[pymvpa] null classification performance in the presence of strong univariate signal??
d.soto.b at gmail.com
Thu Sep 11 19:34:14 UTC 2014
thanks Nick, I will try the within subject approach and get back
now my question is - would not zscoring solve the issue you mentioned?
I realise is not possible to zscore by chunks because these are the subjects
and only 2 samples....but I tried other zscoring schemes (i.e. by task
A vs. B or globally across the 38 samples) and still get null MVPA
would there be any advantage in trying the tstats or zstats instead of the
as the former are already zscored?
On Thu, Sep 11, 2014 at 5:50 PM, Nick Oosterhof <nikolaas.oosterhof at unitn.it
> On Sep 11, 2014, at 5:15 PM, David Soto <d.soto.b at gmail.com> wrote:
> > but I am not clear why you mention that I have 2 samples
> > only for MVPA
> I meant 2 samples per subject.
> Let me try to be clear about terminology and how I understood your
> - within-subject (first-level analysis): you ran a GLM in each subject
> individually (with all N preprocessed volumes as input), and get 2 beta
> values (samples) per subject.
> - group (second-level analysis): you ran a paired t-test over subjects
> using the beta values
> - within-subject: you did not do MVPA here.
> - group: you took the beta values from the within-subject GLM, with 2
> samples per subject, 19 subjects (chunks).
> > still did not figure out how the univariate t-test gives
> > strong signal in frontoparietal cortex but MVPA nothing
> that is still a bit puzzling indeed, though it could, in principle, be due
> to differences in overall amplitude (I think). The idea would be that if
> there is large variability in overall signal magnitude over subjects, the
> SVM hyperplane trying to separate patterns in each condition in the
> training set often falls so that in the test subject both test patterns are
> on the same side, leading to change performance.
> as a first step to understand what is going on, I would suggest to run
> within-subject MVPA using a searchlight (as I wrote earlier).
> Pkg-ExpPsy-PyMVPA mailing list
> Pkg-ExpPsy-PyMVPA at lists.alioth.debian.org
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