Hi Doug,
when I run a two-tailed t-test against 0 in Matlab on the Rs in pcc.nii that I get out of isxconcat-sess with -m pcc, and DOF from ffxdof.dat, I get different -log10(p) values than the ones that come out of mri_glmfit. I am not sure why this is happening.
In principle, I just want pcc maps as final output to show them on the surface (instead of p-values). So I'd be happy to follow your advice regarding the biasing effects of noise and autocorrelation and use the regression coefficients. However, mri_glmfit (v5.1) does not seem to output pcc maps of the contrasts (contrary to selxavg3-sess on the single subject level). How would I get those?

Thanks, Caspar


2013/10/1 Douglas N Greve <greve@nmr.mgh.harvard.edu>

On 10/01/2013 01:13 PM, Caspar M. Schwiedrzik wrote:
> Hi Doug,
> it would be great if you could give me some further advise on the
> group analysis of functional connectivity maps.
> Specifically, I am trying to get PCC maps for certain seeds, and am
> not planning any comparison between groups.
> Following your previous advise, I am running isxconcat-sess with -m
> pcc to get the PCC maps.
> I would then run
>
> mri_glmfit \
> --surf averagesubject hemisphere \
> --y pcc.nii \
> --no-cortex \
> --osgm \
> --glmdir analysisname
>
> *Could you please provide some more detail on what kind of analysis is
> performed when I provide pcc.nii as an input for mri_glmfit? Is it a
> t-test of the Fisher-transformed r-values against 0?
I just run a t-test of the r-values. I don't have a program to convert
them to z-values, however, there are z-values that are created in the
first level analysis. These are generated from the p-values but I bet it
would give you the same thing. Use -m z with isxconcat-sess if you want
to use the z.
> *Is the average r-value or z-value saved somewhere?
Which level? For mri_glmfit,  they are not, but it is not hard to get
them with matlab.
> *Do you take the autocorrelation into account (as in Vincent JL et
> al., 2007. Intrinsic functional architecture in the anaesthetized
> monkey brain. Nature. 447:83-86)?
Not usually, but it could be done by not including -no-whiten when you
run mkanalysis-sess. I usually use the regression coefficients instead
of correlation coefficients because that they are at least unbiased with
respect to noise level and autocorrelation.
doug


> I'd also be happy to look this up but I'd need to know where I can
> find this information.
>
> Thanks, Caspar
>
>
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--
Douglas N. Greve, Ph.D.
MGH-NMR Center
greve@nmr.mgh.harvard.edu
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