Dear Group
In response to my question below, Russ wrote that data are generally
globally scaled to a mean of 100 on the beta0 image I think (the
baseline)? Is this true by default for spm2 data as I found several
subjects with within-brain average beta0's in the 300's across all
voxels?
Was I supposed to press some option to globally normalize / grand mean
scale data in fMRI stats so that I could then do group random effects?
I read on several fMRI protocls for spm that global normalization (grand
mean scaling may be a problem). Please help if at all possible as this is
the step I am stuck in within my data analysis.
see below for my initial
question question and Russ's response.
Sincerely,
Jeffrey Lorberbaum
> On Sun, 30 Nov 2003, Russ Poldrack wrote:
>
> > I think the answer is that because the data are globally scaled to a
> > mean of 100, the betas should always be in relatively similar units
> > (roughly percent). This slightly finesses the issue that the mean of
> > many voxels will be quite different from 100 (since it is normalized
> > across the whole brain), so this issue still exists to some degree.
> > I'll be interested to hear if there are other issues that impact on
> > this.
> >
> > cheers
> > russ
> >
> > On Nov 30, 2003, at 7:44 PM, Jeffrey P Lorberbaum wrote:
> >
> > > Dear Group
> > >
> > > I am asking a basic fMRi stats question which I asked just before the
> > > Thanksgiving holidays and am trying again to see if I can get help.
> > >
> > >
> > > I have a question about the regression coefficients (beta.imgs)
> > > produced
> > > by the spm2 analyses. Is the baseline b0 (constant coefficient)
> > > image weighted in some fashion by default? If not then if I am thinking
> > > correctly, this would be a problem for a random effects analysis.
> > >
> > > Say one person at a voxel had two conditions cond1 with a beta weight
> > > of 2 and cond2 with a beta weight of 1 and a baseline b0 of 1000.
> > >
> > > (ie. yperson1 = 2*cond1 + 1*cond2 + 1000 + error)
> > >
> > > Say another person at a voxel had two conditions cond1 with a beta
> > > weight
> > > of 2 and cond2 with a beta weight of 1 and a baseline b0 of 500.
> > >
> > > (ie. yperson2 = 2*cond1 + 1*cond2 + 500 + error)
> > >
> > >
> > > The beta weights in the second person accounts for a bigger
> > > percent change relative to baseline when looking at cond1, cond2,or
> > > cond1
> > > - cond2. How does a random effects analysis that looks at mean beta
> > > weights and the variance among them account for this?
> > >
> > > Am I thinking correctly?
> > >
> > > Thanks
> > > Sincerely,
> > > Jeff Lorberbaum
> > >
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