Reference Point-Dependent Reinforcement Learning in Humans and Rats

Rewards and punishments in reinforcement learning are encoded in both absolute and relative manners. Reference-point dependence, a valuation bias shared by adaptation-level and prospect theories, is often proposed as the computational mechanism underlying relative value encoding. However, the extent to which these behavioural and computational mechanisms are preserved across species is unclear. We therefore designed parallel reinforcement learning tasks in humans and rats to examine reference-point dependence across species. Behavioural analyses indicated robust relative value encoding in both species and computational modelling confirmed that reference-point dependence provides a reliable account of reinforcement learning behaviour in humans and rats. Despite these major similarities between species, some differences in behavioural and modelling parameters were observed. Overall, our study demonstrates that relative value encoding is a robust, conserved feature of reinforcement learning that is conserved across human and rat species.