Dissociable influences of reward and punishment on adaptive cognitive control
- Xiamin Leng, Brown University, Providence, Rhode Island, United States
- Harrison Ritz, Brown University, Providence, Rhode Island, United States
- Debbie Yee, Brown University, Providence, Rhode Island, United States
- Amitai Shenhav, Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, Rhode Island, United States
AbstractWhen deciding how to allocate cognitive control to a given task, people must consider both positive outcomes (e.g., praise) and negative outcomes (e.g., admonishment). However, it is unclear how these two forms of incentives differentially influence the amount and type of cognitive control a person chooses to allocate. To address this question, we had participants perform a self-paced incentivized cognitive control task, varying the magnitude of reward for a correct response and punishment for an incorrect response. Formalizing control allocation as a process of adjusting parameters of a drift diffusion model (DDM), we show that participants engaged in different strategies in response to variability in reward (adjusting drift rate) versus punishment (adjusting response threshold). We demonstrate that this divergent set of strategies is optimal for maximizing reward rate while minimizing effort costs. Finally, we show that these dissociable patterns of behavior enable us to estimate the motivational salience of positive versus negative incentives for a given individual.