No I meant the dot convert.

Matt.

From: Maarten Vaessen <m.vaes...@gmail.com>
Date: Monday, July 20, 2015 at 3:29 AM
To: Matt Glasser <glass...@wusm.wustl.edu>
Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] tractography

The conversion was done like this:

wb_command -gifti-label-to-roi ../../MNINonLinear/fsaverage_LR32k/102816.L.aparc.a2009s.32k_fs_LR.label.gii L.STS.func.gii -name S_temporal_sup
surf2surf  -i ../../MNINonLinear/fsaverage_LR32k/102816.L.white.32k_fs_LR.surf.gii -o L.STS.fsl_MNI_new.asc --outputtype=ASCII  --values=L.STS.func.gii

Is this what you were referring to?

-Maarten

On Sun, Jul 19, 2015 at 10:20 PM, Glasser, Matthew <glass...@wusm.wustl.edu> wrote:
The --onewaycondition flag doesn’t seem sensible with matrix3.  Also I don’t know what your command was for doing the conversion.  Here is the probtrackx2 call that didn’t make it onto the list:

probtrackx2 -x L.STS.fsl_MNI_new.asc --onewaycondition --omatrix3 --target3=L.STS.fsl_MNI_new.asc --lrtarget3=brainmap_HCP/brainmap_filelist.txt -P 100 --forcedir --dir=./test_surf_track_STS_brainmap_seedspace -s ../Diffusion.bedpostX/merged -m nodif_brain_mask.nii.gz --seedref=../../MNINonLinear/T1w_restore.nii.gz -V 2 --opd --pd --distthresh3=2 --xfm=../../MNINonLinear/xfms/standard2acpc_dc.nii.gz --invxfm=../../MNINonLinear/xfms/acpc_dc2standard.nii.gz


Peace,


Matt.


From: Maarten Vaessen <m.vaes...@gmail.com>
Date: Sunday, July 19, 2015 at 12:03 PM
To: Matt Glasser <glass...@wusm.wustl.edu>
Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
Subject: Re: FW: [HCP-Users] tractography

In this case: seed region to whole brain connectivity. The STS seed is mainly for testing purposes (not as many seed points as the whole WM), the final analysis will use all WM voxels as seeds though. In fact,when I run the analysis with WM as the seed the results look equally strange: only connectivity to what appears to be the right inferior posterior cortex. Could this be an issue with the seed-space to dti-space parameters?

-M

On Sun, Jul 19, 2015 at 5:31 PM, Glasser, Matthew <glass...@wusm.wustl.edu> wrote:
What is it that you are trying to achieve?  Usually one uses a seed of all white matter voxels with matrix3.

Peace,

Matt.

From: Maarten Vaessen <m.vaes...@gmail.com>
Date: Sunday, July 19, 2015 at 3:41 AM
To: Matt Glasser <glass...@wusm.wustl.edu>
Subject: Re: [HCP-Users] tractography

Hi Matthew,

I tried to use the file you suggested, and I can convert the .dot without problem. However, the results don't make any sense, so I think there might be something wrong in my processing pipeline. Would you mind having a quick look at it and see if I do something wrong?
Attached is the pipeline and a screenshot from the matrix as loaded in MATLAB.
As you can see from the screenshot, there is only very limited number of none zeros. And weirdest of all, they appear at column indices which are probably somewhere in the right hemisphere (seed is in the left).

Thanks,

-Maarten

On Wed, Jul 15, 2015 at 6:20 PM, Glasser, Matthew <glass...@wusm.wustl.edu> wrote:
You should be able to use this file: 


Peace,

Matt.

From: <hcp-users-boun...@humanconnectome.org> on behalf of Maarten Vaessen <m.vaes...@gmail.com>
Date: Wednesday, July 15, 2015 at 4:44 AM
To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] tractography

Hello, 

I followed the guide lines below to create a dense connectome with probtrackx. I was just wondering how to proceed with converting the .dot file from probtrackx to cifti using wb_command -probtrackx-dot-convert (for visualisation in wb_view). Specifically, what cifti file can I use as input for the -row-cifti option? So, what files released with the HCP data contain the correct brainmap?

