Thank you very much for anwsers!
Our scanner is Siemens Magnetom Symphony 1.5 T. In our study we use the
modification of "Stroop-Task" in order to cause a frustration in Healthy
and Depressive subjects. I think that the optimal solution is by using
the "brainmask", isn't it?
Best Regards
Alexander Lebedev
* Torben Ellegaard Lund <[log in to unmask]> [Thu, 2 Apr 2009 10:52:20
+0200]:
> I completely agree! But then again some scanners suffer from serious
N/
> 2 ghosting and then you would actually like to get the aliased eye
> movements removed from the visual cortex.
>
> Best
> Torben
>
>
>
> Den 02/04/2009 kl. 10.41 skrev Michael T Rubens:
>
> > Perhaps knowing a bit about the type of task would help determine
> > the best method. For many visual tasks it is likely that the signal
> > you would extract from the eyes would highly correlate with the
> > task, thereby regressing out signal of interest and killing your
> > power.
> >
> > -Michael
> >
> > On Thu, Apr 2, 2009 at 1:23 AM, Torben Ellegaard Lund
> <[log in to unmask]
> > > wrote:
> > Hi Dorain
> >
> > There are several ways this could be done, and which one you choose
> > should depend on your programming skills. But in general you should
> > have a pretty good prior hypothesis that the particular area you
> > want to mask out by regression will be a noise only area. But this
> > would e.g. apply to ventricles, major blood vessels and eyes.
> >
> > One way to do this is to use the Eigenvariate button, when you view
> > your results. Move the cursor to the eyes, and use the Eigenvariate
> > button to extract the timeseries from the region, or single pixel.
> > Now reanalyse your data with the extracted timeseries entered a a
> > covariate, much like you would do with motion parameters. The
> > timeseries you want to remove will be found in the variable xY.u
> >
> > Alternatively you could find typical MNI space locations for eyes
> > and ventricles and automatically extract timeseries from those
> > regions using spm_sample_vol.m This would require a bit of matlab
> > coding.
> >
> > The benefit of regression as opposed to masking is that noise could
> > be removed from other areas than the ones where you timeseries was
> > extracted from. The drawback is that you risk removing real signal,
> > if the noise looks like the signal.
> >
> >
> >
> > Best
> > Torben
> >
> >
> >
> >
> >
> >
> >
> > Den 02/04/2009 kl. 06.49 skrev Dorian P.:
> >
> > Dear Torben,
> >
> > How can a time series from a specific voxel be added as a regressor?
> >
> > And can this be done to covary out the activity similar to any voxel
> > of artifactual activity?
> >
> > Thank you.
> > Dorian.
> >
> > 2009/4/1 Torben Ellegaard Lund <[log in to unmask]>:
> >
> > Dear Alexander
> >
> > If the eye-artefact is only there in some of the con images it will
> > not make
> > it through the threshold in the final second level analysis. This
> > could have
> > been the case in a fixed effects analysis but not in a random
effects
> > analysis. If you want to avoid those artefacts you could include a
> > time-series from an eye-voxel in your design matrix. This would most
> > likely
> > remove the eye-artefact, but you risk removing some of the activity
> > as well.
> >
> > Best
> > Torben
> >
> >
> >
> > Den 31/03/2009 kl. 16.56 skrev Alexander Lebedev:
> >
> > Dear SPM experts
> >
> > I decided to check my old results, and found one problem. When I
have
> > opened con*-files in xjview tbx, strange thing appears... There are
> > activations of eye movements (notwithstanding of Normalization) in
> > some
> > con*-files. May I include such results in group study? Could you
> > advice me
> > any solutions to prevent this trouble?
> >
> > Thank you beforehand
> >
> > Best Regards
> > --
> > Alexander Lebedev.
> >
> >
> >
> >
> > --
> > Research Associate
> > Gazzaley Lab
> > Department of Neurology
> > University of California, San Francisco
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