Chauvet G
Biol Cybern. 1986;55(2-3):201-9. doi: 10.1007/BF00341934.
A quantitative model of cerebellar cortical function is described with a complete formalization based on (i) the topology of cerebellar cortical neuronal network, (ii) some particular synaptic properties of cell classes in cerebellum cortex, and (iii) the dynamics of excitation in this network. For (i), a construction of functional classes around one Purkinje cell is given and their existence is discussed. For (ii), as in Marr-Albus model, the modifiability of synapses between parallel fibres and Purkinje cell is assumed. But the formalization permits to consider the consequences of such a property at the level of glomerulus (with granule cells) which is known as a complex transformation system. For (iii) habituation rules are assumed. It is shown that this method leads to some interesting properties in the functioning of cerebellar cortex. Particularly, emitting frequency along a Purkinje cell axon results from a discrimination by the system between transformed input signals and an external "noise" due to all other "contexts," and learning could be considered as the result of a conflict between a set of patterns and the transformed input signals. This model could be a basis for future numerical simulations.
本文描述了一种小脑皮质功能的定量模型，该模型基于以下三个方面进行了完整的形式化：（i）小脑皮质神经元网络的拓扑结构；（ii）小脑皮质中细胞类别的一些特定突触特性；（iii）该网络中的兴奋动力学。对于（i），给出了围绕一个浦肯野细胞构建功能类别的方法，并讨论了它们的存在性。对于（ii），与马尔-阿尔布斯模型一样，假定平行纤维与浦肯野细胞之间突触的可修饰性。但这种形式化允许在肾小球（与颗粒细胞相关）层面考虑这种特性的后果，肾小球是一个复杂的转换系统。对于（iii），假定了习惯化规则。结果表明，这种方法在小脑皮质功能中产生了一些有趣的特性。特别是，沿浦肯野细胞轴突的发放频率源于系统对转换后的输入信号与由于所有其他“背景”产生的外部“噪声”之间的区分，并且学习可以被视为一组模式与转换后的输入信号之间冲突的结果。该模型可以作为未来数值模拟的基础。
