Adaptive Engagement of Cognitive Control in Context-Dependent Decision Making

Many decisions require a context-dependent mapping from sensory evidence to action. The capacity for flexible information processing of this sort is thought to depend on a cognitive control system in frontoparietal cortex, but the costs and limitations of control entail that its engagement should be minimized. Here, we show that humans reduce demands on control by exploiting statistical structure in their environment. Using a context-dependent perceptual discrimination task and model-based analyses of behavioral and neuroimaging data, we found that predictions about task context facilitated decision making and that a quantitative measure of context prediction error accounted for graded engagement of the frontoparietal control network. Within this network, multivariate analyses further showed that context prediction error enhanced the representation of task context. These results indicate that decision making is adaptively tuned by experience to minimize costs while maintaining flexibility.