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Using the past to estimate sensory uncertainty

Beierholm U, Rohe T, Ferrari A, Stegle O, Noppeney U (2020)

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Publication Type: Journal article

Publication year: 2020

Journal

Book Volume: 9

DOI: 10.7554/eLife.54172

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.

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How to cite

APA:

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

MLA:

Beierholm, Ulrik, et al. "Using the past to estimate sensory uncertainty." eLife 9 (2020).

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