Word and deed: A computational model of instruction following

Instructions are an inextricable, yet poorly understood aspect of modern human life. In this paper we propose that instruction implementation and following can be understood as fast Hebbian learning in prefrontal cortex, which trains slower pathways (e.g., cortical–basal ganglia pathways). We present a computational model of instruction following that is used to simulate key behavioral and neuroimaging data on instruction following. We discuss the relationship between our model and other models of instruction following, the predictions derived from it, and directions for future investigation.

► We propose a model of how people rapidly encode and implement instructions. ► The model is based on a computational tradeoffs framework and has Hebbian learning at its core. ► It is shown to be consistent with both behavioral and neuroimaging data on instruction following.