Neural circuit mechanisms of drug-context associations in the hippocampus

海马区药物关联的神经回路机制

• 批准号: 10723049
• 负责人: Yanjun Sun
• 金额: $ 15.13万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-15 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10723049
• 关键词: Advanced Development; Affect; Animal Behavior; Animal Model; Association Learning; Behavioral; Brain; Brain region; Cells; Clinical; Code; Cognition; Cognitive; Color; Communication; Computer Models; Data; Development; Drug Targeting; Drug usage; Exposure to; Genetic; Goals; Head; Hippocampal Formation; Hippocampus; Image; Imaging Device; Individual; Intervention; Ketamine; Knowledge; Knowledge acquisition; Label; Learning; Maps; Mediating; Memory; Methods; Modeling; Molecular; Morphine; Mus; Nature; Negative Reinforcements; Neurons; Opioid; Output; Pathologic; Perception; Pharmaceutical Preparations; Positioning Attribute; Property; Public Health; Research; Retrieval; Rewards; Running; Speed; Substance Use Disorder; Testing; Therapeutic; Training; Withdrawal; cell type; conditioned place preference; conditioning; drug craving; drug relapse; drug reward; drug seeking behavior; drug withdrawal; high dimensionality; human model; in vivo; in vivo imaging; insight; machine learning method; neural; neural circuit; neural model; neuroimaging; novel; novel therapeutics; opioid withdrawal; programs; prolonged abstinence; psychostimulant; response; skill acquisition; substance use treatment; tool; virus genetics

PROJECT ABSTRACT Addictive drugs usurp the normal neural machinery for learning and memory to generate pathological cognition that can lead to compulsive drug usage. One prominent example is re-exposure to a drug-associated environmental context, which robustly induces drug relapse in both humans and animal models. The hippocampal formation, which is critical for spatial and contextual learning, is well positioned to support the encoding of this type of drug-context association. Despite decades of hippocampal studies on drug-evoked molecular and cellular adaptations and drug-seeking behaviors, we still lack a clear understanding of which hippocampal circuits are involved in acquiring and maintaining maladapted drug-context associations and how neural dynamics in the hippocampus are transformed to support drug-seeking behavior. Moreover, there are no interventions that specifically target the drug-associated memories to treat substance use disorders. Here, with the proposed training in computational modeling for neural dynamics and the development of advanced genetic and imaging tools, I aim to fill these knowledge gaps by elucidating the neural circuit mechanisms in the hippocampus for drug-context associations and probing whether we can reverse this association using a memory-based intervention. Preliminary data suggest opioid reward vs. withdrawal-mediated associative learning have distinct effects on representing different spatial variables in CA1 neurons and ketamine was able to reset the maladapted contextual representation to disrupt the retrieval of drug-associated memories. For Aim 1, I will investigate how drug-associated information alters the neural coding in the hippocampus for multiple spatial variables that are critical for the perception of a given context. Using miniscope imaging in morphine conditioned place preference/aversion, I will learn to build linear-nonlinear Poisson (LNP) models to reveal how drug-context associations under positive vs. negative reinforcement affect the neural coding of CA1 for position, head orientation, running speed and their conjunctions. For Aim 2, I will test the hypothesis that Ketamine disrupts learned drug-context associations by restoring the maladapted representations of functional cell types (e.g., place cells) to their normal state. I will acquire expertise on opioid withdrawal and investigate ketamine’s effect on withdrawal-context associations by targeting memory reconsolidation and reveal the corresponding change in neural dynamics of CA1. For Aim 3, I will elucidate neural circuit assembly and dynamics for coding drug-associated contextual information in the subiculum, a major downstream target of the hippocampal CA1. This study will leverage my training in Aim 1 and 2 to advance our understanding of the principles for processing drug-associated information in the brain. Together, the proposed training and studies will not only help me to establish an independent research program but also provide a mechanistic understanding of how hippocampal neurons encode and represent drug-associated contextual information and shed light on developing novel therapeutic treatments for substance use disorders.

项目摘要 成瘾药物篡夺正常的学习和记忆神经机制以产生病理性认知 这可能会导致强制使用药物。一个突出的例子是再次接触与毒品有关的 环境背景，这强烈地导致了人类和动物模型中的药物复发。这个 海马体结构对空间和语境学习至关重要，它处于良好的位置，支持 对这种类型的药物关联进行编码。尽管几十年来对药物诱发的海马区的研究 分子和细胞的适应和药物寻找行为，我们仍然缺乏清楚的了解 海马区环路参与获取和维持不良适应的药物背景联系以及如何 海马体中的神经动力学被转化为支持药物寻找行为。此外，也没有 专门针对药物相关记忆的干预措施，以治疗物质使用障碍。在这里，与 拟议的神经动力学计算建模培训和高级遗传学的发展 和成像工具，我的目标是通过阐明神经回路机制来填补这些知识空白 海马体的药物上下文关联，并探索我们是否可以用一种 基于记忆的干预。初步数据显示，阿片类药物奖励与戒断介导的联想 学习对CA1神经元不同空间变量的表征有不同的影响，氯胺酮能够 重置适应不良的语境表征，以扰乱药物相关记忆的提取。为了达到目标 1，我将研究药物相关信息如何改变海马体中的神经编码 空间变量对感知给定的上下文至关重要。迷你镜成像在吗啡治疗中的应用 条件位置偏好/厌恶，我将学习建立线性-非线性泊松(LNP)模型，以揭示 正强化与负强化下的药物上下文关联影响CA1对位置的神经编码， 头部朝向、跑步速度及其联合作用。对于目标2，我将测试氯胺酮的假设 通过恢复适应不良的功能细胞类型来破坏获得性药物与环境的联系 (例如，将单元格置于其正常状态)。我将获得阿片类药物戒断方面的专业知识，并调查氯胺酮 靶向记忆再巩固对提取-情境联想的影响 CA1的神经动力学改变。对于目标3，我将阐明用于编码的神经回路组装和动力学 下丘脑中药物相关的上下文信息，这是海马CA1的一个主要下游靶点。 这项研究将利用我在目标1和目标2中的培训来促进我们对加工原理的理解 大脑中与毒品有关的信息。总之，拟议的培训和学习不仅将帮助我 建立独立的研究计划，但也提供对海马体如何 神经元编码和代表药物相关的上下文信息，并为开发新的 药物使用障碍的治疗方法。