A neuronal code for extended time in the hippocampal-entorhinal circuitry

海马-内嗅回路中延长时间的神经元代码

• 批准号: 8984918
• 负责人: Jill K Leutgeb
• 金额: $ 37.47万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8984918
• 关键词: Address; Alzheimer' s Disease; Animals; Area; Behavior; Behavioral; Biological Neural Networks; Brain; Brain region; Cells; Code; Data; Disease; Electrophysiology (science); Environment; Episodic memory; Event; Foundations; Functional disorder; Future; Health; Hippocampal Formation; Hippocampus (Brain); Hour; Human; Lateral; Lesion; Location; Measures; Medial; Memory; Memory Loss; Mental disorders; Neurodegenerative Disorders; Neurons; Pathology; Patients; Pattern; Population; Post-Traumatic Stress Disorders; Publishing; Radial; Rattus; Retrieval; Rodent; Schizophrenia; Structure; Temporal Lobe; Temporal Lobe Epilepsy; Testing; Theoretical model; Time; Traumatic Brain Injury; Update; arm; awake; base; behavior test; entorhinal cortex; experience; long term memory; memory process; nervous system disorder; novel; relating to nervous system; repaired; research study; time interval; treatment strategy

DESCRIPTION (provided by applicant): The hippocampal formation is critical for the formation and retrieval of autobiographical memories, which consist of information about what happened when and where. It is known how objects, context and space (what, where) are represented in the hippocampus and it has recently been described that time (when events occur) on a scale of seconds to minutes is represented by the sequential activation of hippocampal cells. On a longer time scale, a time-varying neural code has previously been shown by theoretical models to be suitable for estimating the recency of a remembered event. In recently published results and results presented as preliminary data, we identify a novel, time-varying hippocampal neural code that can represent how long ago an event occurred on a time scale of hours and days. Our data first identified that the neuronal firing patterns of CA1 cells are characterized by a monotonic accumulation of rate differences as a function of time between experiences. However, we demonstrate that stored information does not simply deteriorate in the CA1 area, but that the code for time can co-exist with reliable coding for other aspects of an event, such as the spatial location or the context. We also found that CA3 contains an exquisitely precise code for context and space that does not vary over time. New preliminary data show an effect in CA2 that is opposite of CA3. CA2 cells represent elapsed time but no information about context. Based on these findings, we hypothesize that the neuronal code for extended time is combined with spatial and contextual information in the CA1 cell population to guide behavior in which the recency of a previous event is remembered. Using a combination of behavioral testing and single-unit recordings in awake behaving rodents, this hypothesis is tested in three aims that: (1) determine whether the neuronal code for extended time intervals is generated in the hippocampal CA2 neural network, (2) determine whether the input from the hippocampal CA3 subregion is necessary for maintaining the stable memory coding component in the CA1 neural network over hours and days, and (3) determine whether a time-varying neural code in hippocampal CA1 and CA2 subregions is correlated with remembering "how long ago". The first two aims address how different subregions contribute to the time-varying and stable components of the neural code. In addition to defining the function of CA2 for temporal coding and the function of CA3 in enabling stable memory representations, we will also ask whether the entorhinal cortex can represent time on an extended scale and is thus a brain region in which temporal coding over a large range of scales can be found. In the third aim, we will use a behavioral task in which it has been shown that rats remember "how long ago" over extended time periods. We will measure the similarity of activity patterns in place cell populations between two time points and determine whether the change in neuronal firing patterns corresponds to the rat's estimate of elapsed time. Taken together, these studies will be important for understanding the neural network mechanisms for long-term memory stability and temporal event coding in the brain structures that support episodic memory. Understanding the key mechanisms for memory processing will guide efforts to repair circuit dysfunction in psychiatric, neurological, and neurodegenerative diseases.

描述（由申请人提供）：海马结构对于自传体记忆的形成和检索至关重要，自传体记忆包括有关何时何地发生的事情的信息。众所周知，物体、环境和空间（什么、哪里）在海马体中是如何表示的，并且最近描述了以秒到分钟为单位的时间（事件发生时）是通过海马体细胞的顺序激活来表示的。在较长的时间尺度上，理论模型先前已证明时变神经代码适合估计记忆事件的新近度。在最近发表的结果和作为初步数据呈现的结果中，我们确定了一种新颖的、随时间变化的海马神经代码，它可以以小时和天的时间尺度表示事件发生的时间。我们的数据首先发现 CA1 细胞的神经元放电模式的特点是速率差异的单调累积，作为两次经历之间时间的函数。然而，我们证明存储的信息不仅仅在 CA1 区域恶化，而且时间代码可以与事件其他方面的可靠编码共存，例如 空间位置或上下文。我们还发现 CA3 包含非常精确的上下文和空间代码，不会随时间变化。新的初步数据显示 CA2 中的效果与 CA3 相反。 CA2 单元代表经过的时间，但没有有关上下文的信息。基于这些发现，我们假设长时间的神经元代码与 CA1 细胞群中的空间和上下文信息相结合，以指导记住先前事件的近期发生的行为。结合使用行为测试和清醒行为啮齿动物的单单元记录，该假设在三个目标上进行了测试：（1）确定海马 CA2 神经网络中是否生成了延长时间间隔的神经元代码，（2）确定来自海马 CA3 子区域的输入是否对于在数小时和数天内维持 CA1 神经网络中稳定的记忆编码组件是必要的，以及 (3)确定海马CA1和CA2亚区的时变神经编码是否与记忆“多久以前”相关。前两个目标解决不同子区域如何对神经代码的时变和稳定部分做出贡献。除了定义 CA2 的时间编码功能和 CA3 的稳定记忆表征功能外，我们还将询问内嗅皮层是否可以在扩展尺度上表示时间，从而成为可以在大范围尺度上找到时间编码的大脑区域。在第三个目标中，我们将使用一项行为任务，其中已表明老鼠在较长的时间内记住“多久以前”。我们将测量不同区域细胞群活动模式的相似性 两个时间点并确定神经元放电模式的变化是否对应于大鼠对经过时间的估计。总而言之，这些研究对于理解支持情景记忆的大脑结构中的长期记忆稳定性和时间事件编码的神经网络机制非常重要。了解记忆处理的关键机制将指导修复精神、神经和神经退行性疾病中的回路功能障碍。