Hi, Philipp-

Great, glad that was sorted for this case.

Re. the 3dAllineate command: I am just more familiar with 3dAllineate options, and there is probably more detailed control over alignment. You command looks reasonable/well-formed to me, though it is important to verify all alignment visually, to be sure. (Though, is @SUMA_Align* worked for you in this case, okeyoke.)

Re. using nonlinear vs affine: the general recommendation would be to use nonlinear whenever you are alignment brains from different subjects. Here are some notes/images about the difference of alignment (between a subject and a template):
[youtu.be]
... and here are more general alignment videos in the AFNI Bootcamp series:
[www.youtube.com]
Here, 3dNwarpApply would note be applicable, because you were only applying linear affine fits. If you had used 3dQwarp, @SSwarper, auto_warp.py, or @animal_warper, and therefore generated nonlinear *_WARP* dataset files, then 3dNwarpApply might come to bear.

--pt