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

基本信息

批准号：
8128693
负责人：
TOR D. WAGER
金额：
$ 35.65万
依托单位：
UNIVERSITY OF COLORADO
依托单位国家：
美国
项目类别：
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/8128693
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 Behavioral Bilateral Brain Brain Stem Brain region Choice Behavior Clinical Clinical Research Cognitive Cognitive Therapy 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 program 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

项目摘要

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要付出代价，但持续使用药物是大多数药物依赖定义的核心。一个关键问题是，尽管成本增加，但为什么人们继续选择使用毒品，而不是避免使用毒品。神经生物学研究已经开始通过调查滥用药物如何影响作为情感、动机和学习基础的大脑系统来回答这个问题。几种主要理论关注大脑食欲“奖励”系统的敏感性。越来越多的证据表明，快感缺乏和厌恶学习也很重要，但相对较少的工作涉及人类厌恶学习系统的变化如何与药物滥用相关。迫切需要开展此类工作，以在动物和人类研究之间提供更深入、更具体的联系，并将基本神经生物学机制与人类吸毒行为联系起来。这就是本提案的目标。我们将计算强化学习方法（已成功表征食欲学习系统）与实验性热疼痛模型（已成功表征参与生成和调节疼痛和厌恶期望的大脑系统）结合起来。这种两种成功研究传统的新颖结合是一种强大的方法，可以为健康个体和药物滥用者提供回避学习的新措施，并将其与成瘾动物模型联系起来。在目标 1 中，我们开发了人类大脑系统的规范模型，该模型涉及学习预测疼痛、疼痛随时间的动态变化以及它们与回避行为的关系。三项实验使用功能磁共振成像（fMRI）来表征参与表达疼痛和回避学习的大脑系统。我们关注疼痛处理和学习网络之间的相互作用、可能支持学习互补方面的多个记忆系统，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描述甲基苯丙胺 (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日益严峻的挑战。我们将对 MA 滥用者和对照进行比较研究，以 a) 表征疼痛表征和回避学习系统的差异； b) 在两个月的随访期间，使用基于大脑系统的测量方法前瞻性地预测药物使用模式。成功完成这些目标将有助于研究人员利用成瘾动物模型的理论和发现，将其与人类吸毒行为联系起来。它还将为大脑和行为中的厌恶体验和厌恶学习提供新的测量方法，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、认知和药理学药物滥用治疗方案提供信息； b) 提出防止吸毒达到临床依赖阶段的新方法，以及 c) 确定个体的亚型，以帮助更具体地针对个体制定预防和治疗方案。公共健康相关性：对大脑奖励和惩罚引导学习的神经生物学研究为为什么药物依赖者继续选择药物提供了有力的解释，尽管在生活的许多领域付出了巨大的代价。神经生物学的解释提供了理论，导致新的行为、认知和药理学干预措施的发展，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经历（身体或心理疼痛）如何激发持续吸毒。我们提出了一些初步工作，以研究避免疼痛的学习如何在人脑的机械、计算水平上发挥作用，以及这些系统的变化如何与滥用者的甲基苯丙胺使用模式相关。这些研究的结果将为开发新的药物滥用模式和新的治疗方法提供信息，这将有助于减少滥用者的个人健康成本和公共卫生负担。