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Bayesian models of individual differences: combining autistic traits and sensory thresholds to predict motion perception

Powell, Georgie ORCID:, Bezeczky, Zoe, McMillin, Rebecca and Freeman, Tom C. A. ORCID: 2016. Bayesian models of individual differences: combining autistic traits and sensory thresholds to predict motion perception. Psychological Science 27 (12) , pp. 1562-1572. 10.1177/0956797616665351

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According to Bayesian models, perception and cognition depend on the optimal combination of noisy incoming evidence with prior knowledge of the world. Individual differences in perception should therefore be jointly determined by a person’s sensitivity to incoming evidence and their prior expectations. Pellicano and Burr (2012) proposed that individuals with autism have flatter priors, suggesting that prior variance is linked to the degree of autistic traits in the general population. We tested this idea by studying how perceived speed changes during pursuit eye-movement and at low contrast. We found that individual differences in these two motion phenomena were predicted by differences in thresholds and autistic traits when combined in a quantitative Bayesian model. Our findings therefore support the flatter-prior hypothesis and suggest that individual differences in prior expectations are more systematic than previously thought. In order to be revealed, however, individual differences in sensitivity must also be taken into account.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Psychology
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Additional Information: This article is distributed under the terms of the Creative Commons Attribution 3.0 License.
Publisher: SAGE
ISSN: 0956-7976
Date of First Compliant Deposit: 5 December 2016
Date of Acceptance: 1 August 2016
Last Modified: 09 May 2023 09:26

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