[pymvpa] null classification performance in the presence of strong univariate signal??

[J.A. Etzel]

Yes, that looks like a reasonable single-subject searchlight accuracy 
map, and not the sort of thing that would lead to high significance in 
all voxels in a t-test.

I second Nick's guess that you might have tested against zero instead of 
chance.

Jo


On 9/18/2014 5:44 PM, David Soto wrote:
> Thanks Jo and Nick for the advise, the individual acc maps
> which I registered to MNI prior to t-test look fine to me
> (see example pic attached, spot with accuracy around 0.7)...there might
> be something going on in the t-testing done  in FSL, though I cant see
> what- as should work fine across imaging data types -
>
> I will try your R code - thanks!
>
> ds
>
> On Thu, Sep 18, 2014 at 11:04 PM, J.A. Etzel <jetzel at artsci.wustl.edu
> <mailto:jetzel at artsci.wustl.edu>> wrote:
>
>     I agree with Nick that something might have went wrong with the
>     t-test. I've never tried one in fsl, either, but usually use R.
>     Here's a little bit of R code to do a voxelwise t-test:
>     http://mvpa.blogspot.com/2014/__09/demo-r-code-to-perform-__voxelwise-t-test.html
>     <http://mvpa.blogspot.com/2014/09/demo-r-code-to-perform-voxelwise-t-test.html>
>
>     I assume you looked at the 19 subjects' accuracy maps before trying
>     the t-test ...
>
>     Jo