Dear FSL experts,
having gone through quite a lot of older discussions I am still wondering what way would the best to work out voxel connectivity profiles. I am quite confused since I red that division by waytotal should be enough in unidirectional tracking.
So if you don't mind, I'd like to explain my 5 actual approaches for connectivity probability of each spinal voxel to be connected to M1.
just for information:
downwward tracking = M1 seed mask (500 voxels, 5000 samles each) to spinal mask as classification mask
upward tracking = spinal (230) to M1 classification mask
waypoit masks: peduncular mask, spinal mask (in upward M1)
extending exclusion mask (hemispheres, basal ganglia, cerebellum)
Calculation of every spinal voxel connectivity probability is achieved via:
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A) (Spinal voxel's downward fdt_path value) / 500 x 5000
B) (Spinal voxel's downward fdt_path value) / (only non-zero M1 voxels as read in downward's seed_to_spin x 5000)
C) (Spinal voxel's downward fdt_path value) / (only non-zero M1 voxels as read in upward's fdt_path x 5000)
D) (Spinal voxel's downward fdt_path value) / (only that M1 voxel that are non-zero as in B and (!) C x 500)
The reason for approaches B-D was to exlude those M1 voxel from the normalization that were covered by the mask but are likely not sending and/or receiving paths to/from the spinal mask. To prevent undercorrection of the spinal voxel connectivity profiles.
E) Simply upward-tracking, reading upward's seed_to_M1 voxel values / 5000. In this case, do I have to consider different cortical target mask sizes? Does they impact on tfhe spinal voxel connectivity probabilities?
I would be very grateful if you could comment shortly on each approach. I know they are arbitrary, but I really want to consider as much as possible differing parameters to get robust probabilities.
There are some more ways to calculate robust VCP I could think of (e.g. A x E, or further normalization for seed masks averaged FA), but for now I am confused enough. Can someone help me out here?
Looking forward to your comments?
Best
Robert
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