HCP tractography | tract statistics | MNI space

Dear all,

I am trying to compute statistics on tracts generated from the HCP data-set. I am still planning my protocol but the plan is to track in native space (the space that the HCP diffusion data is in). I then want to compute some statistics for the tracts generated from each seed region. The problem is that since the individual brains are of different volumes, I would ideally need to do some normalization before computing any statistics.

Probably the best way would be to warp the tracts generated in native space to MNI space then compute the statistics. Is there a standard or recommended way of doing this with the HCP data?


I am replying to my own question because I found a response that, I think, answers this question:

While the linked post explains how to perform the streamline warping, it doesn’t fully answer the question. The answer depends on details that were omitted from your original post, specifically the “then compute the statistics” part. I would refer you to this question from another thread, bearing in mind that the answer may be different to that reported in the prior thread if your experiment.

Thanks @rsmith, I am not looking to generate a connectome in MNI space, however, the link is a very useful one should anyone be looking for that.