Lanzhou Center for Theoretical Physics and Key Laboratory of Theoretical Physics of Gansu Province, Lanzhou University, Lanzhou, Gansu 730000, China.
Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China.
Phys Rev E. 2021 Feb;103(2-1):022312. doi: 10.1103/PhysRevE.103.022312.
We investigate the occurrence of synchronous population activities in a neuronal network composed of both excitatory and inhibitory neurons and equipped with short-term synaptic plasticity. The collective firing patterns with different macroscopic properties emerge visually with the change of system parameters, and most long-time collective evolution also shows periodic-like characteristics. We systematically discuss the pattern-formation dynamics on a microscopic level and find a lot of hidden features of the population activities. The bursty phase with power-law distributed avalanches is observed in which the population activity can be either entire or local periodic-like. In the purely spike-to-spike synchronous regime, the periodic-like phase emerges from the synchronous chaos after the backward period-doubling transition. The local periodic-like population activity and the synchronous chaotic activity show substantial trial-to-trial variability, which is unfavorable for neural code, while they are contrary to the stable periodic-like phases. We also show that the inhibitory neurons can promote the generation of cluster firing behavior and strong bursty collective firing activity by depressing the activities of postsynaptic neurons partially or wholly.
我们研究了由兴奋性和抑制性神经元组成并具有短期突触可塑性的神经网络中同步种群活动的发生。随着系统参数的变化，具有不同宏观特性的集体发射模式在视觉上显现出来，并且大多数长时间的集体演化也表现出类似周期性的特征。我们在微观层面上系统地讨论了模式形成动力学，并发现了许多种群活动的隐藏特征。在爆发式相位中，幂律分布的阵发事件观察到，其中种群活动可以是整体或局部类似周期性的。在纯粹的尖峰到尖峰同步状态下，局部周期性种群活动和同步混沌活动在向后的倍周期过渡后从同步混沌中出现。局部周期性的群体活动和同步混沌活动表现出大量的试验间变异性，这不利于神经码，而与稳定的周期性阶段相反。我们还表明，抑制性神经元可以通过部分或完全抑制突触后神经元的活动来促进簇状发射行为和强烈爆发性集体发射活动的产生。
