Functional significance of network dynamics in hippocampal circuits

描述（由申请人提供）：海马体是记忆在独特的空间和时间背景下发生的个人事件（情景记忆）的重要结构。该项目的长期目标是了解海马电路（即，子场）和相关的皮层区域处理事件相关的信息，并在这些神经过程和记忆行为之间建立因果关系。先进的记录技术和复杂的分析方法目前允许监测大量的神经元的放电模式，同时从多个大脑区域在自由行为的动物。然而，关于情景记忆，通过使用这些技术获得的知识的功能意义仍然不清楚，因为当动物从事类似情景的记忆任务时，很少记录神经活动。该项目将填补这一关键空白，并阐明海马体中不同的神经元网络如何在需要编码和检索特定于上下文的事件时对动物的行为做出贡献。计算模型预测，海马的齿状回和CAS子字段是必不可少的，当不同的背景下，需要形成独立的表示（模式分离），也当原始表示的上下文需要在面对不完整/模糊的上下文（模式完成）检索。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。具体地说，动物将被要求产生与不同背景环境相关的离散行为反应。此外，该建议旨在确定这些上下文相关的行为反应和同时从多个海马子场记录的整体神经元活动之间的关系。因此，当前项目的结果将通过将计算理论的预测、神经网络的生理特性和记忆行为联系起来，推进我们对情节记忆成分如何在详细的海马回路中处理的知识。临床上，海马体和相关区域（例如，阿尔茨海默氏症和精神分裂症）导致毁灭性的健忘症。因此，这项建议的结果将有助于改善对大脑依赖性遗忘症的诊断和治疗。

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.