A neural circuit model for human sensorimotor timing

Abstract

Humans can rapidly and flexibly coordinate their movements with external stimuli. Theoretical considerations suggest that this flexibility can be understood in terms of how sensory responses reconfigure the neural circuits that control movements. However, because external stimuli can occur at unexpected times, it is unclear how the corresponding sensory inputs can be used to exert flexible control over the ongoing activity of recurrent neural circuits. Here, we tackle this problem in the domain of sensorimotor timing and develop a circuit-level model that provides insight into how the brain coordinates movement times with expected and unexpected temporal events. The model consists of two interacting modules, a motor planning module that controls movement times and a sensory anticipation module that anticipates external events. Both modules harbor a reservoir of latent dynamics and their interaction forms a control system whose output is adjusted adaptively to minimize timing errors. We show that the models output matches human behavior in a range of tasks including time interval production, periodic production, synchronization/continuation, and Bayesian time interval reproduction. These results demonstrate how recurrent interactions in a simple and modular neural circuit could create the dynamics needed to control temporal aspects of behavior.