Food reinforcement architecture: A framework for impulsive and compulsive overeating and food abuse

Abstract

Few reward‐based theories address key drivers of susceptibility to food cues and consumption beyond fullness. Decision‐making and habit formation are governed by reinforcement‐based learning processes that, when overstimulated, can drive unregulated hedonically motivated overeating. Here, a model food reinforcement architecture is proposed that uses fundamental concepts in reinforcement and decision‐making to identify maladaptive eating habits that can lead to obesity. This model is unique in that it identifies metabolic drivers of reward and incorporates neuroscience, computational decision‐making, and psychology to map overeating and obesity. Food reinforcement architecture identifies two paths to overeating: a propensity for hedonic targeting of food cues contributing to impulsive overeating and lack of satiation that contributes to compulsive overeating. A combination of those paths will result in a conscious and subconscious drive to overeat independent of negative consequences, leading to food abuse and/or obesity. Use of this model to identify aberrant reinforcement learning processes and decision‐making systems that can serve as markers of overeating risk may provide an opportunity for early intervention in obesity.

Ultraprocessed Foods at Home and Children's Attentional Bias Toward Those Foods

“…Through cue-reward reinforcement learning processes, this may establish attentional biases toward ultraprocessed foods. It has been posited that propensity for this type of food cue–reward learning contributes to impulsive eating (ie, frequent food cue–potentiated consumption) and thus increases risk for excess weight gain . This risk for weight gain may be amplified by additional aberrant eating patterns (eg, delayed satiation) .…”

“…It has been posited that propensity for this type of food cue–reward learning contributes to impulsive eating (ie, frequent food cue–potentiated consumption) and thus increases risk for excess weight gain . This risk for weight gain may be amplified by additional aberrant eating patterns (eg, delayed satiation) . Limitations include the cross-sectional nature of the study and self-reported measures of the home food environment.…”

Mendelian Randomization Analysis Identifies Inverse Causal Relationship between External Eating and Metabolic Phenotypes

“…Additionally, a concept related to eating behaviour known as food reinforcement explores how much effort an individual is willing to exert to obtain tasty food [ 4 ]. Research indicates that there are individual differences, with obese individuals showing a greater incidence of food addiction and greater attachment to food than non-obese individuals [ 5 ].…”