The role of priors in Bayesian models of perception

Teufel, Christoph ORCID: https://orcid.org/0000-0003-3915-9716, Subramaniam, Naresh and Fletcher, Paul C. 2013. The role of priors in Bayesian models of perception. Frontiers in Computational Neuroscience 7 , 25. 10.3389/fncom.2013.00025

Preview

PDF - Published Version Available under License Creative Commons Attribution. Download (571kB) | Preview

Abstract

In a recent opinion article, Pellicano and Burr (2012) speculate about how a Bayesian architecture might explain many features of autism ranging from stereotypical movement to atypical phenomenological experience. We share the view of other commentators on this paper (Brock, 2012; Friston et al., 2013; Van Boxtel and Lu, 2013) that applying computational methods to psychiatric disorders is valuable (Montague et al., 2012). However, we argue that in this instance there are fundamental technical and conceptual problems which must be addressed if such a perspective is to become useful. Based on the Bayesian observer model (Figure 1), Pellicano and Burr speculate that perceptual abnormalities in autism can be explained by differences in how beliefs about the world are formed, or combined with sensory information, and that sensory processing itself is unaffected (although, confusingly, they also speak of sensory atypicalities in autism). In computational terms, the authors are suggesting that the likelihood function is unaltered in autism and that the posterior is atypical either because of differences in the prior, or because of the way in which prior and likelihood are combined. The latter statement is problematic because within the framework of probability theory, the combination of these two components is fixed as determined by Bayes' theorem: they are multiplied. Put simply, a mathematically consistent Bayesian model cannot accommodate a perceptual abnormality in autism that is due to the way in which belief and sensory information, i.e., prior and likelihood, are combined. Furthermore, if sensory processing is mathematically represented as a likelihood function (as it typically is within Bayesian models), then changes in the prior cannot lead to changes in sensation, as the authors claim (they can only lead to changes in perception).

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Psychology
Additional Information:	This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc. This document is protected by copyright and was first published by Frontiers. All rights reserved. It is reproduced with permission.
Publisher:	Frontiers Media
ISSN:	1662-5188
Date of First Compliant Deposit:	30 March 2016
Date of Acceptance:	15 March 2013
Last Modified:	09 May 2023 02:06
URI:	https://orca.cardiff.ac.uk/id/eprint/69819

Citation Data

Cited 20 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item