Hi Moises,

I have tried to rerun the script. When using the option --ompl, I can obtain the files ended with _lengths. However, the fdt_network_matrix does not change no matter I add --pd or --ompl.  Would it be possible to send me your output fdt_network_matrix after adding option --pd?

Additional question is that if I choose to obtain the probabilistic tractography without using any of these options but dividing each matrix-row by each waytotal-row, the calculated probabilistic actually has not been adjusted for the distance. Do you have any suggestion about how to adjust for the distance?

Last question is about the meaning of the data in the fdt_path.nii and fdt_path_length.nii. I know there are 3D image data of the path distribution and path length. They can also be considered as large and multiple dimension matrix.  I am not sure what the meaning of each element in those two matrix.  Would it be possible to explain it?

Thank you so much for your help.

Sincerely,
Yingtian

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With --pd option, the results are the sum of the length of all the streamlines from ROI to ROI.
So, if there are 3 streamlines that go from A to B, with lengths [20,30,20]  mm, the result in the Matrix-cell A->B will be 70mm
With --ompl, will be 23.33mm (the mean)
Another approach is to normalize by the number of survival streamlines from each ROI, i.e. without using any of these options but dividing each matrix-row by each waytotal-row.
And another approach is to divide each Matrix-row by the size/area of each ROI.

Moises


On Wed, 31 Oct 2018 at 23:32, Yingtian Hu <[log in to unmask]> wrote:
Hi Moises,

Thank you very much for your help. I will try to run the script again and also the script with --ompl option.

Another question is about the fdt_network_matrix. Based on my understanding, the results in the fdt_network_matrix are the number of streamlines connecting ROIs without option --pd.  Now if we add option --pd, the results in the fdt_network_matrix should be the corrected number of streamlines. Is my understanding correct?

Thank you very much.

Sincerely,
Yingtian


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