Hi-
Can you please describe a bit more what datasets you are inputting into the initial warping program? Basically, there is probably a "source" and a "base" dataset: what you might think of as warping "from" and "to", respectively. Important considerations are:
+ relative tissue contrast of the datasets (do they both have bright CSF/ventricles and dark GM? or opposite contrasts?)
+ spatial resolution: do they have similar voxel size?
+ is this the same subjects' data, or different subjects' data?
+ initial overlap: are they "far apart" from each other, in terms of relative shifts and rotations?
+ are both dsets whole brain coverage, or something else?
+ does one/both have their skull on?
These factors determine initial parameter settings for warping, with perhaps the most important one being cost function (highly dependent on relative contrast of dsets). Knowing the above kind of information is vital for every alignment procedure (one also generally wants to consider the purpose of alignment, for determining how much warping to allow-- you have already stated that nonlinear alignment suits your purpose).
In part of the AFNI Academy set of videos online, there is a playlist about alignment, and I think it would probably be useful to watch most of these, certainly the opening one about a lot of these concepts, as well as the nonlinear one:
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www.youtube.com]
--pt
