Foundational studies in decision making focused on behavior as the most accessible and reliable data on which to build theories of choice. More recent work, however, has incorporated neural data to provide insights unavailable from behavior alone. Among other contributions, these studies have validated reinforcement learning models by…

Excessively devaluing delayed reinforcers co-occurs with a wide variety of clinical conditions such as drug dependence, obesity, and excessive gambling. If excessive delay discounting is a trans-disease process that underlies the choice behavior leading to these and other negative health conditions, efforts to change an individual's discount rate…

This article presents an interpretation of autoshaping, and positive and negative automaintenance, based on a neural-network model. The model makes no distinction between operant and respondent learning mechanisms, and takes into account knowledge of hippocampal and dopaminergic systems. Four simulations were run, each one using an "A-B-A" design…