preprocess steps for HCP-style DWI data

dear developers:
hello~I met a question about preprocess steps for HCP-styple DWI data. my DWI data is acquired as the HCP-style(Opposite phase encoding direction is left-right, right-left, single shell(b = [0,1000], number of gradient directions = 90), , 1.8 mm isotropic voxels). However, I find the recommend Diffusion Preprocess [HCP miniprocessing pipeline ]has different steps from FBA diffusion preprocee. the former pipeline include B0 intensity normalization, EPI distortation correction via “topup”, eddy current and head movement correction via “eddy”, gradient nonlinearity corretion, and transform between the native diffusion space and the native structural space.[Glasser et al. 2013 Neuroimage. The Minimal Preprocessing Pipelines for the Human Connectome Project]. I wonder if I want to conduct FBA analysis based on my HCP-style data, which diffusion preprocess steps should I retain?
sincerely appreciate for any helps!

Hi Suming,

It is fine to do FBA analysis on data that has been preprocessed with the HCP pipeline.

We typically recommend denoising your data as the first step, but if you’d rather not, it is not necessary. In fact, FBA was developed before MP-PCA denoising was introduced.

Gradient nonlinearity correction is the one step we do not currently support in MRtrix, and can therefore not be combined with FBA.