Re: probabilistic models of human visual perception

From: Neil H. (neuronexmachina@gmail.com)
Date: Wed Apr 05 2006 - 00:54:49 MDT


I'm not sure if this has been mentioned in the past (I'm new to this list),
but in 2002 Rajesh Rao, Bruno Olshausen, and Mike Lewicki were the editors
for an entire book on "Probabilistic Models of the Brain: Perception and
Neural Function":

http://www.cs.washington.edu/homes/rao/book.html
http://www.cs.washington.edu/homes/rao/nn_book_review.pdf (review in nature
neuroscience)

The websites for Rao, Olshausen, and Lewicki are also great resources:

http://www.cs.washington.edu/homes/rao/
http://redwood.berkeley.edu/bruno/
http://www.cnbc.cmu.edu/cplab/publications.html

On 4/4/06, George Dvorsky <george@betterhumans.com> wrote:
>
> http://www.cns.nyu.edu/~alan/research/research_bayes.html
>
> extracting prior expectations and noise characteristics from
> psychophysical experiments
>
> sensory percepts result from a fusion of our current sensory input and
> our internal expectations. more formally, bayesian inference specifies
> how an observer can fuse uncertain sensory measurements with prior
> expectations to compute an optimal estimate of a quantity in the world.
> in this work we show that this theory provides an excellent description
> of human speed perception. we are also able to "reverse-engineer" the
> sensory uncertainty and prior expectations of human observers by
> experimentally gathering their responses to moving stimuli.
> collaborators: alan stocker and eero simoncelli
> papers: NIPS 2004 | nature neuroscience 2006
> abstracts: COSYNE 2004 | VSS2005 (journal of vision (5):8, abstract 928)
> comments: news and views | scienceNOW | faculty1000
> ...
>



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