I am trying to use the connectome2tck function to extract certain streamlines based on their assignment to parcellated nodes. Ultimately, I want to be able to define 4-5 cortical nodes I am interested in and select the streamlines that connect between these in each participant.
To get started I thought I would just try using a whole parcellated brain to understand how the function works, I can then refine my nodes.
To start with I used the tck2connectome function to generate the .csv file required.
tck2connectome /pathtofile/subjID_wholebrain.tck /pathtofile/subjID_aparc.a2009s+aseg.nii.gz /pathtofile/subjIDnodes_a2009s.csv -force
The .csv contains a lot of zeros, so I don’t know if that is part of the problem – the streamlines just aren’t being assigned to many parcels? Warning error: tck2connectome: [WARNING] The following nodes are missing from the parcellation image: long list of nodes!
[WARNING] (This may indicate poor parcellation image preparation, use of incorrect or incomplete LUT file(s) in labelconvert, or very poor registration)
I checked registration and it is fine. Maybe I am inputting the wrong nodes_in image, what should this be? I have been using an image parcellated in freesurfer.
When I then use the .csv I have generated into the connectome2tck I get the following error.
connectome2tck /pathtofile/subjID_wholebrain.tck /pathtofile/subjIDnodes_a2009s.csv /pathtofile/subjID_output
connectome2tck: [ERROR] Assignments file contains 12175 entries; track file contains 200000 tracks
Any guidance would be great. I think the error lies with what I am selecting as the input for the parcellation image. In the documentation the tck2connectome nodes_in argument just sates ‘the input node parcellation image’.
Thanks for any suggestions!!