A Drift Diffusion Model of Proactive and Reactive Control in a Context-Dependent Two-Alternative Forced Choice Task

Most of our everyday decisions rely crucially on context: foraging for food in the fridge may be appropriate at home, but not at someone else’s house. Yet the mechanism by which context modulates how we respond to stimuli remains a topic of intense investigation. In order to isolate such decisions experimentally, investigators have employed simple context-based decision-making tasks like the AX-Continuous Performance Test (AX-CPT). In this task, the correct response to a probe stimulus depends on a cue stimulus that appeared several seconds earlier. It has been proposed (Braver, 2007) that humans might employ two strategies to perform this task: one in which rule information is proactively maintained in working memory, and another one in which rule information is retrieved reactively at the time of probe onset. While this framework has inspired considerable investigation, it has not yet been committed to a formal model. Such a model would be valuable for testing quantitative predictions about the influence of proactive and reactive strategies on choice and reaction time behavior. To this end, we have built a drift diffusion model of behavior on the AX-CPT, in which evidence accumulation about a stimulus is modulated by context. We implemented proactive and reactive strategies as two distinct models: in the proactive variant, perception of the probe is modulated by the remembered cue; in the reactive variant, retrieval of the cue from memory is modulated by the perceived probe. Fitting these models to data shows that, counter-intuitively, behavior taken as a signature of reactive control is better fit by the proactive variant of the model, while proactive profiles of behavior are surprisingly better fit by the reactive variant. We offer possible interpretations of this result, and use simulations to suggest experimental manipulations for which the two models make divergent predictions.