On 5/5/2014 2:51 PM, Vadim Axel wrote:
I personally use always normalized and I do not think that this
should matter too much. I think given that normalization introduces
some smoothing, it may probably even increase predictions - as Hans
Op De Beeck showed that smoothing might be helpful for prediction
rate.
Unfortunately, *should* matter doesn't always mean *does* matter, and
I'm very hesitant to draw too many conclusions from experiences with
smoothing: some spatial normalization algorithms are far, far different
than Gaussian smoothing.
That doesn't mean to never spatially normalize, but I would certainly
never assume that it's a neutral procedure.
Jo
--
Joset A. Etzel, Ph.D.
Research Analyst
Cognitive Control & Psychopathology Lab
Washington University in St. Louis
http://mvpa.blogspot.com/
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