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，预测未来结果，取决于大脑感知和形成事件持续时间记忆的能力。尽管在建立以毫秒为单位的计时和以小时为单位的昼夜节律计时的神经基础方面取得了进展，但关于间隔计时的中间尺度（即秒到几十分钟）的时间编码仍然存在许多基本问题。为了研究间隔时间是如何在大脑中表现的，我们将开发一种新的行为范式，它将与我们开发的用于监测和操纵内侧内嗅皮层中数千个脑细胞的成像方法相结合。这项工作将为理解大脑如何执行复杂的功能提供基础，这些功能取决于秒到分钟的时间编码。这项研究也有可能指导我们对疾病的理解，并为几种流行的神经退行性疾病和精神疾病提供靶向治疗。此外，这笔赠款将通过旨在支持高级神经科学研究生的科学交流研讨会来支持更广泛的影响，重点是支持来自代表性不足背景的学生。这项建议将解决有关间隔计时的神经回路机制的基本问题。先前的工作表明，内侧内嗅皮层（MEC）可以发挥选择性的作用，只有在初始学习阶段的时间间隔行为。然而，一个有趣的假设是，MEC可能是必要的间隔时间之前和/或之后的学习，这取决于特定的时间行为是否是基于纹状体的程序性学习，而不是只在初始学习阶段的间隔时间行为发挥选择性作用。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会持续需要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，并且可以通过服务于程序学习的大脑回路（如背侧纹状体）解决。该建议将应用一种新的间隔计时范例来测试MEC对于学习之前和/或之后的间隔计时是必要的这一假设，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学方法，在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，我们将确定哪些大脑回路在需要快速，灵活计时与静态，重复计时的任务中不同地参与间隔计时行为。此外，我们将确定MEC中的神经动力学，这是快速，灵活的时间行为学习的基础。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.