Functional significance of network dynamics in hippocampal circuits

描述（由申请人提供）：海马体是记忆在特定空间和时间背景下发生的个人事件（情景记忆）的基本结构。该项目的长期目标是了解海马体回路（即子区）和相关皮质区域如何处理事件相关信息，并在这些神经过程和助记行为之间建立因果关系。目前，先进的记录技术和复杂的分析方法可以监测自由行为动物大脑多个区域同时产生的大量神经元的放电模式。然而，就情景记忆而言，通过使用这些技术获得的知识的功能意义仍然不清楚，因为当动物从事情景记忆任务时，神经活动很少被记录下来。该项目将填补这一关键空白，并阐明当特定情境的事件需要编码和检索时，海马体中不同的神经元网络如何对动物的行为做出贡献。计算模型预测，当需要形成不同情境的独立表征（模式分离）时，以及当面对不完整/模糊的情境（模式完成）时，需要检索情境的原始表征时，海马的齿状回和CAS子场是必不可少的。该提案将通过采用创新的调查策略来测试这些来自计算模型的关键预测。具体来说，这些动物将被要求在不同的情境环境中产生离散的行为反应。此外，本研究旨在确定这些情境依赖的行为反应与同时从多个海马子区记录的整体神经元活动之间的关系。当前项目的结果将通过将计算理论、神经网络的生理特性和助记行为的预测联系起来，从而推进我们对情景记忆成分如何在详细的海马体回路中被处理的认识。在临床上，海马体及相关区域的损伤（如阿尔茨海默病和精神分裂症）会导致严重的健忘症。因此，这项建议的结果将有助于改善海马依赖性健忘症的诊断和治疗。

DESCRIPTION (provided by applicant): The hippocampus is an essential structure for remembering personal events that have occurred in unique spatial and temporal contexts (episodic memory). The long-term objective of this project is to understand how detailed hippocampal circuits (i.e., subfields) and associated cortical areas process event-related information and to establish a causal relationship between these neural processes and mnemonic behavior. Advanced recording techniques and sophisticated analytical methods currently allow monitoring of the firing patterns of a large number of neurons simultaneously from multiple brain regions in freely behaving animals. With respect to episodic memory, however, the functional significance of the knowledge gained by using these techniques remains unclear, because the neural activity is rarely recorded when the animals are engaged in an episodic-like memory task. This project will fill this critical gap and elucidate how different networks of neurons in the hippocampus contribute to the animal's behavior when context-specific events need to be encoded and retrieved. Computational models predict that the dentate gyrus and CAS subfields of the hippocampus are essential when independent representations of different contexts need to be formed (pattern separation) and also when original representations of contexts need to be retrieved in the face of incomplete/ambiguous contexts (pattern completion). This proposal will test these critical predictions from the computational models by adopting an innovative investigative strategy. Specifically, the animals will be required to produce discrete behavioral responses in association with different contextual environments. Furthermore, this proposal seeks to identify the relationship between these context-dependent, behavioral responses and the ensemble neuronal activity recorded from multiple hippocampal subfields simultaneously. The outcomes from the current project will thus advance our knowledge of how episodic memory components are processed in detailed hippocampal circuits by linking the predictions from computational theories, physiological properties of neural networks, and mnemonic behavior. Clinically, damage within the hippocampus and associated areas (e.g., in Alzheimer's disease and schizophrenia) results in a devastating amnesic syndrome. The outcomes from this proposal will thus contribute to creating improved diagnosis and treatment of the hippocampal-dependent amnesia.