[pymvpa] Why to standardize (z-score) a time course?
axel.vadim at gmail.com
Fri Jul 30 19:59:58 UTC 2010
When I run classification on raw fMRI data I always make a z-score (subtract
the mean and divide by std) for each voxel / scan.
Now I tried some sort of correlation analysis, while I run a correlation for
beta images (similar to Haxby 2001). So, the z-score is going to be across
beta_per_condition values (several values only). The question is: does is
make sense to zcore the beta results?
I ran some simulations while I add a noise to each voxel. So, I know that
there is a real correlation in my data. Whereas without zscore the results
indeed show high correlation, after zscoring procedure the correlation is
virtually disappeared. I also tried just to subtract the mean across
conditions, but the correlations still do not look good.
What is the correct way to do run this analysis?
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