Beyond the average: The role of variable reward sensitivity in eating disorders

•Eating is characterized by variability in energy intake.•Sensitivity to food reward guides non-homeostatic eating.•Reward sensitivity as distribution over different states incorporates variability.•Quantitative modeling frameworks provide measures of variability.•Eating disorders might be associate...

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Veröffentlicht in:Physiology & behavior 2020-09, Vol.223, p.112971-112971, Article 112971
Hauptverfasser: Neuser, Monja P., Kühnel, Anne, Svaldi, Jennifer, Kroemer, Nils B.
Format: Artikel
Sprache:eng
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Zusammenfassung:•Eating is characterized by variability in energy intake.•Sensitivity to food reward guides non-homeostatic eating.•Reward sensitivity as distribution over different states incorporates variability.•Quantitative modeling frameworks provide measures of variability.•Eating disorders might be associated with variability in reward sensitivity. Eating disorders are often characterized by episodes of overeating and undereating. To date, most theories have explained the liability for such episodes by differences in traits such as reward sensitivity or cognitive control. Here, we review the evidence for a more parsimonious account of the waxing and waning in food intake by linking it to state-like variability of alleged traits such as reward sensitivity. To formally demonstrate that our variability model of eating disorders could explain a wide range of observed reward-related behavior, we conducted simulations of value-based choices and learning. These simulations based on well-established computational models of reinforcement learning and Bayesian sequential updating show how variability may arise and manifest in eating behavior. We argue that by reconceptualizing stable traits as distributions over likely states promoting adaptation, our proposed model integrates disparate findings and leads to novel predictions in a quantitative framework. Collectively, these emerging results call for a stronger emphasis on within-person variability to improve mechanistic insights into eating disorders.
ISSN:0031-9384
1873-507X
DOI:10.1016/j.physbeh.2020.112971