Activity-Dependent Tagging of Cerebellar Neurons for Studying Signal Processing and Learning

项目摘要 拟议研究的目标是实现国家的最先进的技术记录和操纵 神经元在小脑中的活动，解剖小脑执行的计算， 控制眼球运动。视觉是一种主动的感觉，对眼球运动的准确控制在视觉中起着至关重要的作用。 在视觉中的作用。小脑在控制眼球运动和眼睛的精细化方面起着关键作用 运动的准确性和精度通过视觉学习。众所周知，小脑的一部分 控制眼睛运动接收视觉和前庭感觉信息以及眼睛的复制 运动指令，并可能使用这些感觉和运动信号来指导眼功能 通过学习来改变它。然而，一些技术挑战限制了我们研究如何 不同的感觉和运动信号被整合在小脑中，以及不同的信号通路是如何被整合在小脑中的。 在学习过程中每一个都被修改，以提高视力表现。两个新开发的工具，CaMPARI 和Cal-Light，有很大的希望克服一些限制研究的技术挑战， 小脑计算。这些工具在记录和操纵神经元的能力方面提供了先进的精度 基于它们在特定任务条件下的活动。我们将（1）评估CAMPARI和Cal-light的疗效 为了选择性地靶向（“标记”）任务和活动依赖性的小脑神经元亚群， 的方式，以及（2）使用这些工具来剖析在眼科手术期间小脑执行的计算 表现和视觉技能学习。拟议工作的技术成果将是一套新的 研究小脑的实验方法，以及研究小脑的新实验策略 其他神经回路中的计算和学习。科学成果将是对人类 小脑在感觉（视觉和前庭）和运动（传出复制）上执行的计算 输入。在了解小脑如何支持精确的眼球运动方面的进展将提供 为眼科疾病制定更合理的干预措施的概念基础，以及 通常用于与小脑功能障碍相关的各种疾病。

PROJECT SUMMARY The goal of the proposed research is to implement state-of-the-art techniques for recording and manipulating neurons based on their activity in the cerebellum, to dissect the computations performed by the cerebellum to control eye movements. Vision is an active sense, and the accurate control of eye movements plays an essential role in vision. The cerebellum plays a key role in the control of eye movements, and in the refinement of eye movement accuracy and precision through oculomotor learning. It is known that the part of the cerebellum controlling eye movements receives visual and vestibular sensory information as well as copies of the eye movement commands, and presumably uses these sensory and motor signals to guide oculomotor performance and its modification by learning. However, a number of technical challenges have limited our ability to study how different sensory and motor signals are integrated in the cerebellum, and how the different signaling pathways are each modified during learning to improve oculomotor performance. Two newly developed tools, CaMPARI and Cal-Light, hold great promise to overcome some of the technical challenges that have limited studies of cerebellar computation. These tools offer advanced precision in the ability to record and manipulate neurons based on their activity during specific task conditions. We will (1) evaluate the efficacy of CAMPARI and Cal-light for selectively targeting (“tagging”), subpopulations of cerebellar neurons in a task- and activity-dependent manner, and (2) use these tools to dissect the computations implemented by the cerebellum during oculomotor performance and oculomotor skill learning. The technical outcome of the proposed work will be a new set of experimental approaches for studying the cerebellum, as well as new experimental strategies for studying computation and learning in other neural circuits. The scientific outcome will be new insights about the computations performed by the cerebellum on its sensory (visual and vestibular) and motor (efference copy) inputs. Advances in understanding how the cerebellum supports accurate eye movements will provide conceptual underpinning for developing more rational interventions for oculomotor disorders, and, more generally for the wide array of disorders associated with cerebellar dysfunction.