To do this I think I can reduce the fixel maps to voxel maps by taking the mean of each fixel and then calculate the correlation with height at each voxel
If you had to project things to the voxel grid, then the appropriate statistic depends on the nature of the metric. E.g. For FD, you would want to be summing FD across fixels within a voxel (though taking the WM l=0 term would be more direct and have less variance since it doesn’t necessitate fixel segmentation; see e.g. this work). Whereas for FC, I’d personally instead advocate a weighted mean, where fixels with greater FD make greater contribution toward the mean; see e.g. this thread for a more extensive justification (In hindsight, taking the log, then a weighted mean, then the exponent if wanting FC rather than log(FC), would probably be slightly better).
This however assumes that computing correlations between covariate data and fixel-wise data is not the way to go. There’s no existing MRtrix3 command that will do this for you, but there’s a number of possible solutions:
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If you have an existing solution for this for voxel data, just save the fixel data files as NIfTI, and (as long as NIfTI-2 is supported) your existing solution should just work; the “voxel images” will be interpreted as size e.g. 500,000 x 1 x 1.
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A command written against the MRtrix3 C++ API for this task would not be terribly difficult to produce for anyone with some familiarity with the C++ language.
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You could use the MRtrix3 image format MatLab functions to get the fixel data in & out of MatLab / Octave in order to perform the correlations there.
Cheers
Rob