I. Louren�o, R. Mattila, R. Ventura and B. Wahlberg, A Biologically Inspired Computational Model of Time Perception, IEEE Transactions on Cognitive and Developmental Systems, vol. 14, no. 2, pp. 258-268, June 2022 DOI: 10.1109/TCDS.2021.3120301.
Time perception\u2014how humans and animals perceive the passage of time\u2014forms the basis for important cognitive skills, such as decision making, planning, and communication. In this work, we propose a framework for examining the mechanisms responsible for time perception. We first model neural time perception as a combination of two known timing sources: internal neuronal mechanisms and external (environmental) stimuli, and design a decision-making framework to replicate them. We then implement this framework in a simulated robot. We measure the robot\u2019s success on a temporal discrimination task originally performed by mice to evaluate their capacity to exploit temporal knowledge. We conclude that the robot is able to perceive time similarly to animals when it comes to their intrinsic mechanisms of interpreting time and performing time-aware actions. Next, by analyzing the behavior of agents equipped with the framework, we propose an estimator to infer characteristics of the timing mechanisms intrinsic to the agents. In particular, we show that from their empirical action probability distribution, we are able to estimate parameters used for perceiving time. Overall, our work shows promising results when it comes to drawing conclusions regarding some of the characteristics present in biological timing mechanisms.
NOTE: See also H. Basgol, I. Ayhan and E. Ugur, “Time Perception: A Review on Psychological, Computational, and Robotic Models,” in IEEE Transactions on Cognitive and Developmental Systems, vol. 14, no. 2, pp. 301-315, June 2022, doi: 10.1109/TCDS.2021.3059045.