The regularity of the inter-spike intervals (ISIs) gives a critical window into how the information is coded temporally in the cortex. Previous researches mostly adopt pure feedforward networks (FFNs) to study how the network structure affects spiking regularity propagation, which ignore the role of local dynamics within the layer. In this paper, we construct an FFN with recurrent connections and investigate the propagation of spiking regularity. We argue that an FFN with recurrent connections serves as a basic circuit to explain that the regularity increases as spikes propagate from middle temporal visual areas to higher cortical areas. We find that the reduction of regularity is related to the decreased complexity of the shared activity co-fluctuations. We show in simulations that there is an appropriate excitation–inhibition ratio maximizing the regularity of deeper layers. Furthermore, it is demonstrated that collective temporal regularity in deeper layers exhibits resonance-like behavior with respect to both synaptic connection probability and synaptic weight. Our work provides a critical link between cortical circuit structure and realistic spiking regularity.

尖峰间隔（ISI）的规律性为了解如何在皮质中临时编码信息提供了一个重要的窗口。先前的研究大多采用纯前馈网络（FFN）来研究网络结构如何影响尖峰规律性传播，而忽略了层内局部动力学的作用。在本文中，我们构造了具有递归连接的FFN，并研究了尖峰规律性的传播。我们认为，具有递归连接的FFN可以作为基本电路来解释，随着尖峰从中间颞部视觉区域传播到更高的皮质区域，规则性会增加。我们发现规律性的降低与共享活动共波动的复杂性降低有关。我们在仿真中表明，存在适当的激发抑制比，可最大化深层的规则性。此外，已经证明，相对于突触连接概率和突触权重，更深层的集体时间规律性表现出类似共振的行为。我们的工作为皮层电路结构和现实的尖峰规律性之间提供了关键的联系。