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Using the past to estimate sensory uncertainty

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

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T. Rohe

A. Ferrari

O. Stegle

U. Noppeney


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.


Beierholm, U., Rohe, T., Ferrari, A., Stegle, O., & Noppeney, U. (2020). Using the past to estimate sensory uncertainty. eLife, 9, Article e54172.

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
Publisher eLife Sciences Publications
Peer Reviewed Peer Reviewed
Volume 9
Article Number e54172


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