Synchronization and Rhythm Transition in a Complex Neuronal Network

Yuan Wang,Junliang Chen,Xia Shi,Bo Cheng

doi:10.1109/access.2020.2997879

Abstract

Synchronization and rhythm transition in an excitatory-inhibitory balanced cortical neuronal network are investigated in this paper. A small-world neuronal network is performed to be the cortical region of cerebral cortex, which is composed of different types of Izhikevich neurons. The combination of regular spiking (RS) cells, chattering (CH) cells, or mixed RS and CH cells are imitated as excitatory neurons, whereas fast spiking (FS) cells mimic inhibitory neurons. We mainly focus on the effect of different types of neurons on synchronization and rhythm transition of the neuronal network. The simulation results illustrate that it is easier for the neuronal network with CH excitatory neurons to achieve synchronization, and it is also more susceptible to the parameters than the network with RS neurons. Together with the weight of the synaptic connection, the structure of the small-world network is also explored to identify its influence on the synchronization and the rhythm transition. Moreover, we found that the synchronization performance could be improved by increasing the degree of influence among neurons. Importantly, the synchronization states are associated with the rhythm transitions. Especially, the consistency of synchronization of the neuronal network and y band rhythm is illustrated. In addition, our results could have an important significance on further understanding brain rhythms and synchrony in neuroscience.

Highlights

The human brain is the most sophisticated and interactive network with nontrivial topological properties, consisting of 1011 neurons, with each neuron connecting to more than 104 neurons via synapses [1], [2]
We divide the study into three different cases to discuss: (i) the network consists of excitatory regular spiking (RS) neurons and inhibitory fast spiking (FS) neurons, (ii) the network is composed of excitatory CH neurons and inhibitory FS neurons, and (iii) the network is constituted of hybrid excitatory RS and CH neurons, as well as inhibitory FS neurons
As for the connection structure, we focus on the effects of the synaptic strength of connections among excitatory neurons, and the critical parameters of the small-world network

Summary

INTRODUCTION

The human brain is the most sophisticated and interactive network with nontrivial topological properties, consisting of 1011 neurons, with each neuron connecting to more than 104 neurons via synapses [1], [2]. A computationally efficient model, proposed by Izhikevich, is chosen to simulate the individual dynamics of each neuron in the studied network This model exhibits rich and complex spiking and bursting behaviors of a single neuron with the appropriate choice of parameters, allowing us to analyze the different dynamical properties [30], [31]. More than twenty biological firing dynamics can be achieved, we wonder how different types of classic Izhikevich neurons affect the synchronization and rhythm transition in an excitatory-inhibitory balanced cortical neuronal network. For these reasons, three classical types of biological spiking neurons are selected for exploration. To the RS neuron, the FS neuron can fire in response to an injected current, but the firing frequency is even greater than 300 Hz as shown in Fig. 2(c) and Fig. 3(c)

NETWORK STRUCTURE

MEASUREMENT

RESULTS

CONCLUSION