I would denoise the CIFTI data first. I'll admit I'm not sure I understand your initial question if you already have CIFTI data, you should be able to use wb_command -cifti-parcellate on it. Is your data "HCP Style"?
http://www.nature.com/neuro/journal/v19/n9/abs/nn.4361.html Peace, Matt. From: <[email protected]<mailto:[email protected]>> on behalf of Timothy Coalson <[email protected]<mailto:[email protected]>> Date: Monday, November 14, 2016 at 5:10 PM To: Guy Hwang <[email protected]<mailto:[email protected]>> Cc: "[email protected]<mailto:[email protected]>" <[email protected]<mailto:[email protected]>> Subject: Re: [HCP-Users] Question about -cifti-create-dense-timeseries That is a more difficult question. If the denoising you are adding doesn't need spatial information, and is being applied after FIX, etc, one possibility that might be less painful is to take the existing CIFTI data and run the denoising on that (using -cifti-convert if you need it in a different file format strictly for IO purposes). Otherwise, you may need to mess with the arguments to the pipeline scripts in order to patch in your volumes at the right location. Tim On Mon, Nov 14, 2016 at 4:17 PM, Guy Hwang <[email protected]<mailto:[email protected]>> wrote: Hi Tim, Thank you so much for the prompt reply. So actually I have both volume preprocessed and surface preprocessed data using HCP v3.4.0 scripts. I took the resting images from the volume preprocessed dataset because I wanted to apply some denoising, regressing first before pushing them through cifti-parcellate. Would you rather recommend I take the surface preprocessed data and apply denoising there? Thank you, Guy ________________________________ From: Timothy Coalson <[email protected]<mailto:[email protected]>> Sent: Monday, November 14, 2016 3:47:42 PM To: Guy Hwang Cc: [email protected]<mailto:[email protected]> Subject: Re: [HCP-Users] Question about -cifti-create-dense-timeseries To use the resulting dtseries.nii file with HCP data, you will first need to map the cortical data to surfaces. The various -cifti-create commands do not do this mapping, they are simply data conversion. You also need to nonlinear register to MNI (for subcortical signal). The <label-volume> is specifically to define the structures to represent as voxels in the resulting dtseries file, which is why it says this about <label-volume> lower in the help: The label volume should have some of the label names from this list, all other label names will be ignored: CORTEX_LEFT CORTEX_RIGHT CEREBELLUM ACCUMBENS_LEFT ACCUMBENS_RIGHT ... While that shows that it is possible to represent cortex as voxels in the cifti format, note that it is not recommended, and that it is not what HCP cifti files do (so you will have a very hard time using the HCP parcellation unless you map your subject timeseries data to the surface). The label volume for subcortical signal we use for HCP data exists in the pipelines repository, the Atlas_ROIs.2.nii.gz file here: https://github.com/Washington-University/Pipelines/tree/master/global/templates/91282_Greyordinates The full process we use is fairly involved, and the HCP Pipelines (https://github.com/Washington-University/Pipelines) are the easiest way to do it, when you have data matching our acquisition recommendations. Even if your acquisitions don't entirely meet our recommendations, many of the pipeline scripts can still be used to make the process easier. Tim On Mon, Nov 14, 2016 at 3:11 PM, Guy Hwang <[email protected]<mailto:[email protected]>> wrote: Hello, I am trying to turn nifti files into dtseries.nii so that I can later use -cifti-parcellate to create resting state connectivity matrices. 1) What is <label-volume>? As in the syntax "wb_command -cifti-create-dense-timeseries {output}.dtseries.nii -volume {input}.nii.gz <label-volume>" 2) Where can I find the most up-to-date dtseries.nii file from HCP to use for the parcellation? I would appreciate your help. Thank you, Guy _______________________________________________ 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 ________________________________ 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] http://lists.humanconnectome.org/mailman/listinfo/hcp-users
