Testing the state-dependent model of time perception against experimental evidence

Abstract

AbstractCoordinated movements, speech and other actions are impossible without precise timing. Computational models of interval timing are expected to provide key insights into the underlying mechanisms of timing, which are currently largely unknown. However, existing models have only been partially replicating key experimental observations, such as the linear increase of time, the dopaminergic modulation of this increase, and the scalar property, i.e., the linear increase of the standard deviation of temporal estimates. In this work, we incorporate the state-dependent model of time perception, which encodes time in the dynamic evolution of network states without the need for a specific network structure into a strongly data-driven prefrontal cortex (PFC). We show that this model variant, termed the state-dependent PFC model, successfully encodes time over several hundreds of milliseconds and reproduces all of the experimental results mentioned above. Furthermore, we propose a theory for the mechanism underlying time perception in this model, based on correlation and ablation studies as well as mathematical analyses. We show the representations of different intervals are based on the natural heterogeneity in the parameters of the network leading to stereotype responses of subsets of neurons to a stimulus at the end of each interval to be represented. The theory explains both the emergence of the scalar property of timing errors and of Vierordt’s law, the fact that subjective duration is overestimated for short and underestimated for longer intervals. Overall, the state-dependent PFC model constitutes the first model of time perception in the range of hundreds of milliseconds that has been thoroughly tested against a variety of experimental data. As such, it provides an ideal starting point for further investigations of the mechanism of time perception.Author summaryAn accurate representation of time is crucial for a wide range of sensory, motor and cognitive tasks. Despite this importance, there is currently no commonly accepted theory for the mechanisms of time perception, although a wide range of modelling approaches exists. A possible reason for this discrepancy may be the fact that none of the existing models have been thoroughly tested against recurring experimental findings of time perception, such as the linear increase of subjective durations (psychophysical law) and timing errors (Weber’s law) with objective duration and the manipulation of subjective duration by dopamine. Here, we attempt to test one of the established models of time perception in this manner, namely the state-dependent model. We implement this model within a strongly data-driven network model of the prefrontal cortex and show that all the above-mentioned experimental findings are reproduced within a limited range of durations. We also offer a theoretical account for understanding the mechanisms underlying time perception in this model, with a focus on the emergence of Weber’s law. Overall, the state-dependent PFC model represents the first model of time perception in the range of hundreds of milliseconds that reproduces the most prominent experimental findings of time perception.