Rules for aversive learning and decision-making

Associative and reinforcement learning rules describe how animals, including humans, predict events in the world. In aversive learning, these rules describe how we predict danger. Here we outline major associative and reinforcement rules for aversive learning as well as behavioural approaches to study them. We identify key findings from the emerging literature on how these different learning rules are instantiated in the mammalian brain. We also highlight key areas where understanding is lacking and more research is needed. Finally, we consider how these learning rules not only help solve the problem of predicting danger but also provide a theoretical and empirical basis for understanding aversive decision-making.