Thx

-Maarten 




_______________________________________________________________
Hi

You need to create such a file that contains the 90k grayordinates. To ensure 
consistency we do that in MNI 2mm space:
- First create surface files in an FSL friendly format. Use the 32k surfaces, 
as the vertices are ~2mm apart.
Left Surface:
surf2surf -i 
$Subject/MNINonLinear/fsaverage_LR32k/${Subject}.L.white.32k_fs_LR.surf.gii -o 
white.L.asc --outputtype=ASCII 
--values=$Subject/MNINonLinear/fsaverage_LR32k//${Subject}.L.atlasroi.32k_fs_LR.shape.gii

Right Surface:
surf2surf -i 
$Subject/MNINonLinear/fsaverage_LR32k/${Subject}.R.white.32k_fs_LR.surf.gii -o 
white.R.asc --outputtype=ASCII 
--values=$Subject/MNINonLinear/fsaverage_LR32k//${Subject}.R.atlasroi.32k_fs_LR.shape.gii

- Then extract the volume subcortical files from e.g. 
$Subject/MNINonLinear/ROIs/Atlas_Rois.2.nii.gz, let’s say as 
CIFTI_Structure_{Name}.nii.gz, using e.g. fslmaths or your favourite tool for 
ROI extraction. You should get 19 of these NIFTI files. (You can obviously use 
your favourite subcortical parcellation here, but if you want consistency with 
the CIFTI standard grayordinates, you need to resample the final results, the 
file above ensures consistency).

- Put all the filenames in a text file in the following sequence, to ensure 
consistency with the rest of the CIFTIs:

white.L.asc
white.R.asc
CIFTI_STRUCTURE_ACCUMBENS_LEFT.nii.gz
CIFTI_STRUCTURE_ACCUMBENS_RIGHT.nii.gz
CIFTI_STRUCTURE_AMYGDALA_LEFT.nii.gz
CIFTI_STRUCTURE_AMYGDALA_RIGHT.nii.gz
CIFTI_STRUCTURE_BRAIN_STEM.nii.gz
CIFTI_STRUCTURE_CAUDATE_LEFT.nii.gz
CIFTI_STRUCTURE_CAUDATE_RIGHT.nii.gz
CIFTI_STRUCTURE_CEREBELLUM_LEFT.nii.gz
CIFTI_STRUCTURE_CEREBELLUM_RIGHT.nii.gz
CIFTI_STRUCTURE_DIENCEPHALON_VENTRAL_LEFT.nii.gz
CIFTI_STRUCTURE_DIENCEPHALON_VENTRAL_RIGHT.nii.gz
CIFTI_STRUCTURE_HIPPOCAMPUS_LEFT.nii.gz
CIFTI_STRUCTURE_HIPPOCAMPUS_RIGHT.nii.gz
CIFTI_STRUCTURE_PALLIDUM_LEFT.nii.gz
CIFTI_STRUCTURE_PALLIDUM_RIGHT.nii.gz
CIFTI_STRUCTURE_PUTAMEN_LEFT.nii.gz
CIFTI_STRUCTURE_PUTAMEN_RIGHT.nii.gz
CIFTI_STRUCTURE_THALAMUS_LEFT.nii.gz
CIFTI_STRUCTURE_THALAMUS_RIGHT.nii.gz


- You can then use such a file in FSL probtrackx2 as a seed (for Matrix1) or as 
a target3 (for Matrix3). Notice that running a single probtrackx2 command with 
all these seed locations and with many samples per location will require huge 
processing power and memory. In practice, we run multiple probtrackx2 in 
parallel, by splitting and parallelising the computation by using the --rseed 
option in probtrackx2 and using a small number of samples --nsamples per 
instance. I.e. instead of running one command, which will attempt to propagate 
5000 curves per seed, we can run e.g. 100 instances of the above commands, 
using --nsamples=50 and --rseed=i, i=1..100. Results can then be combined using 
fdt_matrix_merge (which however also needs quite a lot of memory to produce the 
final dense connectomes, but at least it is one final process).

- Another approach for parallelisation would be to split the seed locations and 
merge the final matrices. There is no solution that fits all systems, you 
should try and find the best approach depending on your computing resources.

Hope this helps
Stam





On 19 May 2015, at 01:01, David R. Haynor <hay...@uw.edu<mailto:hay...@uw.edu>> 
wrote:

hi HCP,

we are trying to do tractography using FSL and HCP data.  i have some questions 
-- i suspect they have been answered already, but couldn't find those answers:

1. is there a file containing the grayordinate coordinates in the diffusion 
space for a particular subject, both subcortical voxels and cortical vertices?

2. if i want to use some cortical and subcortical voxels from the list of 
grayordinates as targets, do i have to run probtrackx2 twice (i.e. once for the 
cortical surface vertices and once for the subcortical voxels), or can i run it 
just once?

3. where is the label file for the grayordinate vertices/voxels for a given 
subject?

thanks in advance.

-dh
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