Generalization of prior information for rapid Bayesian time estimation

Significance When sensory information is uncertain, humans rely on prior knowledge of the environment when making perceptual judgments and planning actions. Humans can rapidly learn new priors, but the rules governing how recent experiences are grouped together are unknown. Here, we show that observers initially form single priors by generalizing across distinct sensory signals but form multiple priors when they are coupled with different motor outputs. Thus, our results reveal that internal models of temporal statistics are initially organized not according to the nature of the sensory input but according to the way on which it is acted. To enable effective interaction with the environment, the brain combines noisy sensory information with expectations based on prior experience. There is ample evidence showing that humans can learn statistical regularities in sensory input and exploit this knowledge to improve perceptual decisions and actions. However, fundamental questions remain regarding how priors are learned and how they generalize to different sensory and behavioral contexts. In principle, maintaining a large set of highly specific priors may be inefficient and restrict the speed at which expectations can be formed and updated in response to changes in the environment. However, priors formed by generalizing across varying contexts may not be accurate. Here, we exploit rapidly induced contextual biases in duration reproduction to reveal how these competing demands are resolved during the early stages of prior acquisition. We show that observers initially form a single prior by generalizing across duration distributions coupled with distinct sensory signals. In contrast, they form multiple priors if distributions are coupled with distinct motor outputs. Together, our findings suggest that rapid prior acquisition is facilitated by generalization across experiences of different sensory inputs but organized according to how that sensory information is acted on.