The anticipation of events in time

Matthias Grabenhorst (), Georgios Michalareas, Laurence T. Maloney and David Poeppel
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Matthias Grabenhorst: Max-Planck-Institute for Empirical Aesthetics
Georgios Michalareas: Max-Planck-Institute for Empirical Aesthetics
Laurence T. Maloney: Center for Neural Science
David Poeppel: Max-Planck-Institute for Empirical Aesthetics

Nature Communications, 2019, vol. 10, issue 1, 1-13

Abstract: Abstract Humans anticipate events signaled by sensory cues. It is commonly assumed that two uncertainty parameters modulate the brain's capacity to predict: the hazard rate (HR) of event probability and the uncertainty in time estimation which increases with elapsed time. We investigate both assumptions by presenting event probability density functions (PDFs) in each of three sensory modalities. We show that perceptual systems use the reciprocal PDF and not the HR to model event probability density. We also demonstrate that temporal uncertainty does not necessarily grow with elapsed time but can also diminish, depending on the event PDF. Previous research identified neuronal activity related to event probability in multiple levels of the cortical hierarchy (sensory (V4), association (LIP), motor and other areas) proposing the HR as an elementary neuronal computation. Our results—consistent across vision, audition, and somatosensation—suggest that the neurobiological implementation of event anticipation is based on a different, simpler and more stable computation than HR: the reciprocal PDF of events in time.

Date: 2019
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DOI: 10.1038/s41467-019-13849-0

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