Hello,

I’ve used Dartel to normalise some functional images and then taken these to first level analysis, then smoothed the contrast images and taken them to second level analysis. So long as I set the following during smoothing :  matlabbatch{1}.spm.spatial.smooth.im = 1;%set mask to 1 to avoid crazy mask my second level mask looks normal.

I now have a new first level analysis conducted in native space. I am attempting to normalise and then smooth the 1^st level contrast images using Dartel. I have tried both the ‘normalise2mni’ routine and also the ‘combine deformations’ route (followed by a separate smoothing step) to achieve the normalisation of these contrast images. In both cases the normalised contrasts (and hence the mask created at the second level) are massive! The voxels around the brain (that are NaN in the functional images) are all given numbers very close to zero, and hence appear grey right to the edge of the FOV. Using the ‘normalise2mni’ routine this inflation occurs in x, y and z planes. Using the ‘combine deformations’ route this inflation only occurs in the x plane (left to right).

I have already searched the spm archive and this “greying” of the contrast image beyond the brain looks different to the “flowery” effects that other people have reported after normalising contrast images using Dartel.

Any ideas folks?

B.

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Dr Rebecca Lawson

UCL Institute of Cognitive Neuroscience

17 Queen Square

London

WC1N 3AR