Dissociable influences of reward and punishment on adaptive cognitive control

Abstract

When 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 achieve task goals. 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 reward (primarily adjusting drift rate) versus punishment (primarily 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 infer the motivational salience of positive versus negative incentives for a given individual. These results provide a normative and mechanistic account for how reward and punishment differentially influence the adaptive allocation of cognitive control.

Humans reconfigure target and distractor processing to address distinct task demands

“…Together, these results support a cognitive control architecture that is parametric, multivariate, and dynamic. Previous research has found that cognitive effort is enhanced in response to incentives (Hübner & Schlösser, 2010; Leng, Yee, Ritz, & Shenhav, 2020; Padmala & Pessoa, 2011; Parro, Dixon, & Christoff, 2018) and to prior conflict (Egner, 2007; Gratton et al, 1992). The current experiments extend these previous findings to show that these adaptations are both graded in their intensity, and selective in the allocation.…”

Decomposing the Motivation to Exert Mental Effort

“…The EVC model offers a potential explanation for these apparent inconsistencies: The value of potential outcomes can signal the need to adjust both how much and what kind of control to engage. A recent study from our lab tested the model’s prediction that different types of control can be adaptive depending on the relative incentives for achieving correct responses and avoiding incorrect responses (Leng et al, 2020). Participants were allowed to complete as many trials of the assigned task as they wanted within a fixed period of time, so they had the freedom to choose how much to emphasize speed and accuracy.…”

Aversive Motivation and Cognitive Control

“…Lastly, while we acknowledge that these paradigms are certainly not exhaustive, our hope is that consideration of these motivational dimensions will provide a broad foundation to inspire future research that will clarify the specific and nuanced ways through which aversive motivational value interacts with cognitive control. (Leng et al, 2020), such that they were rewarded with monetary gains for correct responses and were penalized with monetary losses for incorrect responses. The motivational value of the rewards and penalties were varied, which enabled clear dissociation between how expected rewards increased response rate (via faster response times while maintaining accuracy) and expected penalties decreased response rate (via slower response times and increased accuracy).…”

“…Another approach to examining the effect of aversive incentives on cognitive control would be to examine the dissociable, rather than integrated, influence of multiple incentives on cognitive control. Our group recently developed a novel task that examines how expected rewards and penalties influence the allocation of cognitive control on a self-paced Stroop task (Leng et al, 2020). Specifically, in contrast to previous studies that have primarily measured motivation in terms of performance on a fixed number of obligatory task trials, this task contains fixed time intervals through which a person can choose how much effort to invest based upon the expected rewards for success and penalties for failure (Schmidt et al, 2012).…”

“…However, while these current results lend support for how mixed motivation (i.e., bundled incentives) may modulate cognitive control via an instrumental manner, it remains unknown how this integrated value signal may differentially impact cognitive control when incentives are conditioned in Pavlovian or even combined (e.g., Pavlovian-Instrumental Transfer) manner. Future studies could explicitly examine the relative impact of bundled aversive incentives (e.g., monetary loss + saltwater) against bundled rewarding and aversive incentives (e.g., monetary loss + juice) on cognitive control, or alternatively consider the motivational context of incentives examine the degree to which different neural signals within dACC may underlie how rewarding vs. aversive incentives influence dissociable strategies for allocating cognitive control (Leng et al, 2020).…”