Structural Connectomes from HCP Preprocessed Data

I’d like to make a Singularity container for generating structural connectomes from data that have already been preprocessed through HCP pipelines. I see that the ISMRM tutorial from 2015 is outdated. Is there any new documentation available that provides guidance/best practices for working with HCP preprocessed data in MRtrix3?

Dear @droediger,

It’s not “official” or anything like that, but at https://github.com/civier/HCP-dMRI-connectome you will be able to find the scripts I used for my recent NI paper:
Civier, O., Smith, R. E., Yeh, C. H., Connelly, A., & Calamante, F. (2019). Is removal of weak connections necessary for graph-theoretical analysis of dense weighted structural connectomes from diffusion MRI? NeuroImage, 194, 68-81
http://doi.org/10.1016/j.neuroimage.2019.02.039
The scripts include everything up to the construction of the tractogram, but you are welcome to contact me for the commands for running SIFT2 and generating the actual connectome.

The resulting connectivity matrices are available as well at https://osf.io/n6b5p/ if you want to verify that your analysis makes sense (please do let me know if you get a large discrepancy).

Just two quick requests:

  1. If you take from my scripts, could you cite my paper in the documentation of the container?
  2. Could you share your container with the community? (I’d be happy to help you test it in our facilities at Swinburne Imaging in Melbourne: https://www.swinburne.edu.au/neuroimaging)

All the best,
Oren