I did not have a specific application in mind when I wrote it. Part of 
it was to help look for artifacts (ie, structured noise in the 
residuals). It will always give you a number of eigenvectors equal to 
the smaller of the number of "temporal" dimensions or spatial 
dimensions. For imaging, this is usually the "temporal" (14 in your case).

doug

On 12/05/2014 12:00 PM, Thomas DeRamus wrote:
> Appreciate the quick reply. I may be re-framing my question a bit 
> here, but I'm curious as to the context in which one would use the PCA 
> analysis. Is it meant primarily for functional data or can it be 
> applied to glmfits for structural data? When I ran this the first 
> time, I got 14 eigenvalues on a subset of 14 participant MPRAGE's from 
> a large dataset to test the --pca flag (I haven't seen much about it 
> on the documentation). In hindsight, I think the 14 eigenvalues I'm 
> getting are actually the number of participants in the study, which 
> means I am probably using this flag in the wrong context. I'm curious 
> about using this on a larger dataset from different types of scanners 
> and finding components unique to scanner type using pca that can be 
> addressed in later group analyses. Given that PCA uses "temporal" 
> components (if you don't mind could you expand on this?) can it even 
> be applied to morphological data like individual T1 images? Or should 
> it be used solely in isolation with functional images for individual 
> subjects (such as the way GIFT or ICA toolboxes would?).
>
> Basically I'd like to know conceptually when you would use this and 
> what it is capable of doing. My apologies if that is a horrible 
> combination of vague and broad.
>
> On Thu, Dec 4, 2014 at 1:50 PM, Douglas N Greve 
> <[email protected] <mailto:[email protected]>> wrote:
>
>
>     It performs pca/svd on the residuals. The sdiag.mat I think
>     includes the
>     singular values but also the percent variance explained by each
>     component and the cumulative explained by all components upto and
>     including that component. You probably just need to change the overlay
>     thresholds on the v.mgh to make it look more reasonable. The range of
>     the singular values depends on your data so you can't just look at
>     them
>     and decide they are too big. The u.mtx are the "temporal" components.
>
>     doug
>
>     On 12/04/2014 11:10 AM, Thomas DeRamus wrote:
>     > Dear Freesurfer experts,
>     >
>     > Potentially super-noob question here, but I'm curious about the
>     --pca
>     > flag on mri_glmfit.  I can see that it does PCA/SVD on the
>     dataset? in
>     > question and saves the residuals to the glmdir specified, but I was
>     > unable to find anything in the documentation describing what exactly
>     > it is doing. I got sdiag.mat, stats.dat (with some rather large
>     > eigenvalues, on the order of 40k, but they might look more
>     normal once
>     > I demean my variables), a u.mtx, a v.mgh surface overlay, and an
>     error
>     > log (stating MatlabRead: readHeder returned NULL, ImageRead
>     > (/path/glmdir/pca-eres/sdiag.mat) failed. When I loaded the
>     v.mgh, it
>     > looked rather binarized (with red and blue colors covering the
>     entire
>     > cortex mask for that hemi).
>     >
>     > May I ask how it is computing these eigenvalues? What the sdiag and
>     > u.mtx files are used for? And what is being displayed in the
>     v.mgh (is
>     > it components? if so, what do these components reflect?).  And most
>     > importantly, is this meant primarily for functional data or can
>     it be
>     > applied to mophometric data? If it can be used for the latter,
>     what is
>     > being fed into the PCA/SVD to determine spatial components?
>     >
>     > --
>     > *Thomas DeRamus*
>     > UAB Department of Psychology, Behavioral Neuroscience
>     > Graduate Research Trainee
>     > Civitan International Research Center
>     > 1719 6th Ave S, Suite 235J, Birmingham, AL 35233
>     > _Phone_: 205-934-0971 <tel:205-934-0971> _Email:_
>     [email protected] <mailto:[email protected]>
>     > <mailto:[email protected] <mailto:[email protected]>>,
>     [email protected] <mailto:[email protected]> <mailto:[email protected]
>     <mailto:[email protected]>>
>     >
>     >
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>     --
>     Douglas N. Greve, Ph.D.
>     MGH-NMR Center
>     [email protected] <mailto:[email protected]>
>     Phone Number: 617-724-2358 <tel:617-724-2358>
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> -- 
> *Thomas DeRamus*
> UAB Department of Psychology, Behavioral Neuroscience
> Graduate Research Trainee
> Civitan International Research Center
> 1719 6th Ave S, Suite 235J, Birmingham, AL 35233
> _Phone_: 205-934-0971 _Email:_ [email protected] 
> <mailto:[email protected]>, [email protected] <mailto:[email protected]>
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-- 
Douglas N. Greve, Ph.D.
MGH-NMR Center
[email protected]
Phone Number: 617-724-2358
Fax: 617-726-7422

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