School of Computer Science and Technology, Xidian University, Xi'an, China.
School of Telecommunication Engineering, Xidian University, Xi'an, China.
PLoS Comput Biol. 2021 Feb 10;17(2):e1008670. doi: 10.1371/journal.pcbi.1008670. eCollection 2021 Feb.
The dynamics of cerebellar neuronal networks is controlled by the underlying building blocks of neurons and synapses between them. For which, the computation of Purkinje cells (PCs), the only output cells of the cerebellar cortex, is implemented through various types of neural pathways interactively routing excitation and inhibition converged to PCs. Such tuning of excitation and inhibition, coming from the gating of specific pathways as well as short-term plasticity (STP) of the synapses, plays a dominant role in controlling the PC dynamics in terms of firing rate and spike timing. PCs receive cascade feedforward inputs from two major neural pathways: the first one is the feedforward excitatory pathway from granule cells (GCs) to PCs; the second one is the feedforward inhibition pathway from GCs, via molecular layer interneurons (MLIs), to PCs. The GC-PC pathway, together with short-term dynamics of excitatory synapses, has been a focus over past decades, whereas recent experimental evidence shows that MLIs also greatly contribute to controlling PC activity. Therefore, it is expected that the diversity of excitation gated by STP of GC-PC synapses, modulated by strong inhibition from MLI-PC synapses, can promote the computation performed by PCs. However, it remains unclear how these two neural pathways are interacted to modulate PC dynamics. Here using a computational model of PC network installed with these two neural pathways, we addressed this question to investigate the change of PC firing dynamics at the level of single cell and network. We show that the nonlinear characteristics of excitatory STP dynamics can significantly modulate PC spiking dynamics mediated by inhibition. The changes in PC firing rate, firing phase, and temporal spike pattern, are strongly modulated by these two factors in different ways. MLIs mainly contribute to variable delays in the postsynaptic action potentials of PCs while modulated by excitation STP. Notably, the diversity of synchronization and pause response in the PC network is governed not only by the balance of excitation and inhibition, but also by the synaptic STP, depending on input burst patterns. Especially, the pause response shown in the PC network can only emerge with the interaction of both pathways. Together with other recent findings, our results show that the interaction of feedforward pathways of excitation and inhibition, incorporated with synaptic short-term dynamics, can dramatically regulate the PC activities that consequently change the network dynamics of the cerebellar circuit.
小脑神经元网络的动力学受神经元及其之间突触的基本构建块控制。对于小脑皮层的唯一输出细胞浦肯野细胞 (PCs) 的计算,是通过各种类型的神经通路相互作用实现的,这些通路将兴奋和抑制汇聚到 PCs 上。这种兴奋和抑制的调谐,来自于特定通路的门控以及突触的短期可塑性 (STP),在控制 PC 的发射率和尖峰定时方面起着主导作用。PCs 从两个主要的神经通路接收级联前馈输入:第一个是来自颗粒细胞 (GCs) 到 PCs 的前馈兴奋性通路;第二个是来自 GCs 的前馈抑制通路,通过分子层中间神经元 (MLIs) 到 PCs。GC-PC 通路,以及兴奋性突触的短期动力学,在过去几十年一直是研究的焦点,而最近的实验证据表明,MLIs 也极大地有助于控制 PC 的活动。因此,预计由 GC-PC 突触的 STP 门控引起的兴奋多样性,由 MLI-PC 突触的强抑制调制,可以促进 PCs 执行的计算。然而,目前尚不清楚这两种神经通路如何相互作用来调节 PC 的动力学。在这里,我们使用安装有这两种神经通路的 PC 网络的计算模型来解决这个问题,以研究单个细胞和网络层面上 PC 动力学的变化。我们表明,兴奋性 STP 动力学的非线性特征可以显著调节抑制介导的 PC 尖峰动力学。PC 放电率、放电相位和时间尖峰模式的变化,受到这两个因素的强烈调制,方式各不相同。MLIs 主要通过兴奋 STP 调制来贡献 PC 后突触动作电位的可变延迟。值得注意的是,PC 网络中的同步和暂停响应的多样性不仅取决于兴奋和抑制的平衡,还取决于突触 STP,这取决于输入爆发模式。特别是,只有在两种途径相互作用的情况下,PC 网络中才会出现暂停响应。结合其他最近的发现,我们的结果表明,兴奋和抑制的前馈通路的相互作用,结合突触的短期动力学,可以显著调节 PC 的活动,从而改变小脑回路的网络动力学。