Reduced sensitivity but intact motivation to monetary rewards and reversal learning in obesity

• Published in: Addictive behaviors Vol. 140; p. 107599
• Main Authors: Isıklı, Serhan, Bahtiyar, Gökhan, Zorlu, Nabi, Düsmez, Selin, Bağcı, Başak, Bayrakcı, Adem, Heinz, Andreas, Sebold, Miriam
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.05.2023
• Subjects: Computational psychiatry; Decision Making; Effort; Humans; Motivation; Obesity; Reinforcement learning; Reversal Learning; Reward; Obesity; Computational psychiatry; Reward; Decision making; Reinforcement learning; Effort
• ISSN: 0306-4603; 1873-6327
• DOI: 10.1016/j.addbeh.2022.107599

•Obesity has been linked to reward processing deficits.•Subdomains of reward processing were examined.•Reward motivation and learning seem to be intact in obesity.•Hyposensitivity to non-food rewards was found in obese subjects. Obesity has been linked to altered reward processing but little is known about which components of reward processing including motivation, sensitivity and learning are impaired in obesity. We examined whether obesity compared to healthy weight controls is associated with differences in distinct subdomains of reward processing. To this end, we used two established paradigms, namely the Effort Expenditure for Rewards task (EEfRT) and the Probabilistic Reversal Learning Task (PRLT). 30 individuals with obesity (OBS) and 30 healthy weight control subjects (HC) were included in the study. Generalized estimating equation models were used to analyze EEfRT choice behavior. PRLT data was analyzed using both conventional behavioral variables of choices and computational models. Our findings from the different tasks speak in favor of a hyposensitivity to non-food rewards in obesity. OBS did not make fewer overall hard task selections compared to HC in the EEfRT suggesting generally intact non-food reward motivation. However, in highly rewarding trials (i.e.,trials with high reward magnitude and high reward probability),OBSmadefewer hard task selections compared to normal weight subjects suggesting decreased sensitivity to highly rewarding non-food reinforcers. Hyposensitivity to non-food rewards was also evident in OBS in the PRLT as evidenced by lower win-stay probability compared to HC. Our computational modelling analyses revealed decreased stochasticity but intact reward and punishment learning rates in OBS. Our findings provide evidence for intact reward motivation and learning in OBS but lower reward sensitivity which is linked to stochasticity of choices in a non-food context. These findings might provide further insight into the mechanism underlying dysfunctional choices in obesity.