The Modelling And Analysis Of Thalamic Neural Mass Model

The neural mass model can generate different types of EEG signals.By simulating the model,it can simulate various physiological activities between brain nerve cells,which helps to understand the physiological mechanism of brain neural activity,and is clinically neurological.The diagnosis,prevention and treatment of diseases are of great significance.In this paper,the thalamic neuron group model is established to analyze the influence of the parameter changes on the model output.The thalamic cortical coupled neuron group model is further constructed and the model is simulated.The genetic algorithm and the unscented Kalman filter algorithm are applied to the brain.In the neuron model of electrical signals,the physiological parameters of the model are identified,and the physiological mechanisms of brain neural activity are deeply understood to study the mechanism of the onset of Alzheimer's disease and epilepsy.Firstly,construct a single-channel basic neuron group model,analyze the influence of parameter changes in the basic neuron group model on the model output,and better understand the physiological mechanism of EEG signals;add a fast suppression loop and build a single The channel suppression loop model changes the parameters in the model,and the EEG signal can be converted between different stages of seizures through simulation.Secondly,the model of the thalamic neuron group is established.Through the simulation analysis of the thalamic model,it is found that the inhibitory synaptic gain in the model is increased or the excitatory synaptic gain is reduced,which will reduce the frequency of the alpha band of the simulated EEG signal.The results indicate that the slowing of the alpha rhythm observed in the EEG of patients with Alzheimer's disease is related to the synaptic connection parameters in the thalamus;a hypothalamic cortical coupled neuron model is proposed,which is coupled by the thalamic module and the cortical module.The effect of simulated coupling coefficient on the synaptic circuit of the brain.Simulation experiments show that the excitatory coupling coefficient of the cortical module to the thalamic module reduces the alpha frequency in the thalamus,indicating that changes in the synaptic connection parameters of the thalamus will also lead toAlzheimer's.The alpha rhythm of the disease slows down.Finally,the genetic parameters of the neuron group model were identified by genetic algorithm,and the genetic algorithm was applied to the real EEG data of patients with epilepsy.It was found that the excitatory synaptic gain during seizure was higher than the seizure interval,seizure.The inhibitory synaptic gain of the period is lower than the seizure interval,and the seizure mechanism of epilepsy is explained from the perspective of the neural model;the UKF algorithm is applied to the basic neuron model,the inhibition loop model and the thalamic model to estimate the model change with time.State and parameters to help people understand the changes in physiological parameters of the brain.