I have an additional question related to tck2connectome, then connectome2tck

I generated connectomes and output assignments without any scaling:

`tck2connectome 10M_ten_prob_SIFT.tck ROIv_HR_th_dil.nii.gz connectome_A.csv -zero_diagonal -out_assignments tck2connA.csv -force`

I was expecting to then be able to run connectome2tck to extract bundles of interest based on the connectomes that i am comparing.

For instance, i’ve read in 2 connectomes and am interested in the connection between nodes 174,225 … I know in connA has 21 streamlines, but 0 in connB.

`In [217]: connA[174][225], connB[174][225] Out[217]: (21.0, 0.0)`

So i’d expect to be able to run connectome2tck and get a bundle with 21 streamlines:

`connectome2tck -exclusive -nodes 174,225 10M_ten_prob_SIFT.tck tck2connA.csv edges/edge`

However, on some of these results where i know connA has some number, but connB has zero i am getting empty tck files … is there something i am missing, or misunderstanding :

`tesla:cmp12_test cmp12$ tckinfo edges/edge174-225.tck

Tracks file: "edges/edge174-225.tck"

SIFT_mu: 0.0025456627053402335

act: anat/t1_5tt.nii.gz

backtrack: 0

**count: 0**

init_threshold: 0.0599999987

max_angle: 45

max_dist: 250

max_num_attempts: 10000000000

max_num_tracks: 100000000

max_seed_attempts: 50

method: TensorProb

min_dist: 3

mrtrix_version: 3.0_RC1

rk4: 0

seed_dynamic: hires/WM_FODs.mif

source: hires/hires_biascorr.mif

step_size: .425

stop_on_all_include: 0

threshold: 0.06

timestamp: 1498571432.8158144951

total_count: 42520

unidirectional: 0

ROI: seed WM_FODs.mif`