Learning to avoid pain: Computational mechanisms and application to methamphetami

项目摘要 尽管在生活的多个领域中花费巨大，但持续使用毒品是大多数毒品定义的核心 依赖一个关键问题是，为什么人们继续选择使用毒品，而不是避免使用毒品， 尽管成本不断增加。神经生物学研究已经开始回答这个问题， 滥用药物会影响情感、动机和学习的大脑系统。几大理论 专注于大脑“奖励”系统的敏感化。越来越多的证据表明， 快感缺乏和厌恶性学习也很关键，但相对较少的工作涉及人类如何改变 令人厌恶的学习系统与药物滥用有关。迫切需要开展这项工作， 动物和人类研究之间的具体联系，并将基本的神经生物学机制与人类 吸毒行为这就是本提案的目标。 我们结合联合收割机的计算强化学习方法，它已成功地表征 食欲学习系统，具有实验性热疼痛模型，该模型成功地表征了大脑 参与产生和调节疼痛和厌恶性期望的系统。这种新颖的组合， 成功的研究传统是一个强有力的方法，可以提供新的措施，避免学习， 健康个体和药物滥用者以及与成瘾动物模型的联系。 在目标1中，我们开发了一个参与学习预测疼痛的人脑系统的规范模型， 动态随时间的变化，以及它们与回避行为的关系。三个实验使用功能磁 磁共振成像（fMRI），以表征参与表征疼痛和回避学习的大脑系统。 我们专注于疼痛处理和学习网络之间的相互作用，多个记忆系统， 支持学习的补充方面，以及期望对这些过程的影响。在目标2中， 将这项工作扩展到甲基苯丙胺（MA）滥用者的特征，这是一个不断增长但研究不足的人群， 对公共安全和公共卫生提出了越来越大的挑战。我们将对MA进行比较研究 滥用者和控制者，以a）表征疼痛表征和回避学习系统的差异; 和B）使用基于大脑系统的测量来前瞻性地预测两个月期间的药物使用模式 跟进成功完成这些目标将有助于研究人员利用理论和研究结果， 通过将它们与人类吸毒行为联系起来，建立成瘾的动物模型。它还将提供新的措施， 厌恶性经验和厌恶性学习的大脑和行为，这将提供重要的见解， 持续滥用药物的神经生物学原因这些发现可以a）告知行为，认知， 药物滥用治疗方案; B）提出防止药物使用达到 临床依赖的阶段，以及c）识别可以帮助预防的个体的亚型，以及 治疗方案应更具体地针对个人。

Project summary The persistent use of drugs in spite of costs in multiple areas of life is central to most definitions of drug dependence. A critical question is why individuals continue to choose to use drugs, rather than avoid them, despite increasing costs. Neurobiological research has begun to answer this question by investigating how drugs of abuse impact brain systems that underlie affect, motivation, and learning. Several major theories focus on sensitization in appetitive brain 'reward' systems. A growing body of evidence suggests that anhedonia and aversive learning are also critical, but relatively little work addresses how changes in human aversive learning systems are linked to drug abuse. Such work is critically needed to provide deeper and more specific links between animal and human research, and to link basic neurobiological mechanisms with human drug-taking behavior. That is the goal of this proposal. We combine a computational reinforcement learning approach, which has successfully characterized appetitive learning systems, with an experimental thermal pain model that has successfully characterized brain systems involved in generating and modulating pain and aversive expectancies. This novel combination of two successful research traditions is a powerful approach that can provide new measures of avoidance learning in healthy individuals and drug abusers and links with animal models of addiction. In Aim 1, we develop a normative model of human brain systems involved in learning to predict pain, their dynamics over time, and their relationship to avoidance behavior. Three experiments use functional magnetic resonance imaging (fMRI) to characterize brain systems involved in representing pain and avoidance learning. We focus on interactions between pain-processing and learning networks, multiple memory systems that may support complementary aspects of learning, and the effects of expectation on these processes. In Aim 2, we extend this work to characterize methamphetamine (MA) abusers, a growing but under-studied population that presents an increasing public safety and public health challenge. We will conduct a comparative study of MA abusers and controls to a) characterize differences in pain representation and avoidance learning systems; and b) use brain systems-based measures to prospectively predict patterns of drug use during a two-month follow up. Successful completion of these aims will help researchers to leverage theories and findings from animal models of addiction by linking them to human drug-use behavior. It will also provide new measures of aversive experience and aversive learning in both brain and behavior, which will provide important insights into the neurobiological causes of persistent drug abuse. Such findings can a) inform behavioral, cognitive, and pharmacological drug-abuse treatment programs; b) suggest new ways of preventing drug use from reaching the stage of clinical dependence, and c) identify sub-types of individuals that can help prevention and treatment programs be tailored more specifically to individuals.