Synchronization Analysis Of A Class Of Complex Biological Neural Network

Complex network research spans many different fields such as mathematical disciplines, life science and engineering disciplines, the understanding of extremely complex topology of biological network and network dynamics has become the key subject of life science in the21st century. Synchronization is an important direction of the complex network research, the research on dynamics of mammalian brain is the goal of modern neuroscience. Therefore, combining synchronous with biological neural network, this paper applies the method of complex network research on biological neural networks, adaptive synchronization method was proposed based on dynamic coupling, with the help of Matlab to simulate the mammalian brain cortex dynamic behavior of the nervous system.In this paper, we study the mammal cat brain cortex neural network, the network contains visual (V), auditory (A), somato-motoric (SM) and fronto-limbic (FL) of four interconnected sub function, gives each node in the network nonlinear chaotic behavior of Rossler system dynamic performance, and expressed single neurons dynamic behavior nonlinear system of differential equations.In this paper, research work mainly includes the following aspects:first, in this paper, based on the dynamic coupling, is proposed based on adaptive synchronization strategy of nodes and adaptive synchronization strategy based on edge. The simulation results show that the adaptive dynamic coupling synchronization is better than that of static coupling synchronization strategies, and under the condition of the same coupling, based on the adaptive node coupling is superior to the adaptive coupling synchronization strategy based on edge. Secondly, study the effect of network topology characteristics on the synchronization performance, according to the node degrees, betweenness and closeness statistical properties such as the key node for network adaptive synchronization, by the Matlab simulation result:in the process of synchronization of complex network, the node features the coupling strength and network to achieve synchronization time negatively correlated trends, and degree and betweenness and similarity of the smaller node need to contribute in the process of synchronization of coupling intensity, in a separate control network to achieve synchronization with time is shorter, and the statistical properties of the larger node in achieve synchronous moment coupling strength is small, separate control network synchronization when needed for a long time; And in the process of synchronization, despite the cat cortical layer of each function area of the node number is not the same, but each area success ratio in the process of synchronization of nodes play an important role in the process of synchronization, at the same time, it illustrates the topology of the network properties influence the network synchronous ability. Finally with the help of Matlab, the synchronous coupling adjacency matrix in the process of numerical simulation and comparison based on nodes and the dynamic coupling synchronization strategies based on the edge of the two kinds of synchronization effect, draw the conclusion:biological network synchronization and dynamic clustering is to follow the topology of the organism itself, and the conclusion proves that numerical simulation is also a kind of can reconstruct and understand the dynamic behavior of a kind of method of the brain.This paper for complex network synchronization research provides a new clue, at the same time, this paper proves that the dynamic behavior of the network follows the topology of the organism itself, the numerical simulation is also a kind of new method of dynamic behavior to explore brain, also has important significance for research in the field of biological.