Someone more an expert on FSL than myself probably knows where the
actual numerical values of the covariance/correlation matrix of the
regressors can be found.
As you noted, you can always just compute the correlations yourself from
the columns of the design.mat file.
cheers,
-MH
On Wed, 2010-04-28 at 21:01 +0200, Cornelius Werner wrote:
> Hello Mike,
>
> thanks for your reply and sorry for the delay. Is there an easy way to get the correlation of the regressors? I.e., are the numerical values of the design_cov.png somewhere inside the feat-directory? The alternative would be probably to calculate a Pearson's r from the respective columns in the design.mat file. Right?
>
> Thanks a million!
> Cornelius
>
>
> Am 23.04.2010 um 14:17 schrieb Michael Harms:
>
> > Hello Cornelius,
> > The negative beta weight at t-1 means that in order to best fit the
> > actual signal something had to be subtracted from the response estimated
> > by the t-2 beta weight (and vice verse for the region with the inverse
> > pattern). What you are observing is the model simply finding the best
> > fit to the actual response, given the regressors that you've supplied.
> > It is very difficult to meaningfully interpret the individual beta
> > weights of highly correlated regressors -- the results are unstable and
> > can be changed dramatically by just subtle changes in the underlying
> > data. What is the correlation of t-2, t-1, and t0 regressors?
> >
> > cheers,
> > -Mike H.
> >
> > On Fri, 2010-04-23 at 11:34 +0200, Cornelius Werner wrote:
> >> Dear list,
> >>
> >> I am somewhat puzzled by a review I got and really can't wrap my head
> >> around this. Perhaps this is because I am just a physician - maybe you
> >> can help me see the error of my ways :-)
> >>
> >> We performed an fMRI experiment by scanning a patient population. They
> >> exhibited frequent spontaneous behavior, which we recorded and entered
> >> into the GLM as the first regressor. As we were interested in
> >> preparatory brain activity, we added two more regressors, preceding
> >> the behavioral regressor by one and two seconds, respectively, each
> >> with one second duration. Events were frequent enough and jittered
> >> enough to allow for some sort of rapid event-related design.
> >> This of course resulted in a design with three quite correlated
> >> regressors (lets say t-2, t-1 and t0). Thus, we did not model
> >> derivatives. The design matrix itself was still judged to be estimable
> >> by FSL. While I am aware that using such a setup in a whole-brain
> >> analysis in theory can yield strange results, we did obtain quite
> >> reasonable activations, corrected for multiple comparisons with voxel
> >> z>2.0 and p=0.05. Our results are anatomically meaningful and
> >> replicate (in part) previous observations.
> >>
> >> Crucially, in one of these activations, we see a significant positive
> >> beta weight at t-2, a negative beta weight at t-1, and no effect at
> >> t0. Another region shows the inverse pattern. One reviewer pointed out
> >> that, according to the signal properties of the HRF, such a signal
> >> could not be possibly observed. This is what astounded me somewhat. I
> >> was of the opinion that the BOLD effect is at least assumed to be
> >> additive. Isn't that the prerequisite for linear contrasts? Our
> >> methods folks couldn't help me out on this, so I am really interested
> >> in a clarification on this matter.
> >>
> >> Thank you very much!
> >> Cornelius
> >>
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