Coding and processing of error signals in inferior olivary-cerebellar networks

项目总结 小脑在运动控制中起着关键作用，特别是在运动学习中。最近，小脑 也与认知过程有关。事实上，小脑损伤与广泛的 神经和神经心理障碍，包括共济失调、肌张力障碍、精神分裂症和自闭症。尽管如此 明显的功能异质性，小脑微电路显著同质，无论是在其 不同的地区和不同的动物物种。因此，有人认为小脑可能 通过执行一次通用计算，然后发送 计算到其他大脑区域，包括运动和非运动。先前的工作表明，普遍存在的 由小脑执行的计算包括使用过去的经验来预测未来的事件，包括 那些是由我们自己的运动引起的。该项目的长期目标是实现全面的 对小脑如何学习做出这些预测的机械理解。重点将放在 错误信号对于提醒小脑预测是错误的并且需要更新是至关重要的。 在这项提议的三个目标中，我们检查：1)积极的预测误差(当某事出乎意料的时候 发生)，2)负预测错误(当预期的事情没有发生时)，以及3)时间- 差异预测错误(当刺激预测某件事即将发生时)。所有的实验都是 在一种新开发的跑步机设备上完成的，用于头部固定小鼠的眨眼条件调节。眨眼 选择空调作为模型系统是因为它为项目提供了许多优势：1) 与行为相关的误差信号在实验控制下，易于操作，2)基本的 条件任务可以被修改为询问关于错误信号在驱动运动学习中的作用的问题 和更高阶的联系，以及3)对处理误差信号至关重要的橄榄-小脑区域 已经被确认了。通过将眨眼调节的优雅简单性与新技术相结合 光遗传学、电生理学和双光子钙成像，拟议的实验将记录和 以前所未有的水平操纵学习过程中出现的与错误相关的神经信号 时间和细胞的特异性。这项研究可能有助于开发治疗运动障碍的新疗法。 以及与小脑功能障碍相关的认知障碍，而不是通过靶向 神经可塑性，但驱动它们的指导性错误相关信号。在这方面，委员会的具体目标是 应用程序被设计成不仅询问“小脑中错误信号的神经代码是什么”，而且还询问 “我们如何才能操纵代码来增强学习能力？”

PROJECT SUMMARY The cerebellum plays a key role in motor control, particularly in motor learning. More recently, the cerebellum has also been implicated in cognitive processing. Indeed, cerebellar damage is associated with a wide range of neurological and neuropsychatric disorders, including ataxia, dystonia, schizophrenia and autism. Despite this apparent functional heterogeneity, the cerebellar microcircuit is remarkably homogeneous, both across its different regions and across different animal species. Thus, it has been suggested that the cerebellum may accomplish its job by performing one universal computation, and then sending out the results of the computation to other brain areas, both motor and non-motor. Previous work indicates that the universal computation performed by the cerebellum involves using past experience to predict future events, including those that are caused by our own movements. The long-term objective of this project is to achieve a full mechanistic understanding of how the cerebellum learns to make these predictions. The focus will be on the error signals that are critical for alerting the cerebellum that a prediction was wrong and needs to be updated. In the three aims of this proposal, we examine: 1) positive prediction errors (when something unexpected happens), 2) negative prediction errors (when something expected doesn't happen), and 3) temporal- difference prediction errors (when a stimulus predicts that something is about to happen). All experiments are done on a newly developed treadmill apparatus for eyeblink conditioning in head-fixed mice. Eyeblink conditioning was chosen as the model system because it offers a number of advantages for the project: 1) The behaviorally-relevant error signals are under experimental control and can be easily manipulated, 2) The basic conditioning task can be modified to ask questions about the role of error signals in driving both motor learning and higher-order associations, and 3) The olivo-cerebellar regions that are critical for processing error signals have been identified. By combining the elegant simplicity of eyeblink conditioning with new technologies for optogenetics, electrophysiology, and two-photon calcium imaging, the proposed experiments will record and manipulate the error-related neural signals present during the learning process with an unprecedented level of temporal and cellular specificity. This research could help develop new therapeutic approaches to treat motor and cognitive disorders associated with cerebellar dysfunction, not by targeting molecular mechanisms of neural plasticity, but the instructive error-related signals that drive them. In this regard, the specific aims of the application are designed to ask not only “what is the neural code for error signals in the cerebellum”, but also “how can we manipulate the code to enhance learning?”.