The Perceptual Prediction Paradox
- PMID: 31787500
- DOI: 10.1016/j.tics.2019.11.003
The Perceptual Prediction Paradox
Abstract
From the noisy information bombarding our senses, our brains must construct percepts that are veridical - reflecting the true state of the world - and informative - conveying what we did not already know. Influential theories suggest that both challenges are met through mechanisms that use expectations about the likely state of the world to shape perception. However, current models explaining how expectations render perception either veridical or informative are mutually incompatible. While the former propose that perceptual experiences are dominated by events we expect, the latter propose that perception of expected events is suppressed. To solve this paradox we propose a two-process model in which probabilistic knowledge initially biases perception towards what is likely and subsequently upweights events that are particularly surprising.
Keywords: expectation; inference; learning; perception; surprise.
Copyright © 2019 Elsevier Ltd. All rights reserved.
Comment in
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Predicting to Perceive and Learning When to Learn.Trends Cogn Sci. 2020 Apr;24(4):259-260. doi: 10.1016/j.tics.2019.12.005. Epub 2020 Feb 10. Trends Cogn Sci. 2020. PMID: 32160559 Free PMC article. No abstract available.
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