Francesca,

> I have a similar problem [see email below] but i did not understand
> how you suggested to fix it.
>
> Did you suggest to create a new mask for the analysis (intersection)?

Yes, precisely.

> and how this mask could be applied to the analysis?
>
> In sum, could you please explain me exactly how to conduct the process?

Create the intersection mask with the code snippet below. Just copy and
paste that code and a SPM file dialog will appear; select all of the
mask.img images found in each of the analyses directories that created
each of your subject's contrast images.

To apply the mask to your analysis see Stefan Kiebel's message

  http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind0006&L=spm&P=R13693

or, in a more pretty format,

  http://www.sph.umich.edu/~nichols/JohnsGems.html#Gem9

Stefan's message could be summarized as

        (1) Configure, but don't estimate a model
        (2) Modify SPMcfg.mat...

                load SPMcfg.mat
                xM.TH = -Inf;
                xM.VM = spm_vol('mask_all.img');
                save SPMcfg xM -append
        (3) Estimate the model

Hope this helps.

-Tom


    -- Thomas Nichols --------------------   Department of Biostatistics
       http://www.sph.umich.edu/~nichols     University of Michigan
       [log in to unmask]                     1420 Washington Heights
    --------------------------------------   Ann Arbor, MI 48109-2029



> ***************************************************************************
>
>
> > -----Messaggio originale-----
> > Da: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]]Per
> > conto di Thomas E Nichols
> > Inviato: venerdi 30 novembre 2001 15.42
> > A: [log in to unmask]
> > Oggetto: Re: outside activation
> >
> >
> > Tobias
> >
> > > I have a problem with activation clusters extending outside
> > > the brain.
> > >
> > > I performed a second-level Rfx-analysis according to the
> > > instructions in the SPM Help-facility and many helpful comments
> > > in the discussion list archives.
> > >
> > > Things worked really well but the results were rather thin. After
> > > reading that greater smoothing could enhance the results, I applied
> > > additional smoothing to my first-level con*-files, as recommended
> > > in a correspondance in the archives.
> > >
> > > Indeed, the results got better, i.e. the cluster sizes and
> > > significances increased. Unfortunately, the clusters are now
> > > extending considerably outside the brain.
> > >
> > > My understanding was, that this should not happen after normalizing
> > > my images to the same template before first-level analysis.
> > >
> > > Now, how is this possible ?
> >
> > By smoothing, you've "created" data outside of the brain; the new
> > data are a mixture of zeros (from outside the brain) and nonzero
> > data from within the brain
> >
> > > What can I do to get rid of such "spurious" activated voxels
> > > outside the brain ?
> >
> > Create a mask based on each of the subject's brain masks ("mask.img").
> > This is important to do, not only to eliminate voxels outside the
> > brain but to increase your power.
> >
> > You gain power because your corrected significances reflect the extra
> > search over the "cloud" of these new extracerebral voxels; when you
> > eliminate this cloud via masking, you will have fewer resels/voxels to
> > search over, and hence a less severe multiple comparisons correction.
> >
> >
> > Below is a code snippet which will create an intersection mask based
> > on each of your intrasubject masks (assuming you have run intrasubject
> > analyses on the exact same data---that is, you spatially normalized
> > your raw data.)
> >
> > -Tom
> >
> >     -- Thomas Nichols --------------------   Department of
> >        Biostatistics
> >        http://www.sph.umich.edu/~nichols     University of Michigan
> >        [log in to unmask]                     1420 Washington Heights
> >     --------------------------------------   Ann Arbor, MI 48109-2029
> >
> >
> > %
> > %  Create an intersection mask
> > %
> > %  Doesn't check that all images have same dimensions or have the same
> > %  space.
> > %
> >
> > fNm = 'mask_all.img'
> > P   = spm_get(Inf,'mask.img');
> > n   = size(P,1);
> >
> > str = sprintf('i%d&',1:n);
> > str(end) = [];
> >
> >
> > spm_imcalc_ui(P,fNm,str,{[],[],spm_type('uint8')});
>