期刊
JOURNAL OF NEUROSCIENCE
卷 39, 期 6, 页码 1077-1087出版社
SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.1596-18.2018
关键词
alcohol use disorder; anterior insular cortex; context; iP rat; punishment; relapse
资金
- National Health and Medical Research Council [1105741, 1116930]
- University of Melbourne Early Career Researcher Grant Scheme
- National Health and Medical Research Council of Australia [1105741] Funding Source: NHMRC
Humans with alcohol use disorder typically abstain because of the negative consequences associated with excessive drinking, and exposure to contexts previously associated with alcohol use can trigger relapse. We used a rat model that captures a characteristic of this human condition: namely voluntary abstinence from alcohol use because of contingent punishment. There is substantial variability in the propensity to relapse following extended periods of abstinence, and this is a critical feature preventing the successful treatment of alcohol use disorder. Here we examined relapse following acute or prolonged abstinence. In male alcohol preferring P rats, we found an increased propensity to relapse in Context B, the punishment context after prolonged abstinence. Next, we found that neither alcohol intake history nor the motivational strength of alcohol predicted the propensity to relapse. We next examined the putative circuitry of context-induced relapse to alcohol seeking following prolonged abstinence using Fos as a marker of neuronal activation. The anterior insular cortex (AI) was the only brain region examined where Fos expression correlated with alcohol seeking behavior in Context B after prolonged abstinence. Finally, we used local infusion of GABA(A) and GABA(B) receptor agonists(muscimol + baclofen) to showa causal role of the AI in context-induced relapse in Context B, the punishment context after prolonged abstinence. Our results show that there is substantial individual variability in the propensity to relapse in the punishment-associated context after prolonged abstinence, and this is mediated by activity in the AI.
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