Dear MRtrix expert,
I read (on the batman tutorial) that using GMWM interface as seeding mechanism tend to penalize subcortical connections. A small pilot I did on my data seem to confirm this. As suggested from the tutorial I was going to concatenate the whole-brain tractography ( -seed_gmwmi) with the results of a second tractography in which I employ -seed_image with a mask of subcortical structures (basal ganglia, amygdala, hippocampus and “midbrain”) as input. However, I am not sure if the sifts2 framework would still be applicable in this context. The data are not formidable to start with (b-values 0 and 1000; directions: 30 or 48 in a subset of cases; nevertheless I would like to apply sift2).
An alternative would be to use dynamic seeding. The purpose is to generate connectivity matrices. Would you suggest the former or the latter approach?
Another related question is about combining cortical and subcortical regions in whole-brain tractography. I know that this a bit of a speculation but my understanding is that not everybody agree on dealing with cortical and subcortical structures in the same way. In my lab we encounter the problem using deterministic tractography with DTI-quality data, where it appears that subcortical structures “steal” streamline from cortica-cortical connections especially in cases presenting frank atrophy (cause by neurodegeneration). In a small pilot I run using MRtrix3 (taking a probabilistic approach, FOD2) on the same data the problem do not appear to be evident, but I was wondering if you would have any comment on the topic.
Many thanks in advance!