Bear with me - I am a novice....
I realise there is a code for reversing the linear affine components
(although I have yet to track it down) but I am also wondering whether
there is now a way in which the nonlinear component can be reversed.
My understanding of the basic principles of nonlinear transforms would
suggest that this isn't possible, so therefore I wondered if I were to
describe what I wish to do, seomone could suggest an optimum strategy:
I want to use group fMRI activation clusters as seed points for
probabilistic tractography. Clearly I need to do the tracking in the
native space, so I want a means to reverse normalise the group-level
clusters back into the individual brain. I guess that I can merely
invert a linear transform to get an approximate position of the
cluster, and then adjust the position manually, however, our concern
is that the linear components are least effective in our area of
interest (which is the temporal pole) and we infact need the
non-linear component.
Does anyone have any suggestions?
--
Richard Binney BSc(Hons) MSc
PhD Student
University of Manchester
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