The influence of mesolimbic-hippocampal interactions on episodic memory during active information seeking

主动信息寻求过程中中边缘-海马相互作用对情景记忆的影响

基本信息

批准号：
10621702
负责人：
Vishnu Pradeep Murty
金额：
$ 54.72万
依托单位：
TEMPLE UNIV OF THE COMMONWEALTH
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-05-15 至 2027-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10621702
关键词：
Active Learning Adaptive Behaviors Animal Model Behavior Behavior assessment Behavioral Behavioral Paradigm Cognitive Computer Models Corpus striatum structure Cues Decision Making Development Dopamine Elements Environment Episodic memory Event Feedback Functional Magnetic Resonance Imaging Future Hippocampus Human Incubated Individual Individual Differences Knowledge Learning Mediating Memory Modeling Motivation Outcome Perception Pharmaceutical Preparations Phase Pre-Clinical Model Process Psychiatry Psychological reinforcement Relapse Research Rewards Risk Risk Factors Rodent Sampling Shapes Signal Transduction Substance abuse problem Support System Testing Uncertainty Ventral Tegmental Area animal data contextual factors craving drug seeking behavior experience forgetting information processing information seeking behavior insight long term memory memory consolidation memory encoding mesolimbic system motivated behavior neuroimaging novel response substance use tool

项目摘要

PROJECT SUMMARY Interactions between the hippocampus and mesolimbic dopamine system supports memory encoding and subsequent consolidation to stabilize salient information in long-term memory. These episodic traces are used to support a variety of adaptive behaviors, including inference, generalization, and decision-making. Information seeking further represents a context in which motivated learning occurs in the absence of explicit reward, including incubation-induced craving and context-dependent feedback. In this way, information seeking may serve as a model to dissect how mesolimbic-hippocampal circuits contribute to the complexity of drug seeking behavior. Most research characterizing the contributions of mesolimbic-hippocampal interactions on memory have focused on reward. However, this circuit is also critically involved in memory enhancements resulting from active exploration. Critically, memory enhancements during active information seeking involves the integration of mesolimbic signaling across multiple elements of an event (cues versus outcomes) and timescales (event-evoked versus state-dependent). Rodent studies show that hippocampal engagement during exploration triggers a positive feedback loop, which increases tonic dopamine signaling in the ventral tegmental area (VTA), which in turn yields larger VTA anticipation and feedback responses. Prominently, these positive feedback loops could instantiate and propagate the variety of behaviors contributing to substance use. We propose to characterize how state-dependent VTA responses relate to memory enhancements during active information seeking using a combination of novel behavioral paradigms, state-of-the-art neuroimaging, and computational modeling to inform mechanisms underlying memory. Aim 1 will study mesolimbic- hippocampal contributes to memory encoding during active learning and hypothesis testing. Aim 2 will study how engagement of this circuit during encoding stabilizes memory representations during periods of post- encoding consolidation. Finally, Aim 3 will utilize a computational psychiatry approach to study how individual differences in memory during active information seeking relates to predictors of substance use risk.

项目摘要海马和中唇多巴胺系统之间的相互作用支持记忆编码和随后的合并以稳定长期记忆中的显着信息。这些情节迹线被使用支持各种自适应行为，包括推论，概括和决策。寻求信息进一步代表了一个上下文，在没有明确的情况下进行积极学习奖励，包括孵化引起的渴望和与上下文有关的反馈。这样，寻求信息可以用作剖析中左右 - 卫星电路如何有助于药物复杂性的模型寻求行为。大多数研究表征了中左右 - 山皮相互作用对记忆重点是奖励。但是，该电路还与内存增强有关由主动探索产生。至关重要的是，在积极信息寻求期间的记忆增强涉及跨事件的多个元素（提示与结果）和时间尺度（事件诱发的与状态依赖性）。啮齿动物研究表明，海马在探索触发了一个正反馈回路，这增加了腹侧的滋补多巴胺信号换段区域（VTA），进而产生更大的VTA预期和反馈响应。显着，这些积极的反馈回路可以实例化并传播导致药物使用的各种行为。我们建议表征状态依赖性VTA响应与记忆增强的关系使用新型行为范式，最先进的神经影像的组合寻求主动信息，和计算建模，以告知内存的机制。 AIM 1将研究中左右海马有助于在主动学习和假设检验期间进行记忆编码。 AIM 2将学习该电路在编码过程中的参与如何在后期稳定记忆表示编码合并。最后，AIM 3将利用计算精神病学方法来研究个人主动信息寻求期间内存的差异与物质使用风险的预测因素有关。