We consider a cerebellar ring network for the optokinetic response (OKR), and investigate the effect of diverse recoding of granule (GR) cells on OKR by varying the connection probability $p_c$ from Golgi to GR cells. For an optimal value of $p_c^{\ast }(=0.06)$, individual GR cells exhibit diverse spiking patterns which are in-phase, anti-phase, or complex out-of-phase with respect to their population-averaged firing activity. Then, these diversely-recoded signals via parallel fibers (PFs) from GR cells are effectively depressed by the error-teaching signals via climbing fibers from the inferior olive which are also in-phase ones. Synaptic weights at in-phase PF-Purkinje cell (PC) synapses of active GR cells are strongly depressed via strong long-term depression (LTD), while those at anti-phase and complex out-of-phase PF-PC synapses are weakly depressed through weak LTD. This kind of “effective” depression (i.e., strong/weak LTD) at the PF-PC synapses causes a big modulation in firings of PCs, which then exert effective inhibitory coordination on the vestibular nucleus (VN) neuron (which evokes OKR). For the firing of the VN neuron, the learning gain degree ${\mathcal{L}}_g$, corresponding to the modulation gain ratio, increases with increasing the learning cycle, and it saturates at about the 300th cycle. By varying $p_c$ from $p_c^{\ast }$, we find that a plot of saturated learning gain degree ${\mathcal{L}}_g^{\ast }$ versus $p_c$ forms a bell-shaped curve with a peak at $p_c^{\ast }$ (where the diversity degree in spiking patterns of GR cells is also maximum). Consequently, the more diverse in recoding of GR cells, the more effective in motor learning for the OKR adaptation.

我们考虑将小脑环网络用于光动力学反应（OKR），并通过改变连接概率来研究颗粒（GR）细胞的多种编码对OKR的影响 $p_C$从高尔基到GR细胞 为的最佳值$p_C^{\ast }（=0。06）$单个GR细胞在种群平均激发活性方面表现出同相，反相或复杂异相的多种尖峰模式。然后，通过来自下橄榄的攀爬纤维（也是同相的）通过爬虫纤维发出的错误教学信号有效地抑制了来自GR细胞的通过并行纤维（PF）进行的这些不同编码的信号。活性GR细胞的同相PF-Purkinje细胞（PC）突触的突触权重通过强烈的长期抑制（LTD）受到强烈抑制，而反相和复杂异相PF-PC突触的突触权重则弱沮丧通过弱有限公司。PF-PC突触处的这种“有效”抑郁（即强/弱LTD）会引起PC放电的较大调节，进而对前庭核（VN）神经元（引起OKR）施加有效的抑制性协调作用。${\mathcal{大号}}_G$对应于调制增益比的，随着学习周期的增加而增加，并且在第300个周期时达到饱和。通过变化$p_C$ 从 $p_C^{\ast }$，我们发现一个饱和学习增益度的图 ${\mathcal{大号}}_G^{\ast }$ 与 $p_C$ 形成一个钟形曲线，在 $p_C^{\ast }$（其中GR细胞的突增模式的多样性程度也最大）。因此，GR细胞的编码越多样化，对于OKR适应的运动学习就越有效。