Dynamic decision making in predatory pursuit of mice

Abstract

Most animals must reserve their limited intelligence for the most important situations, such as predation and escape, in order to have a better chance of survival. As a highly sequentially programmed behavior driven by innate desire, one of the most challenging parts of predation is how the predator can pursue and capture an escaping prey that is also running for its own survival. This requires the predator to synthesize environmental and prey information to make dynamic decisions in real time to guide appropriate behavior. However, it is still largely unclear whether and how mice can cope with such challenge. Here, we developed a real-time interactive platform to study the pursuit behavior during predation in rodents. An artificial prey was magnetically controlled by a closed-loop system that attempts to escape an approaching predator (e.g., a hungry mouse) in real time. By recording the time costs, trajectories and other parameters of both predator and prey, we found that not only were the mice able to complete predation tasks of varying difficulty, but that they could also improve their predation efficiency over trials, mainly due to the improvements in the pursuit phase. Further investigation revealed that the increase in pursuit performance may not entirely achieved by physical improvement, but rather by optimization of velocity control as well as a change of navigation strategy. In conclusion, this study reveals that mice are capable of making dynamic decisions during predatory pursuit, and the transition from novice to veteran can be used to study the biological mechanisms of dynamic decision making in mice.