Using the past to estimate sensory uncertainty

Beierholm, U.; Rohe, T.; Ferrari, A.; Stegle, O.; Noppeney, U.

Abstract

To form a more reliable percept of the environment, the brain needs to estimate its own sensory uncertainty. Current theories of perceptual inference assume that the brain computes sensory uncertainty instantaneously and independently for each stimulus. We evaluated this assumption in four psychophysical experiments, in which human observers localized auditory signals that were presented synchronously with spatially disparate visual signals. Critically, the visual noise changed dynamically over time continuously or with intermittent jumps. Our results show that observers integrate audiovisual inputs weighted by sensory uncertainty estimates that combine information from past and current signals consistent with an optimal Bayesian learner that can be approximated by exponential discounting. Our results challenge leading models of perceptual inference where sensory uncertainty estimates depend only on the current stimulus. They demonstrate that the brain capitalizes on the temporal dynamics of the external world and estimates sensory uncertainty by combining past experiences with new incoming sensory signals.

Citation

Beierholm, U., Rohe, T., Ferrari, A., Stegle, O., & Noppeney, U. (2020). Using the past to estimate sensory uncertainty. eLife, 9, Article e54172. https://doi.org/10.7554/elife.54172

• Journal Article Type: Article
• Acceptance Date: Dec 13, 2020
• Online Publication Date: Dec 15, 2020
• Publication Date: 2020
• Deposit Date: Dec 14, 2020
• Publicly Available Date: Dec 14, 2020
• Journal: eLife
• Electronic ISSN: 2050-084X
• Publisher: eLife Sciences Publications
• Peer Reviewed: Peer Reviewed
• Volume: 9
• Article Number: e54172
• DOI: https://doi.org/10.7554/elife.54172
• Public URL: https://durham-repository.worktribe.com/output/1249139