I must admit I’ve never thought about that, but mostly because I haven’t thought of a situation where this would be required (?). But my instinctive reaction here is that this can’t work – but as is so often the case, this depends on why you’re doing this.
In general, no. If you look at the relationship that underpins SIFT/SIFT2, it’s trying to explain the measured fODF in each voxel as a combination of the streamlines segments that pass through it, assuming each contributes the same amount or or not at all (SIFT); or each contributes a variable amount (SIFT2). From that point of view, the SIFT2 weights represent the contribution of each streamline to the fODF (itself proportional to the DW signal), in units proportional to (very roughly) apparent fibre cross-sectional area – in other words, the apparent volume of white matter per unit length, for that streamline (though I have a feeling @rsmith may wish to comment on that interpretation, it’s hard to nail it down precisely…).
As soon as you apply non-rigid warps to your streamlines, you will be modifying the length of the streamline segments in ways that vary even along a single streamline, destroying that relationship. You will also be modifying the cross-sectional areas across the streamlines, stretching spreading their contributions across into adjacent voxels, and again destroying that relationship.
So from that point of view, I don’t think it makes sense to expect the SIFT2 weights to still carry their original meaning once transformed.
You may however find that the relationship to the transformed and modulated fODF is preserved, since the effects of the warp on the apparent fibre density are exactly what the modulation tries to account for – though I’d be wary of introducing errors in the process.
Another possibility might be if your intention was for example to compute the SIFT2 weights per subject and transform all of these weighted tractograms into some template space to perform some kind of inter-subject analysis, then this might make sense: in this case, the SIFT2 weights retain their original meaning. This would in many ways resemble an FBA analysis, but might make sense depending on the question…
So in short: depends on what you plan to do and what interpretation that implies for the transformed streamlines & their weights…
Hope that kinda vaguely helps…
All the best,