CAREER: A multiple memory systems approach to understand interval timing

该奖项全部或部分由《2021年美国救援计划法案》（公法117-2）资助。神经系统的许多功能，如学习和记忆，推断因果关系，预测未来的结果，都依赖于大脑感知和形成事件持续时间记忆的能力。尽管在毫秒级和小时级昼夜节律计时的神经基础方面取得了进展，但在间隔计时（即秒到几十分钟）的中间尺度上，关于时间编码的许多基本问题仍然存在。为了研究间隔时间是如何在大脑中表现出来的，我们将开发一种新的行为范式，该范式将与我们开发的成像方法相结合，用于监测和操纵内侧内嗅皮层的数千个脑细胞。这项工作将为理解大脑如何执行依赖于以秒到分钟为尺度的时间编码的复杂功能提供基础。这项研究也有可能指导我们对疾病的理解，并为几种常见的神经退行性疾病和精神疾病提供靶向治疗。此外，这笔拨款将通过一个科学交流研讨会来支持更广泛的影响，该研讨会旨在支持高级神经科学研究生，特别强调支持来自代表性不足背景的学生。这一建议将解决有关神经回路机制的基本问题。先前的研究表明，内侧内嗅皮层（MEC）仅在间隔时间行为的初始学习阶段起选择性作用。然而，一个有趣的假设是，在学习之前和/或之后，MEC可能是必要的，这取决于特定的定时行为是否可以修正为基于纹状体的程序学习，而不是只在间隔定时行为的初始学习阶段起选择性作用。从这个角度来看，需要灵活表示或快速学习时间信息的定时行为可能持续需要MEC。另一方面，任务参数保持不变的简单计时行为可能只需要在初始学习期间使用MEC，之后可以通过服务于程序学习的脑回路（如背纹状体）来解决。该提案将应用一种新的间隔计时范式来检验假设，即MEC对于学习之前和/或之后的间隔计时是必要的，这取决于要学习的特定计时行为所施加的约束。为了验证这一假设，我们将利用我们最近开发的几种方法，在行为小鼠的MEC中进行大规模细胞分辨率功能成像。通过将这些方法与一系列因果神经操作相结合，我们将确定哪些脑回路在需要快速、灵活的计时与静态、重复计时的任务中参与间隔计时行为的差异。此外，我们将确定MEC中的神经动力学，这是快速，灵活的定时行为学习的基础。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Many functions of the nervous system such as learning and memory, inferring cause and effect, and predicting future outcomes depend upon the brain’s ability to perceive and form memories of the duration of events. Despite progress in establishing the neural basis of timing on the scale of milliseconds and circadian timing over hours, many fundamental questions remain about time encoding on the intermediate scale of interval timing (i.e. second to tens of minutes). To investigate how interval time is represented in the brain we will develop a novel behavioral paradigm that will be used in concert with imaging methods we have developed to monitor and manipulate thousands of brain cells in medial entorhinal cortex. This work will provide a basis for understanding how the brain performs complex functions that depend upon encoding of time on the scale of seconds to minutes. The research also has the potential to guide our understanding of disease and provide targeted therapies for several prevalent neurodegenerative diseases and psychiatric disorders. Furthermore, this grant will support broader impacts through a science-communication workshop that is designed to support senior-level neuroscience graduate students, with a strong emphasis on supporting students from under-represented backgrounds. This proposal will address fundamental questions regarding the neural circuit mechanisms underlying interval timing. Prior work suggests that medial entorhinal cortex (MEC) could play a selective role only during the initial learning phase of interval timing behavior. However, an intriguing hypothesis is that MEC might be necessary for interval timing before and/or after learning, depending on whether the particular timing behavior is amendable to striatal-based procedural learning, rather than playing selective role only during the initial learning phase of interval timing behavior. In this view, timing behavior that require temporal information to be flexibly represented or rapidly learned might continuously require MEC. On the other hand, simple timing behaviors with task parameters that remain constant might only require MEC during initial learning and could be solved later on through brain circuits that serve procedural learning, such as the dorsal striatum. This proposal will apply a novel interval timing paradigm to test the hypothesis that MEC is necessary for interval timing before and/or after learning, depending on the constraints imposed by the particular timing behavior to be learned. In order to test this hypothesis we will leverage several methodological approaches that we have recently developed for large-scale cellular resolution functional imaging in MEC in behaving mice. By combining these methods with a series of causal neural manipulations we will determine which brain circuits are differentially involved in interval timing behavior across tasks that require rapid, flexible timing versus static, repetitive timing. Further, we will determine the neural dynamics in MEC that underlie learning of rapid, flexible timing behavior.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.