Research On Synchronization And Oscillations In Interneuronal Networks

Synchronization is an important phenomenon occurring in many biological and physical systems.Synchronous rhythmic oscillations can be observed in different regions of the brain,which represent synchronized firing of neurons.Since neural oscillations are associated with many advanced brain functions,some research has also attracted considerable attention over the past few decades.Brain rhythmic oscillations not only carry information on their own,but they can also store and retrieve information through neural circuits.Gamma oscillation is an important oscillating mechanism in brain rhythmic activity,with important physiological functions,and is closely related to cognitive memory,sensory processing,and neurological diseases.Studies have shown that inhibitory interneurons play a key role in generating Gamma oscillations.Experimental analysis of hippocampus and neocortex suggests that synapses between interneurons are highly specialized and have some plasticity.Computational analysis further indicates that synaptic structures and synaptic parameters play an important role in interneuronal network oscillations.Based on the research of scientific research workers,this paper mainly constructs different neural networks,and uses Hodgkin-Huxley(H-H)model to simulate the synchronous evolution and rhythm oscillation of neurons under the corresponding network structure.The main contents and conclusions of the thesis are as follows:In the third chapter,an inhibitory interneuron network is constructed.The H-H model is used to simulate the synchronization and oscillation mechanism of small-world neuron networks.And the network topology,coupling strength,synaptic time constant,time delay and other factors will be considered in our studies.The effects of time delay on the synchrony behavior and neural oscillations of the inhibitory synaptic coupled neuron network were studied.The calculation results show that the inhibitory synaptic time delay plays an important role in regulating the firing pattern in the interneuronal network.As the time delay increases,the neural network changes from spiking to bursting,and then the number of bursting in the cluster increases with time delay.According to the oscillation of the neural network,the results show that the neural network is affected by the time delay,and the mixed oscillation mode appears.When the time delay is small,it is mainly the low frequency oscillation.When the time delay is large,there are high frequency oscillation and low frequency oscillation.In both modes,the high frequency is mainly Gamma oscillation,and the low frequency is Theta oscillation.In the fourth chapter,the mechanism of synchronization and oscillation in the balanced neuron network composed of excitatory neurons and inhibitory neurons is studied.Based on the H-H model,the Excitatory-inhibitory(E-I)balanced network is established.The effects of neural network synchronization on various factors such as synaptic coupling strength,network topology and external input current in E-I balanced network are studied.For the role of inhibitory neurons in the E-I network,we compared the excitatory neuron network with the E-I balanced network,demonstrating that inhibitory neurons have a role in promoting synchronization in E-I balanced network.In addition,we also studied the effect of external currents on the E-I neuron balanced network.Different external currents will cause different degrees of synchronization.Choosing the input current at the appropriate frequency is the key to enhancing the synchronization of complex neural networks.The numerical simulation structure proves that the synchronization state of the neural network is better when the frequency of the external input current is in the gamma interval.For the oscillation rhythm of E-I neuron network,numerical simulations show that the neural network oscillation is mainly gamma oscillation,in which the coupling intensity of inhibitory neurons connected with excitatory neurons has a great influence on Gamma oscillation.In the fifth chapter,based on the cluster structure of mammalian cerebral cortex,a modular neural network is constructed.The model is still an H-H neuron model,and the type of neurons is inhibitory neurons.First,a neural network composed of two modular subnetworks is constructed,and each module has the same number of neurons.The effects of intra-module neuron coupling strength and neuron coupling strength between modules on neural network synchronization are studied.In addition,the edge adding probability of the small-world network between module neurons is studied for neural network synchronization.