Yep, I can quickly confirm: @mblesac has correctly summarised the essential bits here. As he hinted at subtly, it doesn’t have to per se be the average response, but just a unique one (per tissue) that is then used consistently for all subjects that are to be compared/combined/… among each other. In practice, the average response is just the most convenient solution for that for now, and is generally also quite a “decent” choice actually. I can also confirm that the
dhollander algorithm will avoid a lot of worries, and as far as my experience goes, it always does at least as well as
msmt_5tt, and most of the time better (in a more convenient way). There’s an improvement on the way that sits ready for the next release candidate of MRtrix3 as well.
That said, I think maybe @david142’s concerns also seems to lie with the “low” b-value of 1000. There’s no crucial problem with that actually, but it just means you have to be a very slight bit more conservative with strongly worded statements (e.g. in your discussion/conclusion type of sections on your work) on interpretation in terms of intra-axonal volume or your results being directly proportional to that, or similar statements. Don’t overdo it on the biophysical statement front there, and you should be fine. At b=1000 you’re definitely still very much sensitive to the properties that matter, but others (e.g. extra-axonal ones) start to contribute more (and more, as b-value decreases) too. It’s more subtle than that, but that’s the gist of it. Definitely have a search in the forum on this topic, there’s several other posts that touch upon this, where others of our team have responded to different aspects of this kind of question.