# Extensive drug histories result in compulsive appetite: functional identification of punishment-reactive neural network re-organization in the rostromedial tegmental nucleus > **NIH NIH U01** · SCRIPPS RESEARCH INSTITUTE, THE · 2023 · $534,381 ## Abstract PROJECT SUMMARY Binge-eating disorder (BED) and bulimia nervosa (BN) are potentially life-threatening eating disorders that share behavioral and brain similarities, genetic risk factors and higher-than-expected comorbidities with drug addiction – suggesting a common etiology. However, no mechanistic study has examined this possibility due in part to the lack of an animal model linking eating disorders and drug addiction. Like drug craving and use in drug addiction, food craving and eating in BED/BN persist despite adverse consequences (punishment). Our finding from rats indicates that extensive cocaine and alcohol histories, known to trigger addiction-like brain changes and punishment-resistant “compulsive” drug intake in rats, trigger punishment-resistant food intake or “compulsive appetite”. These results provide an animal model for studying the neurobiological mechanisms manifesting as compulsive behavior across eating disorders and drug addiction. Food motivation is thought to be regulated by both homeostatic (caloric) and non-homeostatic (hedonic/incentive) systems. The homeostatic system detects energy shortages and elicits food intake. However, like compulsive drug motivation, our finding suggests that compulsive appetite is driven by non-homeostatic ‘motivational/habitual’ dysregulation. Like cocaine and alcohol histories, obesogenic diet histories also led to compulsive appetite via non-homeostatic dysregulation. Thus, similarly common – rather than history-specific – changes in brain sites that control non- homeostatic regulation, such as reward circuits, likely cause compulsive appetite. Our collaborator Dr. Jhou’s group has found that punishments suppress appetitive behavior by recruiting neurons in the rostromedial tegmental nucleus (RMTg), which in turn inhibits reward circuits. Available evidence indicates that extensive drug histories [1] degrade excitatory afferents to RMTg, [2] decrease punishment-reactivity of RMTg neurons and [3] impair inhibitory control of RMTg efferents on reward circuits. Such brain changes would entail “less brakes” on non-homeostatic regulation, potentially manifesting as compulsive appetite. Accordingly, like extensive cocaine/alcohol/obesogenic diet histories, [4] RMTg inactivation results in punishment-resistant compulsive appetite. Based on the rigor of previous research and premise above, this project will test the central hypothesis that extensive cocaine/alcohol/obesogenic diet histories result in punishment-resistant compulsive appetite via decreased neural punishment-reactivity in the RMTg circuitry. RMTg contains neurons selectively reactive to punishments or rewards – likely exerting distinct behavioral functions. Each Aim is thus designed to selectively profile and interrogate punishment-reactive RMTg neurons/afferents/efferents (as Aims 1/2/3) using neural activity-specific methods based on the activation marker Fos. The results will reveal neural activity network reorganizations that are fu... ## Key facts - **NIH application ID:** 10693347 - **Project number:** 5U01DA055017-02 - **Recipient organization:** SCRIPPS RESEARCH INSTITUTE, THE - **Principal Investigator:** Nobuyoshi Suto - **Activity code:** U01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2023 - **Award amount:** $534,381 - **Award type:** 5 - **Project period:** 2022-09-01 → 2024-04-26 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10693347 ## Citation > US National Institutes of Health, RePORTER application 10693347, Extensive drug histories result in compulsive appetite: functional identification of punishment-reactive neural network re-organization in the rostromedial tegmental nucleus (5U01DA055017-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10693347. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*