Trends in Neurosciences
The Bayesian brain: the role of uncertainty in neural coding and computation
Section snippets
Bayesian inference and the Bayesian coding hypothesis
The fundamental concept behind the Bayesian approach to perceptual computations is that the information provided by a set of sensory data about the world is represented by a conditional probability density function over the set of unknown variables – the posterior density function. A Bayesian perceptual system, therefore, would represent the perceived depth of an object, for example, not as a single number Z but as a conditional probability density function p(Z/I), where I is the available
Are human observers Bayes' optimal?
What does it mean to say that an observer is ‘Bayes' optimal’? Humans are clearly not optimal in the sense that they achieve the level of performance afforded by the uncertainty in the physical stimulus. Absolute efficiencies (a measure of performance relative to a Bayes' optimal observer) for performing high-level perceptual tasks are generally low and vary widely across tasks. In some cases, this inefficiency is entirely due to uncertainty in the coding of sensory primitives that serve as
Neural representations of uncertainty
The notion that neural computations take into account the uncertainty of the sensory and motor variables raises two important questions: (i) how do neurons, or rather populations of neurons, represent uncertainty, and (ii) what is the neural basis of statistical inferences? Several schemes have been proposed over the past few years, which we now briefly review.
Discussion
We have described psychophysical evidence that shows human observers to behave in a variety of ways like optimal Bayesian observers. The most compelling features of these data in regard to the Bayesian coding hypothesis are: (i) that subjects implicitly ‘adjust’ cue weights in a Bayes' optimal way based on stimulus and viewing parameters; (ii) that perceptual and motor behavior reflect a system that takes into account the uncertainty of both sensory and motor signals; (iii) that humans behave
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