Hi new mrtrix user,
I am trying to generate a connectome with the edge weights being the density of fibers from one node to another divided by the receiver node volume. I have used the invvol command. Does this give me what I want to do? I also need the lengths of the fibers for which I used the length command. This I am assuming is not weighted by the weight between the nodes,
Hi new mrtrix user,
Assuming you are working with an up-to-date MRtrix3 installation (since the interface to
tck2connectome changed some time ago), the
-scale_invnodevol option will divide the contribution of each streamline to the connectome by the average of the two node volumes, as suggested in Patric Hagmann’s 2008 paper (I should probably add that to the command’s
With regards to your second requirement, I suspect this is what you’re looking for. It’s very important to decompose precisely the quantity you’re looking for: Taking the mean value of those streamlines within the edge (where the value for each streamline is the length of that streamline) effectively “removes” the contribution of the “weighting” between the two nodes, giving you the “mean streamline length” of the edge.
Thanks so much for your response, it was very helpful. One more quick question, I was going through the link you sent me and I noticed there is a scale_invnodevol command combined with scale_invlength. Does this normalize the weight in a better way so that the long range connections weigh about the same as the shorter ones? I know that the between hemisphere connections are known to be fewer and I was hoping to be able to account for that.
-scale_invnodevol option performs a scaling quite different to that of
-scale_invlength: it is based on the volumes of the two parcels involved in the connection, and is not related to the length of the connection. This scaling mechanism is also described in the manuscript mentioned above.
I wouldn’t say that either of these weights are “better” at “normalizing” the connection strengths. The effectiveness of
-scale_invlength relative to the SIFT method is discussed in this manuscript. I also rambled about these issues in this blog post. While inter-hemispheric connections may be relatively sparse (~ 2% of all white matter fibres, as I mentioned in this article), one must be extremely careful about understanding how such observations are made, whether they are in fact “biases” that can / should be “fixed”, and the potential ramifications of any heuristic mechanisms applied.