# Probability estimation by mice in an interval timing task

- Aaron Kheifets,
*Rutgers University Center for Cognitive Science: RUCCS*
- C. Randy Gallistel,
*Rutgers University Center for Cognitive Science: RUCCS*

## Abstract

Keeping track of and detecting changes in the probability of
events is a central problem for animals. We presented mice with an interval
timing task: with probability p, mice were reinforced for staying at the first
hopper until time t. With complementary probability 1-p they were reinforced for
arriving at the second hopper before t+k. Because no animals are perfect timers,
this task was difficult due to small k. Depending on p, the optimal switch point
changed: if long trials were more likely, switching too late became more costly
than switching too early, so the optimal switch time occurred later. Subjects
showed highly significant (p<0.005) differences in their mean switch times
when p was manipulated. Moreover, subjects were able to update their frequency
estimates when the underlying probabilities of trial types changed and their
estimates converged on accurate values quickly in comparison to plausible
Bayesian optimal models.

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