Cheers,
> 
> M@
> 
> 
> On 18/11/15 22:14 , "Timothy Coalson" <tsc...@mst.edu> wrote:
> 
> Sorry, the -*-label-export-table commands don't put the unlabeled key in the 
> text file.  Use -file-information on them instead to check what key value the 
> "???" label is (it means the unlabled value).
> 
> Tim
> 
> 
> On Wed, Nov 18, 2015 at 12:54 PM, Timothy Coalson <tsc...@mst.edu> wrote:
> Inline replies.
> 
> On Wed, Nov 18, 2015 at 8:47 AM, Matthew George Liptrot 
> <matthew.lipt...@di.ku.dk> wrote:
> Hi,
> 
> Thanks both of you. 
> 
> On 17/11/15 21:32 , "Timothy Coalson" <tsc...@mst.edu> wrote:
> So, cifti is not a 1:1 mapping to surface vertices.  If what you plan to use 
> can read gifti, the less error-prone route is probably to use -cifti-separate 
> to get a nifti volume and gifti files that do have a 1:1 mapping to vertices.
> 
> @Tim: By “not a 1:1 mapping to surface vertices”, do you mean:
>       • The CIFTI data-value:vertex mapping is not necessarily bijective 
> (unique)? 
>       • The CIFTI data-value:vertex mapping is not necessarily complete (some 
> vertices may not be represented)?
>       • A combination of 1 & 2?
> I hope it’s (2), because otherwise I’m confused (again!).
> 
> Just (2), yes.  Technically this also means it is not bijective, but the 
> mapping of cifti index to vertex/voxel is injective (no two cifti indices 
> represent the same vertex or voxel).
>  
> A follow-on question is then why would it be less error-prone to use 
> -cifti–separate (as opposed to e.g. -cifti-export-dense-mapping)? 
> I can see that using -cifti-export-dense-mapping on the Conn3.dconn.nii file 
> lists a non-contiguous mapping of node-IDs:Vertex-Ids, presumably due to the 
> omission of the vertices on medial wall that are covered by the subcortical 
> ROIs, i.e.
> 
> I called it less error-prone because it applies the cifti->vertex/voxel 
> mapping for you, rather than making you figure out how to do it.
>  
> CortexLeft, Total entries: 29696 (Node IDs:  0-29695,  Vertice IDs: 0-32491)
> CortexRight, Total entries: 29716 (Node IDs: 29696-59411, Vertice IDs: 
> 0-32491)
> SubCortical, Total entries: 31870 (Node IDs: 59412-91281)
> 
> Is this what you were referring to?
> 
> Yes.
>  
> I then tried using some of your suggestions to extract the labels from the 
> aparc32k atlas in 100307/MNINonLinear/fsaverage_LR32k.
> I tried the following 3 workflows:
> 
> (A)
> > wb_command -cifti-separate 100307.aparc.32k_fs_LR.dlabel.nii COLUMN -label 
> > CORTEX_LEFT aparc32k_fs_LR_dlabel_Separated_CortexLeft.gii
> > wb_command -gifti-convert ASCII 
> > aparc32k_fs_LR_dlabel_Separated_CortexLeft.gii 
> > aparc32k_fs_LR_dlabel_Separated_GiftiConvert_CortexLeft.txt
> > cp aparc32k_fs_LR_dlabel_Separated_GiftiConvert_CortexLeft.txt 
> > aparc32k_fs_LR_dlabel_Separated_GiftiConvert_CortexLeft_LabelsOnly.txt
> # Strip away all header/footer XML codes from 
> aparc32k_fs_LR_dlabel_Separated_GiftiConvert_CortexLeft_LabelsOnly.txt using 
> emacs
> > wc -l aparc32k_fs_LR_dlabel_Separated_GiftiConvert_CortexLeft_LabelsOnly.txt
> 32492
> 
> (B)
> > wb_command -gifti-convert ASCII 100307.L.aparc.32k_fs_LR.label.gii 
> > L_aparc32k_fs_LR_label_GiftiConvert_CortexLeft.txt
> > cp L_aparc32k_fs_LR_label_GiftiConvert_CortexLeft.txt 
> > L_aparc32k_fs_LR_label_GiftiConvert_CortexLeft_LabelsOnly.txt
> # Strip away all header/footer XML codes from 
> L_aparc32k_fs_LR_label_GiftiConvert_CortexLeft_LabelsOnly.txt using emacs
> > wc -l L_aparc32k_fs_LR_label_GiftiConvert_CortexLeft_LabelsOnly.txt
> 32492
> 
> (C)
> > wb_command -cifti-convert -to-text 100307.aparc.32k_fs_LR.dlabel.nii 
> > aparc32k_fs_LR_dlabel_ConvertedToText_NodeID_LabelOnly_CortexAll.txt
> > wc -l aparc32k_fs_LR_dlabel_ConvertedToText_NodeID_LabelOnly_CortexAll.txt
> 59412
> 
> As you can see, they all gave the expected number of outputs (the latter one 
> with the medial wall vertices already removed)
> 
> (C) is obviously not going to match index for index, and the formatting of 
> the below list got messed up, but...
