# Streamline assignment method for tractograms generated without ACT

**URL:** https://community.mrtrix.org/t/streamline-assignment-method-for-tractograms-generated-without-act/8838
**Category:** Uncategorized
**Created:** [September 16, 2026, 6:35pm UTC](https://community.mrtrix.org/t/streamline-assignment-method-for-tractograms-generated-without-act/8838 "2026-09-16T18:35:47Z")
**Posts on this page:** 1
**Page:** 1

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### Author: ![BrainzRCool](https://community.mrtrix.org/letter_avatar_proxy/v4/letter/b/58956e/32.png) [@BrainzRCool](https://community.mrtrix.org/u/BrainzRCool)
#### Post date: [September 16, 2026, 6:35pm UTC](https://community.mrtrix.org/t/streamline-assignment-method-for-tractograms-generated-without-act/8838/1 "2026-09-16T18:35:48Z")

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I ran tractography on our neonatal diffusion data. For the tckgen -mask argument, I used a liberal mask which includes the white matter, deep grey matter, cerebellum and brainstem. I did not use anatomically constrained tractography (ACT), because we do not have good masks for cGM, WM, dGM, etc., despite my best efforts.

The resulting tractograms look fairly good. My question is: how should I assign streamlines to regions in tck2connectome? In the tractograms, there are many streamlines which pass right through deep grey matter structures, and terminate in cortical grey matter at both endpoints. If I _had_ used ACT, I expect that many of these streamlines would instead terminate within the deep grey structures. My concern is that if I use the standard -assignment\_radial\_search in tck2connectome, I will be drastically underestimating connectivity to the deep grey structures because streamlines passing straight through deep grey structures will not be assigned to them. I am aware of the -assignment\_all\_voxels option, but I think using this would introduce a new problem given that I want to use SIFT2 weights: if a streamlines connects nodes A-B-C, I do not think the same SIFT2 weight should be attributed to connections A-B, B-C and A-C.

Any advice for this situation would be greatly appreciated.