How are overweight and obesity associated with reinforcement learning deficits? A systematic review

Reinforcement learning (RL) refers to the ability to learn stimulus-response or response-outcome associations relevant to the acquisition of behavioral repertoire and adaptation to the environment. Research data from correlational and case-control studies have shown that obesity is associated with impairments in RL. The aim of the present study was to systematically review how obesity and overweight are associated with RL performance. More specifically, the relationship between high body mass index (BMI) and task performance was explored through the analysis of specific RL processes associated with different physiological, computational, and behavioral manifestations. Our systematic analyses indicate that obesity might be associated with impairments in the use of aversive outcomes to change ongoing behavior, as revealed by results involving instrumental negative reinforcement and extinction/reversal learning, but further research needs to be conducted to confirm this association. Hypotheses regarding how obesity might be associated with altered RL were discussed.

Automated summary

This study systematically reviewed the association between obesity and overweight with reinforcement learning performance. It was found that obesity might be associated with impairments in utilizing aversive outcomes to change behavior, but further research is needed to confirm this association.