>  
> However, when I look at the first few labels, there are some differences 
> between set (A) and (B):
>  A     B      C
> 10 1010
> 29 2929
> 24 2424
> 28 2828
> 11 1111
> 31 3131
> 27 2727
> 0 -1
> 
> I don't know why -1 is here, that is very unusual for a gifti label file.  It 
> looks like it is used as the unlabeled key, unlike the cifti version that 
> uses 0 - try -cifti-label-export-table and -label-export-table on the two 
> files and see if something shows up for -1, like the "???" key.
> 
> 13 
> 13 1315
> 15 1535
> 35 3535
> 35 3510
> 10 1010
> 10 1010
> 10 1010
> 10 1010
> 10 1010
> 10 1010
> 10 1010
> 10 1010
> 10 1010
> 0 1010
> 0 1010
> 0 1010
> 0 1010
> 0 1010
> 0 1010
> 0 -110
> 0 -110
> 0 -110
> 0 -110
> 0 -110
> 0 -110
> 0 -110
> 0 -110
> 
> Shouldn’t these two give the same? Or maybe this is the errors you were 
> referring to?
> 
> Thanks in advance,
> 
> M@
> 
> 
> Otherwise, have a look at -cifti-label-export-table, -cifti-convert -to-text 
> (other options exist here for nifti-1 and gifti), and 
> -cifti-export-dense-mapping in order to get text files that can get you to 
> the vertex mapping.
> 
> Tim
> 
> 
> On Tue, Nov 17, 2015 at 11:25 AM, <do...@brainvis.wustl.edu> wrote:
> Try this:
> 
> wb_command -gifti-convert ASCII my.label.gii ascii.label.gii
> 
> If needed, strip everything up to <Data>, and then the label values are
> listed in vertex sequence.
> 
> Will need to think about the HOA question.  Hmmm.
> 
> Donna
> 
> > 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"
> > <do...@brainvis.wustl.edu<mailto:do...@brainvis.wustl.edu>> 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
> > <matthew.lipt...@di.ku.dk<mailto:matthew.lipt...@di.ku.dk>> 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"
> > <el...@pcg.wustl.edu<mailto:el...@pcg.wustl.edu>> 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
> > el...@pcg.wustl.edu<mailto:el...@pcg.wustl.edu>
> > www.humanconnectome.org
> >
> > From:
> > hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>
> > [mailto:hcp-users-boun...@humanconnectome.org] On Behalf Of Harms,
> > Michael
> > Sent: Wednesday, November 04, 2015 3:40 PM
> > To: Vishal Patel;
> > hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>
> > 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: mha...@wustl.edu<mailto:mha...@wustl.edu>
> >
> > From: Vishal Patel <vpatel1...@gmail.com<mailto:vpatel1...@gmail.com>>
> > Date: Wednesday, November 4, 2015 1:42 PM
> > To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>"
> > <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
> > 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
> 
> -- 
> 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
> 
> 
> 
> -- 
> 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
> 


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