I am a new user of MRtrix and although I have experience in treating the dMRI signal to find information about the microstructure, it is the first time I am performing tractography.
I’ve started by taking some subjects of the HCP release S1200 and following the suggested pipeline http://mrtrix.readthedocs.io/en/latest/quantitative_structural_connectivity/ismrm_hcp_tutorial.html
Since I don’t have access to a cluster at the moment, the only thing I’ve changed from the pipeline is that I’ve generated 10M streamlines and then I used SIFT command to get 3M streamlines (I thought that this was sufficient to start my analysis).
Since I wanted to investigate some properties in the connection between different areas of the brain I’ve used the given aparc.a2009s+aseg.nii.gz file containing the FreeSurfer parcellation to construct the connectome and here comes my question:
I’ve notice that some nodes have a lot of connections to themselves (for example in one subject the node 95, i.e. ctx_rh_G_and_S_cingul-Ant, has 15133 streamlines connected itself which is about 0.5% of the total streamlines I’ve created). How should I interpret these connections? Because if I extract them using connectome2tck and I visualise them with mrview I see that they are all kind of “U streamlines” that start and end in the selected ROI without passing through it but passing through different portion of white matter (confirming that the ACT constraint works). Can you help me in the interpretation of those streamlines? Are all of them “anatomically reliable” or should I somehow threshold the results?
As connections that both start and end within the same parcel; that’s basically it
A random compilation of thoughts:
It would actually be highly unusual if we were to place a relatively crude parcellation atop a cortical ribbon that looks basically continuous, and somehow perfectly align the borders between parcels such that there are no connections whatsoever that both start and end within the same parcel. Bear in mind here that tractogram generation and connectome construction are two separate steps.
If you picture these histograms (as well as those in my article and the biological justification enclosed within), there are a massive number of very short WM fibres. If the lengths of these very short fibres are shorter than the spatial extent of the parcels, then it’s inevitable that there will be more intra-parcel connections than inter-parcel connections.
Particularly with HCP data, the default minimum streamline length during tracking will be much shorter in MRtrix3 (twice the voxel size, or 2.5mm) compared to other software packages (~ 20-30mm).
Are all of them “anatomically reliable” or should I somehow threshold the results?
You’ll find that a lot of global connectome metrics either mask these values out before calculation, or just ignore them outright. So it depends on exactly what kind of analysis you’re doing.
Even though I’d advocate that such connections do in fact exist, chances are we’re not able to get a good quantitative estimate of how many such connections there are. Not only due to the streamline minimum length criterion, which is an ill-posed threshold from the outset given that’s where so many biological fibres actually exist, but also because there’s most likely a continuum of different connection lengths, from ~ mm down to sum-mm, and even shorter connections that are entirely within the GM but nevertheless along the plane of the cortical ribbon.
thank you very much for your reply and the useful “random thoughts”.
I will read very carefully your article. Thank you for the advise.
One of the reasons why I’ve asked this question is because I wasn’t able to find a paper where the authors were considering these streamlines for their connectivity analysis and I was wondering why. So I’ve decided to visualise some of them. For example, if I consider node 6 in MRtrix lookup table (figure attached), some of the self-connecting streamlines are very short and connect really close points of the same parcel, but some others go almost until node 95 (which is the symmetric parcel on the right side of the brain) and come back. I wonder if I made a mistake in the pipeline or if it is normal to have this kind of streamlines and I should simply threshold my result to be able to consider self-connections in my connectivity analysis.
Is there a chance that these short self connections actually represent somehow the “shorter connection that are entirely within the GM”? Probably not, but I was wondering if we have a mean to detect such structures within GM and I wasn’t able to find any good reference.
I wonder if I made a mistake in the pipeline or if it is normal to have this kind of streamlines …
The latter. This is streamlines tractography we’re talking about
… and I should simply threshold my result to be able to consider self-connections in my connectivity analysis.
Well the connections are there, so the question is whether you should threshold to remove such connections, not consider them; moreover, as mentioned previously, whether retaining or removing them will actually have any effect whatsoever on the analysis.
Is there a chance that these short self connections actually represent somehow the “shorter connection that are entirely within the GM”?
While there’s probably some short connections reconstructed within the WM that are in fact following fibre orientations measured from the GM but spatially extended due to partial voluming, there are likely also short connections within the WM as well; from a naive perspective, whatever is the longest length of individual neurons that are entirely within the GM, I would expect axons of that length and longer to be present within the WM.
I was wondering if we have a mean to detect such structures within GM and I wasn’t able to find any good reference.
There are definitely groups out there trying to do such; but you’d have a hard time having confidence in the reconstruction of such even at the resolution of HCP data. So I’d probably be looking through the ex vivo DW imaging literature.