[pymvpa] the effect of ROI size on classification accuracy

[J.A. Etzel]

On 7/18/2014 12:06 PM, Meng Liang wrote:
> That's one reason I'm puzzled about the results. Having said that,
> sigma=5mm smoothing equals FWHM=11.8mm smoothing, so the smoothed
> image does look considerably smoother than the unsmoothed image.
That helps - I'm more used to thinking in FWHM. 11.8 with 2x2x2 voxels
is fairly substantial and likely make some sort of difference in the
results.

> I was also wondering whether this was due to some mistakes. But all
> results were generated from the same code (the only difference is the
> nifti image files being read into the script). Not sure what other
> things to check... Ideas?
Hmm. So you have 4d niftis with the (smoothed or not) functional data,
plus 3d niftis with the ROI masks, and just send different 4d niftis to
the same classification code? I think you're right then to look at the
smoothed niftis. Perhaps something went strange with the smoothing
procedure, say resulting in some sort of reordering? You could try
something like running the images through the smoothing code, but with
zero (or nearly zero) smoothing, which shouldn't change the actual
functional data, to see if it turns up anything weird (i.e. if the
zero-smoothed images don't exactly match the before-smoothing images).

Jo


-- 
Joset A. Etzel, Ph.D.
Research Analyst
Cognitive Control & Psychopathology Lab
Washington University in St. Louis
http://mvpa.blogspot.com/