Dear Carlos,
> In my fMRI higher level analysis using simple regression (performed
> in SPM 5), I found that activations in brain regions A and B to a
> task were negatively correlated with age. Since gray matter density
> (GMD) in some brain regions is also negatively correlated with the
> age, some may argue that reduced activations in both regions may be
> due to tissue loss rather than BOLD reduction to the task. To prove
> aging effects on BOLD responses, I have to make correction for GMD
> loss. As such, I performed another VBM analysis (in VBM 5.1) to get
> the picture of GMD changes.
>
> My question is, what then should I do to correct BOLD responses for
> brain tissue loss?
There is another angle to this question which has to do with how
accurate the spatial normalization is. If spatial normalization were
perfect, the reduced gray matter volume in older adults wouldn't
(directly) matter, because it would effectively be "expanded" during
normalization (given the typical preprocessing step of not adjusting
fMRI images during normalization). I think this is one reason that this
issue is sometimes not an area of focus. However, it still may be worth
investigating, and both of your suggestions seem reasonable to me.
> I have 2 ideas but each has something I don’t know how to perform:
>
> (1) In the fMRI higher-level simple regression analysis using age as
> covariate of interest, use each subject’s VBM data as covariate of no
> interest, factoring out it’s effect. But how can I do this? How to
> put each subject’s VBM data (file sm0w….?) in the design matrix?
The biological parametric mapping (BPM) toolbox will allow the
specification of voxelwise covariates as you suggest:
http://fmri.wfubmc.edu/software/Bpm
> (2) Produce 2 ROIs from fMRI group analysis representing brain
> regions A and B. Use them to extract individual VBM data in these 2
> regions. In SPSS, perform a partial correlation analysis (variables:
> BOLD signals in A/B, and age) controlling for regional VBM data. But
> how can I extract individual VBM data in these 2 regions?
Extracting the gray matter volume is straightforward, just like
extracting values from fMRI data. You could try using MarsBar, for example:
http://marsbar.sourceforge.net/
I don't think there is a consensus on what the "best" answer to this
question is - including gray matter volume, or not, is really asking two
different questions. In my experience it is not commonly done, but that
doesn't mean that it is not informative.
Hope this helps!
Best regards,
Jonathan
--
Dr. Jonathan Peelle
Center for Cognitive Neuroscience and
Department of Neurology
University of Pennsylvania
3 West Gates
3400 Spruce Street
Philadelphia, PA 19104
USA
http://jonathanpeelle.net/
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