Hi Will
If your aim is to calculate connection probabilities between a set of N regions, you can do one of the following:
1) Set the seed mask to be the union of all N rois, and a list of targets that also include all your rois.
The results in seed_to_<targets> can be subsequently split up to get NxN connections.
2) You can use an option called --omatrix1 (un-documented at the moment). This will calculate connection probability between every voxel and every other voxel of your seed mask. So if your seed is the union of N rois, you can split the matrix to get NxN connections probs.
The only issue with (2) is that the output matrix format is nifti, so you will be bound to use ~30K voxels max. This is not the case for (1).
As for your second question, I suggest reading the Behrens/Jbabdi chapter on tractography (from Tim & Heidi's book). In a nutshell, the quantity that you get from probtrackx is the probability that a path through the diffusion field goes from A to B. Or a spatial histogram of this probability distribution from fdt_paths.
Cheers,
Saad.
> All,
>
> I'm new to the FSL forums, so apologies if I'm posting in the wrong place.
>
> We are working with structural (DTI) data, and trying to do whole brain probabilistic tractography. We know how to do region to region tractography in FSL, but are unsure if there is an efficient way to seed and setup processing so that we can process the entire brain at once. As an output, we'd like to have a measure of connectivity between each of our regions (e.g., if we have n regions, we'd like to obtain n^2/2 (undirected) connections overall).
>
> As a followup question, is there an accepted way to go from FSLs probability map output to fibers, or how does the community usually interpret FSL's output?
>
> Any guidance or links to others' approaches would be much appreciated.
>
> Thanks,
> -Will
>
--
Saad Jbabdi
University of Oxford, FMRIB Centre
JR Hospital, Headington, OX3 9DU, UK
(+44)1865-222466 (fax 717)
www.fmrib.ox.ac.uk/~saad
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