Missing parcellation

[bkossows]

I would like to extract averaged myelin values from the aparc and apar2009s parcellation. I've found dscalar.nii files in the repository, but there are no dlabel.nii files for the respective parcellation. I am not sure, but it seems like the individual parcellations are required to run the following command. Am I correct? wb_command -cifti-parcellate xxx.dscalar.nii xxx.aparc.a2009s.32k_fs_LR.dlabel.nii COLUMN output.pscalar.nii

[ericfeczko]

I think there's some epistemological confusion here. Please allow me to clarify:

subject-specific label files are typically annotations that leverage the subject's measured data in order to customize the parcellation scheme -- also known as precision functional mapping this leads to different ROIs and differently shaped systems from subject to subject. Examples can be found here:

https://doi.org/10.1101/2022.01.12.475422

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568802/

https://www.cell.com/neuron/pdf/S0896-6273(17)30613-X.pdf

In general, template label files that are applied consistently across multiple subjects are often derived a priori from independent data averaged across many subjects (not a literal average, of course). These label files are the same for each subject, and enable comparisons of the same ROI across mutliple subject -- at the cost of precision. These aren't actually specifically labeled for each subject, but in some pipelines, may be provided as a convenience.

As long as such label files are properly mapped to the same standard space (for ABCC data, this would be the MNI 2006 Nonlinear asymmetric atlas in volume, and freesurfer L/R 164/32k for the surface), the cifti parcellate command you have above should work just fine.

I'm curious why Rahul Desikan's (זכרונו לברכה) atlas?

We do have a collection of general ROI sets that can be used for this purpose, here's a link to a folder containing them:

https://drive.google.com/drive/folders/1XUNzIGblYroDvqcNb-GAXNRAfGlZGjek?usp=share_link

Finally, I would be cautious about using myelin maps in general and do some EDA on the stability first. Some normalization transforms to the data may be warranted.

[bkossows]

Thank you for the prompt response. I appreciate the atlases you sent me to obtain the relevant statistics. However, I still have reservations about the redundancy of the DK parcellation for the specific participants. When I examined the output of the HCP-ABCD pipeline, I noticed a significant difference between "fsaverage" and the individual parcellation (for fsLR32k). I did not enable MPM registration for my data. Do you think that may have been the cause? I would like to use the ABCD myelin data as a reference for my dataset. Could you please confirm if the file "sub-#/ses-#/anat/sub-#_ses-#_space-fsLR32k_myelinmap.dscalar.nii" corresponds to "#.MyelinMap.32k_fs_LR.dscalar.nii" or the bias-corrected "#.MyelinMap_BC.32k_fs_LR.dscalar.nii" from the HCP ABCD pipeline? With kind regards,

[ericfeczko]

The above link takes me to the NHP version of our pipeline -- we also have human child/adult and human infant . Given the repository, I was under the impression that the child/adult pipeline was being used -- is that correct or am I mistaken?

No worries either way, just want to make sure we're on the same page :)

Ok, I think I understand now -- you wanted to use the freesurfer naive bayes classified parcellations based on Rahul's manually drawn labels. We don't routinely pull these through to the derivatives -- though they are present in the processed output itself (prior to running file-mapper above).

The "fsaverage" will indeed be different from "fsLR32k". The fsaverage refers to freesurfer's fsaverage template as opposed to the freesurfer L/R resampled to 32k vertices.

Yes the correspondence should be the same to the 32k_fs_LR.dscalar.nii -- we have a list of all the correspondences here, if you're interested :)

[bkossows]

Thank you again for the clarification. We used human child/adult. So, you're saying that the pipeline we ran is not the same one used for the NDA ABCD Collection?

[ericfeczko]

the NDA ABCD collection used the human child/adult. If you're running the pipeline yourself, one can pull this in assuming one has not run the customclean stage.

Happy to walk this through in a quick zoom meeting if you'd like -- feel free to contact me at feczk001@umn.edu

[MarcinSzyWy]

Eric, thanks a lot for these clarifications!