Model Setting And Dynamic Analysis Of A Neuron Under Electromagnetic Radiation

The electric activities of neurons are dependent on the complex electrophysiological condition in neuronal system,and it indicates that complex electromagnetic field distributions can be detected in the nervous system.According to the Maxwell electromagnetic induction theorem,because of the effect of the internal bioelectricity of nervous system,the dynamical behavior in electric activity in each neuron can be changed.Therefore,when the neurons appear collective electrical activity or the signal propagates among a large number of neurons,the fluctuation of the internal electromagnetic field and the magnetic flux through the cell membrane should be considered.Based on the traditional Hindmarsh-Rose neuron model,flux variable is introduced to establish a four-variable neuron model that can describe the electromagnetic induction in neurons.In this new model,taking into account the effect of magnetic flow on the membrane potential,memristive current are added to the membrane potential variable.In order to investigate the dynamics of the novel model,initial state are changed,so multi-mode electric activities can be observed,this indicating that the nervous system has a memory effect.The improved three-variable HR model was used to simulate the dynamic behavior of neuronal activity under the influence of electromagnetic induction,and it can detect the mode of electrical activity in neurons when external electromagnetic radiation was applied to neurons.The improved neuron model has more bifurcation parameters and the mode of electrical activity can be selected within a large range of parameters.We found that electromagnetic radiation not only can stimulate quiescent neurons,but also can inhibit the electrical activity in neurons.Particularly,it is important to find that multi-mode electrical activities can occur alternately,and these results are consistent with biological experiments.At the same time,based on the improved neuron model,magnetic flux coupling is performed and the phase synchronization is studied on the neuron model.The effect of the time-varying electromagnetic field is described by the magnetic flux,and the coupling of the electromagnetic field is realized by the exchange of the magnetic flux.The magnetic coupling can achieve the perfect phase synchronization between the neurons.The phase synchronization of chaotic time series is detected by calculating Lyapunov exponent and Lyapunov dimension.Finally,based on a memristor network,the network synchronization behavior is studied.The network can keeps synchronization by selecting the appropriate coupling strength.And then change the network bifurcation parameters,that is to say,the network parameters from the previous value is switched to another value,Obviously,the network synchronization has been destroyed.Changing the parameters of the network,synchronization has been damaged under different level.The size of the damaged area depends on the deformation of the parameter and the diffusion period of the damage.