The Temporal Dynamics of Reward-Based Goal-Directed Decision-Making

Abstract This chapter reviews recent work on computational models describing the temporal dynamics of reward-based goal-directed decision-making, from a conceptual rather than technical perspective. Models of temporal dynamics make predictions about the time course and duration of deliberation in addition to the choices that people make. We begin by reviewing the simple one-step choice decision situation and the idea of evidence integration, a core feature of dynamic models, within the context of the drift-diffusion model. We then present more recent extensions of the evidence integration perspective to decisions that span more than one time step.