Brain Imaging Studies of Negative Reinforcement in Humans

治疗药物成瘾的一个主要挑战是理解学习性联想如何与厌恶性成瘾者联系起来 促进逃避行为，引发吸毒的发作和复发。对非人类动物的研究 开始阐明回避学习的神经行为机制，但很少有人努力 将这些发现应用于人类。神经可塑性大脑机制，支持长期 记忆的形成被假设为改变刺激的表征并加强语境 协会作为其激励属性的函数。这项研究采用了认知神经科学 的观点来描述动机脑系统如何调节人类陈述性记忆的形成 导致行为回避。虽然人类的陈述性记忆传统上是用列表来探测的， 学习范式，计算机图形界面和沉浸式虚拟现实（VR）的最新进展 技术允许开发新的导航回避任务，这些任务提供了与 动物文献和更密切的模型现实世界的回避行为表现出的药物成瘾者的反应， 环境压力源。健康的参与者将接受一系列功能性磁共振检查 在传统的列表学习和新的列表学习的背景下呈现强化刺激的成像研究 基于VR的导航学习和记忆任务。第一组实验比较了 对陈述性记忆系统的影响。第二系列 实验确定了消极情绪状态如何放大记忆效应的激励属性， 作为一种情绪修复的形式，激励寻求奖励（“救济”）。第三系列 实验开发了一种多感官，沉浸式VR范式，模拟压力诱导的回避， 逃避一个结合了导航和列表学习方法的自然主义记忆任务。功能 连通性建模，结合多元回归和独立成分分析，将 描述动机和记忆系统的相互作用及其与个体的关系 行为表现指数和回避特征标记的差异。因此，拟议的研究 代表了人类回避学习的系统和创新方法，结合了尖端的VR技术， 技术和功能性神经影像学方法。研究结果将弥合翻译差距， 了解积极的行为，情绪状态和压力源如何改变厌恶行为的影响 对学习和记忆系统的影响，有助于建立内部地图的显着特点， 环境

A major challenge to treating drug addiction is understanding how learned associations to aversive reinforcers promote avoidant behavior and trigger the onset and relapse of drug use. Studies in non-human animals have begun to elucidate the neurobehavioral mechanisms of avoidance learning, but there have been few efforts to translate these findings to human populations. Neuroplastic brain mechanisms that support long-term memory formation are hypothesized to alter the representations of stimuli and strengthen contextual associations as a function of their incentive properties. The proposed research adopts a cognitive neuroscience perspective to characterize how motivational brain systems modulate declarative memory formation in humans and lead to behavioral avoidance. Although human declarative memory is traditionally probed using list- learning paradigms, recent advances in computer graphics interfaces and immersive virtual reality (VR) technology permit the development of novel navigational avoidance tasks that provide a tighter link with the animal literature and more closely model real-world avoidant behaviors exhibited by drug addicts in response to environmental stressors. Healthy participants will undergo a series of functional magnetic resonance imaging studies that present reinforcing stimuli within the context of both traditional list-learning and novel VR-based navigational learning and memory tasks. The first series of experiments compares the influence of appetitive versus aversive instrumental reinforcers on declarative memory systems. The second series of experiments determines how negative mood states amplify the mnemonic effects of the incentive properties of instrumental reinforcers and motivate reward-seeking ("relief") as a form of mood repair. The third series of experiments develops a multisensory, immersive VR paradigm that simulates stress-induced avoidance and escape on a naturalistic memory task that combines navigational and list-learning approaches. Functional connectivity modeling, in combination with multiple regression and independent components analyses, will characterize the interactions of motivational and memory systems and their relationship to individual differences in behavioral performance indices and trait markers of avoidance. The proposed studies thus represent a systematic and innovative approach to human avoidance learning that combines cutting-edge VR technology and functional neuroimaging methods. The research findings will bridge a translational gap in understanding how positive reinforcers, mood states, and stressors modify the impact of aversive behavioral consequences on learning and memory systems that help establish internal maps of salient features of the environment.