Mice can count and optimize count-based decisions.

Previous studies showed that rats and pigeons can count their responses, and the resultant count-based judgments exhibit the scalar property (also known as Weber's Law), a psychophysical property that also characterizes interval-timing behavior. Animals were found to take a nearly normative account of these well-established endogenous uncertainty characteristics in their time-based decision-making. On the other hand, no study has yet tested the implications of scalar property of numerosity representations for reward-rate maximization in count-based decision-making. The current study tested mice on a task that required them to press one lever for a minimum number of times before pressing the second lever to collect the armed reward (fixed consecutive number schedule, FCN). Fewer than necessary number of responses reset the response count without reinforcement, whereas emitting responses at least for the minimum number of times reset the response counter with reinforcement. Each mouse was tested with three different FCN schedules (FCN10, FCN20, FCN40). The number of responses emitted on the first lever before pressing the second lever constituted the main unit of analysis. Our findings for the first time showed that mice count their responses with scalar property. We then defined the reward-rate maximizing numerical decision strategies in this task based on the subject-based estimates of the endogenous counting uncertainty. Our results showed that mice learn to maximize the reward-rate by incorporating the uncertainty in their numerosity judgments into their count-based decisions. Our findings extend the scope of optimal temporal risk-assessment to the domain of count-based decision-making.