[Mrtrix-discussion] On trials parameter in streamtrack

[Alessandro Calamuneri]

Hi mrtrix users,

I was wondering how streamtrack work in generating and selecting tracks. As
far as I could see from mailing list, number of streamlines generated are
usually higher than actually selected. Both commands can be set by -maxnum
and -number options.
Reasons for excluding a streamline depend basically on tract length,
inclusion or exclusion rois used.
To get somehow a sense of the probability to get a connection one could
divide number of selected streamlines to the number of generated ones.
Looking at the messages in the archives, during probabilistick tracking,
seed points are randomly selected within the seed mask, then a direction is
chosen and eventually stream process starts if amplitude in that direction
is higher than initcutoff.
>From my point of view an approach where a certain number of attempts are
made from each voxel in brain mask would make a lot of sense to provide
meaningful probability results related to "existence" of a connection;
giving the opportunity to choice output number could be potentially
dangerous, expecially when making connectomics analyses.
I see there exists an option in streamtrack, -trials. How it does work
precisely?
I tried with a single voxel seed, fixing maxnum and number (100 or 500) and
varying trials parameter. Considering i have set a negligible cutoff for
minlength (1mm), what i see is that results strongly depend on trials
parameter. Really small trials (5) cause all tracts terminating quite close
to seed point; with higher number of trials, results get better. On the
other side, the larger this number, the higher the likely to get spurious
connections.
Is it correct to say, due to request of a certain number of streamlines, a
lot of seed points are initializied within that unique seed voxel, and only
after that trial parameter gets effective?
I am asking because I am not interested in making whole brain analysis,
hence I want to carefully inspect how these parameters work. In the light
of that, what could be a good compromise when handling trials, number and
maxnum parameters?

Best,
Alessandro

-- 
Alessandro Calamuneri, M.Sc., PhD
Department of Neurosciences, University of Messina, Italy
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