Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing.

ABSTRACT: Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. In

SUBMITTER: Acerbi L 

PROVIDER: S-EPMC3510049 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature