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 成瘾性药物篡夺了学习和记忆的正常神经机制，从而产生病理性认知 会导致强迫性吸毒一个突出的例子是重新接触与药物有关的 环境背景，其在人类和动物模型中强烈诱导药物复吸。的 海马结构，这是关键的空间和上下文的学习，是很好的定位，以支持 这种类型的药物背景关联的编码。尽管对药物诱发的海马体的研究已经进行了几十年， 分子和细胞的适应和药物寻求行为，我们仍然缺乏一个清晰的理解， 海马回路参与获得和维持不适应的药物背景关联，以及如何 海马体中的神经动力学被转化以支持药物寻求行为。此外，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。这里和 建议的训练，在计算建模的神经动力学和发展先进的遗传 和成像工具，我的目标是填补这些知识空白，阐明神经回路机制， 海马体的药物背景协会，并探讨我们是否可以扭转这种协会使用 记忆干预初步数据表明，阿片类药物奖励与戒断介导的关联 学习对CA1神经元表现不同空间变量有明显影响，氯胺酮能够 重新设置不适应的情境表征，以破坏与药物相关的记忆的检索。为宗旨 1，我将研究药物相关信息如何改变海马体中的神经编码， 对于感知给定上下文至关重要的空间变量。微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，以揭示如何 正强化与负强化下的药物背景关联影响CA1的位置神经编码， 头部方向、跑步速度及其连接。对于目标2，我将检验氯胺酮 通过恢复功能性细胞类型的不适应表征来破坏习得的药物背景关联 (e.g.,将细胞）放置到其正常状态。我会学习阿片类药物戒断方面的专业知识 通过靶向记忆再巩固对戒断情境关联的影响，并揭示相应的 CA1的神经动力学变化。对于目标3，我将阐明编码的神经回路组装和动力学 海马CA1的主要下游靶点下脚中的药物相关背景信息。 这项研究将利用我在目标1和目标2中的培训来提高我们对处理原则的理解 大脑中与药物相关的信息。总之，拟议的培训和研究不仅有助于我 建立一个独立研究项目，同时也提供了海马 神经元编码和代表药物相关的背景信息，并阐明开发新的 物质使用障碍的治疗性治疗。