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 <[email protected]>
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 <[email protected]>
> Date: Sunday, July 19, 2015 at 3:41 AM
> To: Matt Glasser <[email protected]>
> 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 <[email protected]
> > wrote:
>
>>  You should be able to use this file:
>>
>>
>> https://github.com/Washington-University/Pipelines/blob/master/global/templates/91282_Greyordinates/91282_Greyordinates.dscalar.nii
>>
>>  Peace,
>>
>>  Matt.
>>
>>   From: <[email protected]> on behalf of Maarten
>> Vaessen <[email protected]>
>> Date: Wednesday, July 15, 2015 at 4:44 AM
>> To: "[email protected]" <[email protected]>
>> 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 
>> <[email protected]<mailto:[email protected] <[email protected]>>>
>> 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
>> _______________________________________________
>> HCP-Users mailing 
>> [email protected]<mailto:[email protected] 
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