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Subject: Signal detection theory, uncertainty, and Poisson-like population codes
Date: Wed, 08 Sep 2010 06:23:41 +0200
Publication year: 2010
Source: Vision Research, In Press, Accepted Manuscript, Available online 7 September 2010
Wei Ji, Ma
The juxtaposition of established signal detection theory models of perception and more recent claims about the encoding of uncertainty in perception is a rich source of confusion. Are the latter simply a rehash of the former? Here, we make an attempt to distinguish precisely between optimal and probabilistic computation. In optimal computation, the observer minimizes the expected cost under a posterior probability distribution. In probabilistic computation, the observer uses higher moments of the likelihood function of the stimulus on a trial-by-trial basis. Computation can be optimal without being probabilistic, and vice versa. Most signal detection theory models describe optimal computation....
Source: Vision Research, In Press, Accepted Manuscript, Available online 7 September 2010
Wei Ji, Ma
The juxtaposition of established signal detection theory models of perception and more recent claims about the encoding of uncertainty in perception is a rich source of confusion. Are the latter simply a rehash of the former? Here, we make an attempt to distinguish precisely between optimal and probabilistic computation. In optimal computation, the observer minimizes the expected cost under a posterior probability distribution. In probabilistic computation, the observer uses higher moments of the likelihood function of the stimulus on a trial-by-trial basis. Computation can be optimal without being probabilistic, and vice versa. Most signal detection theory models describe optimal computation....
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