CAREER: A multiple memory systems approach to understand interval timing

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公共法律117-2)。神经系统的许多功能，如学习和记忆、推断因果关系和预测未来结果，都取决于大脑感知和形成对事件持续时间的记忆的能力。尽管在建立毫秒尺度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，但许多基本的问题仍然是关于在间隔计时的中间尺度(即，秒到几十分钟)进行时间编码。为了研究间隔时间在大脑中是如何表现的，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一起使用，以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复杂的功能提供基础，这些复杂功能依赖于几秒到几分钟的时间编码。这项研究还有可能指导我们对疾病的理解，并为几种普遍存在的神经退行性疾病和精神障碍提供有针对性的治疗。此外，这笔赠款将通过一个科学交流讲习班支持更广泛的影响，该讲习班旨在支持高级神经科学研究生，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背后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)只能在间隔计时行为的初始学习阶段发挥选择性作用。然而，一个有趣的假设是，MEC对于学习之前和/或学习后的间隔计时可能是必要的，这取决于特定的计时行为是否可以修改为基于纹状体的程序性学习，而不是只在间隔计时行为的初始学习阶段发挥选择性作用。在这一观点中，需要灵活地表示或快速学习时间信息的计时行为可能持续地需要MEC。另一方面，任务参数保持不变的简单计时行为可能只在初始学习期间需要MEC，稍后可以通过服务于程序性学习的大脑回路(如背侧纹状体)来解决。该建议将应用一种新的间隔计时范例来检验这样的假设，即根据要学习的特定计时行为施加的约束，MEC对于学习之前和/或之后的间隔计时是必需的。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，在行为正常的小鼠身上进行MEC的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，我们将确定在需要快速、灵活的计时与静态、重复计时的任务之间，哪些大脑回路与间隔计时行为有关。此外，我们将确定MEC的神经动力学，这是学习快速、灵活的时间行为的基础。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.