Hi The HCP course tractography practical would be a good way to start (see page 386 onwards):
https://wustl.app.box.com/s/wna2cu94pqgt8zskg687mj8zlmfj1pq7 Briefly, if you have a number of surfaces (need to convert them to ASCII using surf2surf) and subcortical volumes you can merge them into text files and use those as seeds. This will get you a dense connectome which you can then parcellate using any parcellation scheme you would like. Best wishes Stam On 30 Oct 2018, at 23:35, Glasser, Matthew <glass...@wustl.edu<mailto:glass...@wustl.edu>> wrote: Also use the label ones to make GIFTI label files. Matt. From: Leonardo Tozzi <lto...@stanford.edu<mailto:lto...@stanford.edu>> Date: Tuesday, October 30, 2018 at 6:34 PM To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>> Subject: Re: [HCP-Users] Diffusion connectivity matrix with cortical and subcortical parcellation Dear Matthew, Thank you for the very quick response. So for clarification, you would use the following command: wb_command -cifti-separate merged.dlabel.nii COLUMN -volume-all subcort.nii.gz To obtain the subcortical volumes. What about the cortical ones? Is the file Q1-Q6_RelatedValidation210.CorticalAreas_dil_Final_Final_Areas_Group_Colors.32k_fs_LR.dlabel.nii already usable as input to FSL? I thought I would need a .gii file. Or do I need to use the option in wb_command -cifti-separate: [-label] - repeatable - separate a surface model into a surface label file. In this case, what would be the argument for “<structure> - the structure to output” ? Thank you very much, Leonardo Tozzi, MD, PhD Williams PanLab | Postdoctoral Fellow Stanford University | 401 Quarry Rd lto...@stanford.edu<mailto:lto...@stanford.edu> | (650) 5615738 From: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>> Date: Tuesday, October 30, 2018 at 4:22 PM To: Leonardo Tozzi <lto...@stanford.edu<mailto:lto...@stanford.edu>>, "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: Re: [HCP-Users] Diffusion connectivity matrix with cortical and subcortical parcellation I would separate the CIFTI file into GIFTI and NIFTI components with wb_command -cifti-separate and follow the instructions for surface tracking on FSL’s website. Matt. From: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Leonardo Tozzi <lto...@stanford.edu<mailto:lto...@stanford.edu>> Date: Tuesday, October 30, 2018 at 6:19 PM To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: [HCP-Users] Diffusion connectivity matrix with cortical and subcortical parcellation To Whom it may concern, I have created a dlabel file by adding to the Glasser Parcellation from BALSA the subcortical regions of the Freesurfer atlas. Now my goal would be to run a tractography analysis and obtain structural connectivity matrices using this cortical+subcortical parcellation. Could you suggest the simplest way to go from my dlabel file to something that is compatible with diffusion software? I know that probtrackx accepts GIFTIs as input, but I was wondering about how to extend this to subcortical areas. Or rather would the simplest solution be to convert each subject’s parcellation into a series of NIFTI files in native/standard space and input these as ROIs into probtrackx? In this case, could you recommend the correct series of workbench commands? I am also open to other software recommendations besides the FSL suite. Thank you very much, Leonardo Tozzi, MD, PhD Williams PanLab | Postdoctoral Fellow Stanford University | 401 Quarry Rd lto...@stanford.edu<mailto:lto...@stanford.edu> | (650) 5615738 _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> 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. 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