Learning to avoid pain: Computational mechanisms and application to methamphetami

学习避免疼痛：计算机制及其在甲基苯丙胺中的应用

• 批准号: 7922059
• 负责人: TOR D. WAGER
• 金额: $ 34.68万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7922059
• 关键词: Absence of pain sensation; Abstinence; Accounting; Acute; Address; Affect; Affective; Amygdaloid structure; Analgesics; Anhedonia; Animal Experimentation; Animal Model; Animals; Anterior; Area; Association Learning; Aversive Stimulus; Avoidance Learning; Base of the Brain; Behavior; Behavior Therapy; Behavioral; Bilateral; Brain; Brain Stem; Brain region; Choice Behavior; Clinical; Clinical Research; Cognitive; Comparative Study; Computer Simulation; Computing Methodologies; Corpus striatum structure; Cues; Data; Dependence; Development; Dopamine; Drug Addiction; Drug abuse; Drug usage; Drug user; Event; Expectancy; Frequencies; Fright; Functional Magnetic Resonance Imaging; Goals; Health Care Costs; Hippocampus (Brain); Human; Image; Imaging Techniques; Individual; Insula of Reil; Interdisciplinary Study; Intervention; Lead; Learning; Life; Link; Literature; Magnetic Resonance Imaging; Measures; Medial; Mediating; Memory; Methamphetamine; Methods; Modeling; Motivation; Multivariate Analysis; Neurobiology; Neurosecretory Systems; Opiates; Opioid; Opioid Receptor; Outcome; Pain; Participant; Pathology; Pattern; Performance; Pharmaceutical Preparations; Pharmacology; Phase; Physics; Placebo Effect; Placebos; Population; Population Study; Preclinical Drug Evaluation; Prefrontal Cortex; Prevention; Probability; Process; Property; Psychological reinforcement; Public Health; Punishment; Relapse; Research; Research Personnel; Rewards; Safety; Scanning; Signal Transduction; Specificity; Staging; Stimulus; Stress; System; Temporal Lobe; Testing; Time; Urine; Ventral Striatum; Visual; Work; addiction; avoidance behavior; base; behavior measurement; brain behavior; cognitive neuroscience; computational neuroscience; cost; design; drug abuser; drug of abuse; endogenous opioids; expectation; experience; follow-up; frontier; hedonic; insight; long term memory; methamphetamine abuse; multiple drug use; neural patterning; neurobiological mechanism; novel; physical process; prevent; psychologic; public health relevance; relating to nervous system; research study; social; theories; treatment program

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH RELEVANCE: Neurobiological studies of reward- and punishment-guided learning in the brain offer powerful explanations for why drug-dependent individuals continue to choose drugs in spite of substantial costs in many areas of life. Neurobiological accounts have provided theories that lead to the development of new behavioral, cognitive, and pharmacological interventions to help break the cycle of drug abuse. An important frontier in this effort is the study of how aversive brain processes and experience (physical or psychological pain) motivate continued drug use. We propose some of the first work to look at how pain-avoidance learning works at a mechanistic, computational level in the human brain, and how changes in these systems are linked to methamphetamine use patterns in abusers. Findings from these studies will inform the development of new models of drug abuse and new treatments for users, which will help to reduce the personal health costs to abusers and the public health burden.

描述（由申请人提供）：尽管在生活的多个领域的成本持续使用药物是大多数药物依赖定义的核心。一个关键的问题是，尽管费用不断增加，为什么人们继续选择使用药物，而不是避免使用药物。神经生物学研究已经开始通过调查滥用药物如何影响情感，动机和学习的大脑系统来回答这个问题。几个主要的理论集中在食欲大脑“奖励”系统的敏化。越来越多的证据表明，快感缺乏和厌恶性学习也很重要，但相对较少的工作解决了人类厌恶性学习系统的变化如何与药物滥用有关。这类工作对于在动物和人类研究之间提供更深入和更具体的联系，以及将基本神经生物学机制与人类吸毒行为联系起来至关重要。这就是本提案的目标。我们结合了联合收割机的计算强化学习方法，它已成功地表征了食欲学习系统，与实验热疼痛模型，已成功地表征了大脑系统参与产生和调节疼痛和厌恶的期望。这两个成功的研究传统的新组合是一个强大的方法，可以提供新的措施，避免学习健康的个人和药物滥用者和动物模型的成瘾。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，它们随时间的动态变化，以及它们与回避行为的关系。三个实验使用功能性磁共振成像（fMRI）来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，可能支持学习的互补方面，以及期望对这些过程的影响。在目标2中，我们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构成了越来越大的挑战。我们将对MA滥用者和对照者进行比较研究，以a）描述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方法前瞻性地预测两个月随访期间的药物使用模式。这些目标的成功实现将有助于研究人员将成瘾动物模型的理论和发现与人类的药物使用行为联系起来。它还将提供大脑和行为中的厌恶体验和厌恶学习的新措施，这将为持续药物滥用的神经生物学原因提供重要的见解。这些发现可以a）为行为、认知和药理药物滥用治疗方案提供信息; B）提出预防药物使用达到临床依赖阶段的新方法; c）确定可以帮助预防和治疗方案更具体地针对个人的个体亚型。 公共卫生相关性：对大脑中奖励和惩罚引导的学习的神经生物学研究提供了强有力的解释，解释了为什么药物依赖者继续选择药物，尽管在生活的许多领域花费巨大。神经生物学帐户提供了理论，导致新的行为，认知和药理干预的发展，以帮助打破药物滥用的循环。这项工作的一个重要前沿是研究厌恶性大脑过程和体验（身体或心理疼痛）如何激发持续使用药物。我们提出了一些第一个工作，看看如何避免疼痛的学习工作在一个机械的，计算的水平在人类大脑中，以及如何在这些系统的变化与滥用者的甲基苯丙胺使用模式。这些研究的结果将为开发新的药物滥用模式和新的吸毒者治疗方法提供信息，这将有助于减少吸毒者的个人健康费用和公共健康负担。