Hi David
> I would like to compare the strength of connectivity between seed_region_A and target_region_B across subjects.
>
> I've already registered my seed and target regions to diffusion space.
You don’t need to do this, you can run tractography in MNI space directly, which would simplify your cross-subject comparisons (unless you are interested in macroscopic aspects of the tracts - e.g. absolute volume, in which case having them in subject space also makes sense)
>
> Q1: Should I run FDT using a single waypoints mask (region B) combined with a termination mask (region B)?
Yes that sounds sensible.
>
> Q2: If yes, how do I compare fdt_paths.nii.gz output files between subjects (both seed and target ROIs have different volumes across subjects)?
It depends what aspects of the paths you want to compare.
If you are interested in the tracts volume/shape/etc. then looking at fdt_paths makes sense. If you make these measurements in MNI space you would be asking about “residual” measures after taking into account overall brain shape.
If you are interested in the probability of streamlining between A and B, then it is best to look at the seed_to_target file, as per you r Q3 below.
>
> Q3: If no, can I just run probtrackx using a single classification target (region B). This provides a seed_to_target.nii.gz image. Is it better to use this image to compare across subjects? Proj_thresh is great for multiple classification targets, but I only have 1 target of interest.
If you only have one target you don’t need to use proj_thresh.
Regarding the differences in seed/target volume, this is somewhat tricky. You cannot simply normalise by the volumes. But I think as long as your ROIs have anatomical meaning (as opposed to a voxel or a sphere) then it is not an issue.
Best wishes
Saad
>
> Essentially, I need to know the best way to normalise so that I can compare across subjects.
>
>
> Stam provided this helpful response, but I'm not sure what steps to take to normalise since I only have 1 target region.
>
> The numbers you are after are probably the ones contained in fdt_paths. The "waytotal" is just a normalisation factor and its absolute value mostly reflects your choices for different algorithmic options in probtrackx. Depending on how you run tractography this can be very similar across subjects for a given seed or quite different. It makes more sense to normalise the fdt_paths of every subject with the respective waytotal to get directly path probabilities (now normalised from 0 to 1).
>
> Another way to compare connectivity for given tracts is to use classification targets. Have a look at the online documentation and proj_thresh. Seed_to_target results are more easily comparable across subjects rather than fdt_paths, because they have some anatomical priors on. These values can be further transformed to proportions (using proj_thresh) that further reduces undesired variability across subjects (e.g. due to noise, partial volume effects).
>
> Cheers,
>
> David
>
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