High-fidelity regulation of information transmission among cerebellar layers is mainly provided by synaptic plasticity. Therefore, determining the regulatory foundations of synaptic plasticity in the cerebellum and translating them to behavioral output are of great importance. To date, many experimental studies have been carried out in order to clarify the effect of synaptic defects, while targeting a specific signaling pathway in the cerebellar function. However, the contradictory results of these studies at the behavioral level further add to the ambiguity of the problem. Information transmission through firing rate changes in populations of interconnected neurons is one of the most widely accepted principles of neural coding. In this study, while considering the efficacy of synaptic interactions among the cerebellar layers, we propose a firing rate model to realize the concept of transmission coefficient. Thereafter, using a computational approach, we test the effect of different values of transmission coefficient on the gain adaptation of a cerebellar-dependent motor learning task. In conformity with the behavioral data, the proposed model can accurately predict that disruption in different forms of synaptic plasticity does not have the same effect on motor learning. Specifically, impairment in training mechanisms, like in the train-induced LTD in parallel fiber-Purkinje cell synapses, has a significant negative impact on all aspects of learning, including memory formation, transfer, and consolidation, although it does not disrupt basic motor performance. In this regard, the overinduction of parallel fiber-molecular layer interneuron LTP could not prevent motor learning impairment, despite its vital role in preserving the robustness of basic motor performance. In contrast, impairment in plasticity induced by interneurons and background activity of climbing fibers is partly compensable through overinduction of train-induced parallel fiber-Purkinje cell LTD. Additionally, blockade of climbing fiber signaling to the cerebellar cortex, referred to as olivary system lesion, shows the most destructive effect on both motor learning and basic motor performance. Overall, the obtained results from the proposed computational framework are used to provide a map from procedural motor memory formation in the cerebellum. Certainly, the generalization of this concept to other multi-layered networks of the brain requires more physiological and computational researches.

中文翻译：

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不同小脑层之间传输系数的概念：分析运动学习的计算工具。

小脑层之间信息传输的高保真调节主要由突触可塑性提供。因此，确定小脑突触可塑性的调节基础并将其转化为行为输出非常重要。迄今为止，已经进行了许多实验研究，以阐明突触缺陷的影响，同时针对小脑功能中的特定信号通路。然而，这些研究在行为层面上的矛盾结果进一步增加了问题的模糊性。通过互连神经元群的放电率变化进行信息传输是最广泛接受的神经编码原理之一。在本研究中，在考虑小脑层之间突触相互作用的功效的同时，我们提出了一种放电率模型来实现传递系数的概念。此后，使用计算方法，我们测试了不同的传输系数值对小脑依赖性运动学习任务的增益适应的影响。与行为数据一致，所提出的模型可以准确预测不同形式的突触可塑性的破坏不会对运动学习产生相同的影响。具体来说，训练机制的损伤，例如平行纤维浦肯野细胞突触中火车诱导的LTD，对学习的各个方面都有显着的负面影响，包括记忆形成、转移和巩固，尽管它不会破坏基本的运动表现。在这方面，平行纤维分子层中间神经元 LTP 的过度诱导无法防止运动学习障碍，尽管它在保持基本运动性能的稳健性方面发挥着至关重要的作用。相比之下，中间神经元和攀爬纤维的背景活动引起的可塑性损伤可以通过训练诱导的平行纤维浦肯野细胞LTD的过度诱导来部分补偿。此外，小脑皮质攀爬纤维信号传导的阻断（称为橄榄系统病变）对运动学习和基本运动表现显示出最具破坏性的影响。总体而言，从所提出的计算框架获得的结果用于提供小脑中程序运动记忆形成的地图。当然，将这个概念推广到大脑的其他多层网络需要更多的生理和计算研究。