Dear FSL Community,
I am trying to understand the appropriate interpretation of probtrackx
output. In particular, I have a few questions regarding normalization steps
that may be necessary:
1) I would like to create connectivity maps seeded from a mask in order to
regress a between-subjects behaviour variable on the maps. However, the seed
mask is based on a different anatomically-determined segmentation for each
participant. To prepare the data for group analysis, should I divide each
fdt_ map by the number of voxels in each subject's segmentation?
2) Along the same lines, would it be fair to compare two maps, each
generated from a different seed mask in the same subject, if I first divide
the maps by the number of voxels in each mask?
3) When using "classification targets" with a seed mask, the number of paths
to each target mask will again be influenced by the number of voxels in that
mask, correct? So if I am going to perform hard classification based on
these values (using find_the_biggest, as done in Cohen et al., 2009), should
I not first divide the values in each seed_to_target_mask file by the number
of voxels in the target mask (to give each target an equal chance)?
Finally, on the parameters side, there seems to be little consensus on an
appropriate step length. I have read that 1/10th voxel size is appropriate;
that one should not venture below 0.5; and that the smallest size with
stable tract output should be selected. Is it safe to leave this parameter
as-is at 0.5? I have tried values ranging from 0.25 to 2.5 with a voxel size
of 2.5mm and cannot intelligently identify an optimal output.
Thanks in advance for your help.
Sincerely,
Jordan Poppenk
PhD Candidate, Rotman Research Institute
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