Biased choice and incentive salience: Implications for addiction.
Mike E Le PelleyPoppy WatsonReinout W WiersPublished in: Behavioral neuroscience (2024)
Before we can make any choice, we must gather information from the environment about what our options are. This information-gathering process is critically mediated by attention, and our attention is, in turn, shaped by our previous experiences with-and learning about-stimuli and their consequences. In this review, we highlight studies demonstrating a rapid and automatic influence of reward learning on attentional capture and argue that these findings provide a human analog of sign-tracking behavior observed in nonhuman animals-wherein signals of reward gain incentive salience and become attractive targets for attention (and overt behavior) in their own right. We then consider the implications of this idea for understanding the drivers of cue-controlled behavior, with focus on addiction as a case in which choices with regard to reward-related stimuli can become injurious to health. We argue that motivated behavior in general-and addiction in particular-can be understood within a "biased competition" framework: Different options and outcomes compete for attentional priority as a function of top-down goals, bottom-up salience, and prior experience, and the winner of this competition becomes the target for subsequent outcome-directed and flexible behavior. Finally, we outline the implications of the biased-competition framework for cognitive, behavioral, and socioeconomic interventions for addiction. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Keyphrases
- working memory
- functional connectivity
- public health
- endothelial cells
- health information
- physical activity
- emergency department
- deep learning
- machine learning
- metabolic syndrome
- insulin resistance
- sensitive detection
- decision making
- social media
- global health
- weight loss
- quantum dots
- risk assessment
- glycemic control