Synchronization events in a spiking neural network

Synchronization in neural populations is one of the mechanisms of brain functioning in a normal state. However, excessive synchronization, including synchronization in large neural populations, is undesirable and, according to experimental studies, is observed in a variety of pathologies, including epilepsy. The importance and prevalence of this phenomenon attracts much attention of many researchers. Methods of mathematical modeling and the theory of dynamical systems contribute to a deeper understanding of this effect. In this paper, we propose a model of a recurrent spiking neural network with a limited excitability resource. According to the results, the model demonstrates synchronization events corresponding to the epileptic brain activity.