If they are already in fsaverage space, then you just need to 
concatenate them together (mri_concat) and then use the concat file as 
input (--y) to mri_glmfit
doug


On 10/01/2014 12:09 PM, lorenzo pasquini wrote:
> Dear Freesurfers,
> I have a question regarding normalization of functional activation maps.
> Let us assume I have functional activation maps on a vertex space 
> (e.g. mgh files reflecting degree centrality, which do not need 
> previous normalization of functional data). After resampling 
> activation maps into individual vertex space (bbregister and 
> vol2surf), I want to investigate if any differences across two groups 
> are detectable regarding this activation maps. Which 
> pipeline/command/stream is better to use for first normalize the 
> activation maps into a common template and then create an output that 
> can be implemented into mri_glmfit ? Should  fsfast be used? Or is 
> mri_surf2surf better?
> Thanks a lot,
>
> Lorenzo
>
>
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MGH-NMR Center
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