Different types of uncertainty in multisensory perceptual decision making

Aston, S.; Nardini, M.; Beierholm, U.

Abstract

Efficient decision-making requires accounting for sources of uncertainty (noise, or variability). Many studies have shown how the nervous system is able to account for perceptual uncertainty (noise, variability) that arises from limitations in its own abilities to encode perceptual stimuli. However, many other sources of uncertainty exist, reflecting for example variability in the behaviour of other agents or physical processes. Here we review previous studies on decision making under uncertainty as a function of the different types of uncertainty that the nervous system encounters, showing that noise that is intrinsic to the perceptual system can often be accounted for near- optimally (i.e. not statistically different from optimally), whereas accounting for other types of uncertainty can be much more challenging. As an example, we present a study in which participants made decisions about multisensory stimuli with both intrinsic (perceptual) and extrinsic (environmental) uncertainty and show that the nervous system accounts for these differently when making decisions: they account for internal uncertainty but under-account for external. Human perceptual systems may be well equipped to account for intrinsic (perceptual) uncertainty because, in principle, they have access to this. Accounting for external uncertainty is more challenging because this uncertainty must be learned.

Citation

Aston, S., Nardini, M., & Beierholm, U. (2023). Different types of uncertainty in multisensory perceptual decision making. Philosophical Transactions of the Royal Society B: Biological Sciences, 378(1886), Article 20220349. https://doi.org/10.1098/rstb.2022.0349

• Journal Article Type: Article
• Acceptance Date: Jun 18, 2023
• Online Publication Date: Aug 7, 2023
• Publication Date: Sep 25, 2023
• Deposit Date: Jul 4, 2023
• Publicly Available Date: Jul 5, 2023
• Journal: Philosophical Transactions of the Royal Society B
• Print ISSN: 0962-8436
• Electronic ISSN: 1471-2970
• Publisher: The Royal Society
• Peer Reviewed: Peer Reviewed
• Volume: 378
• Issue: 1886
• Article Number: 20220349
• DOI: https://doi.org/10.1098/rstb.2022.0349
• Public URL: https://durham-repository.worktribe.com/output/1168901
• Publisher URL: https://royalsocietypublishing.org/journal/rstb