Both are possible. I post I referred you to, were mostly to help with the response function selection (and the
-fa parameter in the
dhollander algorithm). Getting the response functions (the whole triplet of single-fibre WM, GM and CSF response functions) is still independent from the ones you choose to use thereafter in the MSMT-CSD.
As to the choice of the second tissue type being GM or CSF: that depends on your application. Optimally, you’d always want all 3 of them, but to be able to do that from just single-shell data, you need single-shell 3-tissue CSD (SS3T-CSD)… which is not yet available publicly (but I’m working on that!). So in the absence of that one, you need to choose which of GM or CSF is less important for your application. The reason @jdtournier probably suggested GM here, is because the data are ex-vivo, so CSF in the ventricles or surrounding the brain is probably no longer an “issue”. However, if you’re interested in careful interpretation of the microstructure, the value of the CSF is still there, should these animals suffer from some kind of pathology or still be in early development.
However, if you mostly need a very clean FOD for tractography, the GM is your main concern, as it’ll severely mess up the quality of your WM FODs if the GM response function isn’t included in the model. So given the information we’ve got here about your application, a WM+GM model seems the most sensible choice!
That’s exactly what I would expect indeed. For these young animals, you may need to lower the
-fa parameter. I’m not an expert in ferret anatomy, so it’s hard to judge for me from that last screenshot, since the underlying map shows WM and CSF (so hard to localise GM and “validate” whether the green voxels for the GM response are in decent locations). To evaluate this, I’d recommend overlaying those voxels on the anatomical T1 volumes you’ve shown before. Or even better, do it the other way around: open the voxels at the main image, load the T1 as an overlay and set the overlay colour scale to grey (default is hot otherwise), and make it a bit transparent with the opacity slider in the overlay tool.
Especially if you find that the GM voxels are in actual WM tissue, lowering the
-fa parameter would be advised. But do it in small steps and evaluate the result until it looks right (or at least better).
Depending on what you intent to analyse thereafter, another advice could/would be to use the same set of response functions for all your animals. In that case, I would only get the response functions from the more mature ferrets, and average them per tissue type across the more mature animals, resulting in single averaged WM, GM (and CSF, but you wouldn’t be using this one) response functions. This may make tractography slightly harder in the younger animals, but may make the FOD more meaningful.
Contact me privately if you want to look further down this avenue. There’s a few further insights and developments that I can’t disclose publicly yet here; but it would depend of course on what your goal is in this analysis / project.