Disentangling negative reinforcement, working memory, and deductive reasoning deficits in elevated BMI

Abstract

Neuropsychological data suggest that being overweight or obese is associated with a tendency to perseverate behavior despite negative feedback. This deficit might be observed due to other cognitive factors, such as working memory (WM) deficits or decreased ability to deduce model-based strategies when learning by trial-and-error. In the present study, a group of subjects with overweight or obesity (Ow/Ob, n = 30) was compared to normal-weight individuals (n = 42) in a modified Reinforcement Learning (RL) task. The task was designed to control WM effects on learning by manipulating cognitive load and to foster model-based learning via deductive reasoning. Computational modelling and analysis were conducted to isolate parameters related to RL mechanisms, WM use, and model-based learning (deduction parameter). Results showed that subjects with Ow/Ob had a higher number of perseverative errors and used a weaker deduction mechanism in their performance than control individuals, indicating impairments in negative reinforcement and model-based learning, whereas WM impairments were not responsible for deficits in RL. The present data suggests that obesity is associated with impairments in negative reinforcement and model-based learning.