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不同小脑层间传递系数的概念:分析运动学习的计算工具。

The Concept of Transmission Coefficient Among Different Cerebellar Layers: A Computational Tool for Analyzing Motor Learning.

机构信息

Control and Intelligent Processing Center of Excellence, Human Motor Control and Computational Neuroscience Laboratory, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.

Department of Physiology, Neuroscience Research Center, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

出版信息

Front Neural Circuits. 2019 Aug 27;13:54. doi: 10.3389/fncir.2019.00054. eCollection 2019.

Abstract

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.

摘要

高度保真的小脑层间信息传递主要由突触可塑性提供。因此,确定小脑中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,为了阐明突触缺陷的影响,许多实验研究已经针对小脑功能中的特定信号通路进行了研究。然而,这些研究在行为水平上的矛盾结果进一步增加了问题的模糊性。通过相互连接的神经元群体的放电率变化来传递信息是神经编码最广泛接受的原理之一。在这项研究中,我们在考虑小脑层间突触相互作用效率的同时,提出了一个放电率模型来实现传递系数的概念。然后,我们使用计算方法测试了不同传递系数值对小脑依赖的运动学习任务增益适应的影响。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对运动学习没有相同的影响。具体来说,像在平行纤维-浦肯野细胞突触中的训练诱导 LTD 中那样的训练机制的损伤,对学习的所有方面,包括记忆形成、转移和巩固,都有显著的负面影响,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 的过度诱导虽然对基本运动性能的稳健性至关重要,但不能防止运动学习障碍。相比之下,由中间神经元和背景活动的 climbing fibers 诱导的可塑性损伤,通过过度诱导训练诱导的平行纤维-浦肯野细胞 LTD 部分得到补偿。此外,阻断 climbing fibers 到小脑皮层的信号传递,称为橄榄系统损伤,对运动学习和基本运动性能都有最具破坏性的影响。总的来说,所提出的计算框架的结果用于提供小脑程序性运动记忆形成的映射。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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2f1/6718712/d8a9b346783f/fncir-13-00054-g0001.jpg

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