Dear Catherine,
I suppose your problem lies in these 7 lines of spm_sn3d:
> % Rescale images so that globals are better conditioned
> gl = spm_global(VF);
> VF.pinfo(1:2,:) = VF.pinfo(1:2,:)/gl;
> for i=1:prod(size(VG)),
> gl = spm_global(VG(i));
> VG(i).pinfo(1:2,:) = VG(i).pinfo(1:2,:)/gl;
> end;
This means that all images normalised to a certain template will get the same mean activity. As you have a group experiment,
realignment itself will probably not be enough to get comparable data sets. The fastest solution I can think of is to comment
these lines,do your analysis, and then uncomment the lines. But this is a bit tricky, because the normalisation routine is not
only sensitive to grey value distributions (as is the Mutual Information alignment measure), but also to the grey values
themselves. I hope it's worth a try...
Good luck,
Alle Meije Wink
--
Alle Meije Wink
Institute for Mathematics and Computing Science, room 105
University of Groningen P.O. Box 800
9700 AV Groningen
Telephone +31 50 363 71 27 The Netherlands
Fax: +31 20 875 48 00
E-mail: [log in to unmask]
WWW: http://www.cs.rug.nl/~wink
" I guess it comes down to a simple choice, really.
Get busy living, or get busy dying. "
(Andy Dufresne in The Shawshank Redemption)
