Temporal foreknowledge: Anticipation and prospective correction of timing errors by diffusion.

Abstract

A recent line of research has shown that humans and rodents can monitor errors in their timing behavior in individual trials. This ability is called temporal error monitoring (TEM). Electrophysiological studies showed that TEM-related neural signals of error are present before the timing behavior is manifested. These results have crucial implications for the function and modeling of TEM as they show that timing errors are read out rather than detected retrospectively. Such real-time error monitoring allows emergent timing error signals to improve the impending timing behavior in a prospective fashion (e.g., increasing the timing threshold when "earlier-than-target" errors are detected), enabling within-trial error corrections. In this article, we present a drift-diffusion model of real-time TEM with prospective (within-trial) behavioral modulation/refinement elements that are sensitive to task representations. Our model predicts the read-out of timing signals before the manifestation of the timing behavior and the translation of these signals into the improvement of timing accuracy within individual trials (thus improving overall precision) without violating the psychophysical and statistical features of the timing behavior. Finally, the task representation dependency of the decision element accounts for the widely reported reward-rate maximizing timing behavior. Our model introduces a new theoretical foundation for TEM with many testable behavioral and electrophysiological predictions. (PsycInfo Database Record (c) 2025 APA, all rights reserved).