Dissociable influences of reward and punishment on adaptive cognitive control

Abstract

To invest effort into any cognitive task, people must be sufficiently motivated. Whereas prior research has focused primarily on how the cognitive control required to complete these tasks is motivated by the potential rewards for success, it is also known that control investment can be equally motivated by the potential negative consequence for failure. Previous theoretical and experimental work has yet to examine how positive and negative incentives differentially influence the manner and intensity with which people allocate control. Here, we develop and test a normative model of control allocation under conditions of varying positive and negative performance incentives. Our model predicts, and our empirical findings confirm, that rewards for success and punishment for failure should differentially influence adjustments to the evidence accumulation rate versus response threshold, respectively. This dissociation further enabled us to infer how motivated a given person was by the consequences of success versus failure.

Orthogonal neural encoding of targets and distractors supports multivariate cognitive control

“…This flexibility is enabled by the array of mental tools we can bring to bear on challenges to our goal pursuit (Badre et al, 2021; Danielmeier and Ullsperger, 2011; Egner, 2008; Ritz et al, 2022a). For example, someone may respond to a mistake by becoming more cautious, enhancing task-relevant processing, or suppressing task-irrelevant processing (Danielmeier and Ullsperger, 2011), and previous work has shown that people simultaneously deploy multiple such strategies at the same time in response to different task demands (Danielmeier et al, 2011; Fischer et al, 2018; Leng et al, 2021; Ritz and Shenhav, 2021). While the breadth of these control adjustments and the conditions under which they occur have become increasingly clear, how we achieve this level of coordination remains largely mysterious.…”

Mapping the dose–response relationship between monetary reward and cognitive performance.

“…Experiments 1a and 1b provide a first examination of the dose–response relationship between reward value and task-switching performance. Experiment 1a uses a gain frame and Experiment 1b a loss frame (as gains vs. losses may trigger different speed–accuracy tradeoffs; Leng et al, 2021), but are otherwise identical. Experiment 2 examines whether the presence of physical reward cues changes the shape of the relationship between reward value and cognitive performance.…”

Strategically managing learning during perceptual decision making

“…Future modeling work should make the choice of control explicit, taking into account the inherent cost of control ( Shenhav et al, 2013 ), and then using that choice to determine the decision threshold. Doing so would allow control to not only reflect the choice of threshold, as we have done, but also as a gain term on the drift rate ( Leng et al, 2021 ), which may more completely capture control’s role in two-choice decisions.…”