ReviewObesity (Silver Spring, Md.)2023
Food reinforcement architecture: A framework for impulsive and compulsive overeating and food abuse.
Review in Obesity (Silver Spring, Md.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Restriction spectrum imaging reveals brain microstructural correlates of obesity risk in early childhood.Scientific reports · 2026Article
- When tasty becomes threatening: a neurobehavioral perspective on subjective food preferences in eating disorders.Frontiers in psychology · 2026Review
- Article
- Children's satiety responsiveness moderates the association between food reinforcement and eating in the absence of hunger.Physiology & behavior · 2025Article
- Brain Microstructure and Obesity Risk in Early Childhood: Insights from Restriction Spectrum Imaging.bioRxiv : the preprint server for biology · 2025Article
- Appetite Self-Regulation in Childhood: A Narrative Review and Conceptual Model of Processes and Mechanisms With Implications for Research and Practice.Nutrition reviews · 2025Review
- Mendelian Randomization Analysis Identifies Inverse Causal Relationship between External Eating and Metabolic Phenotypes.Nutrients · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.