Analysis Of LFP Characteristics And Parameter Estimation Of Neural Mass Model Under Transcranial Ultrasound Stimulation

Transcranial ultrasound stimulation is a non-invasive neuromodulation technique using ultrasound.Due to its high resolution,high penetration and good directivity,it has been widely used in the research of neuroscience and rehabilitation engineering in recent years.At present,studies on the regulatory effects of ultrasonic stimulation on the nervous system have been carried out from the perspectives of experimental phenomenon analysis and neural signal processing,etc.Neural computational modeling is to analyze the electrophysiological activities and the mechanism of action caused by ultrasonic stimulation through reverse modeling of measured data.Neural mass model can simulate neurons electrophysiological activity of many neurons in the cerebral cortex,fitting the measured LFP characteristics before and after ultrasonic stimulation combining with optimization algorithm,through the model parameters to analyse the regulation way of neural electrical activity of motor cortex by ultrasonic stimulation,for the study of transcranial ultrasound stimulation on the regulation mechanism of the nervous system to provide a new angle.This paper firstly introduces the development status and effects of transcranial ultrasound stimulation,and summarizes the neural computational model and its application in diseases and cranial nerve stimulation.In this paper,a neural mass model was proposed to simulate the LFP signals under ultrasonic stimulation,and to analyze the modulatory effect of ultrasonic stimulation on the brain rhythm of motor cortex in mice.The construction process of the Jansen&Rit model and the physiological significance of its parameters are discussed,and the influence of the change of model parameters on the output signal is analyzed.Secondly,the parameter adjustment method of neural mass model based on particle swarm optimization algorithm is proposed.By setting the difference between the peak frequency of the simulation signal and the target signal as the fitness function,the optimal model parameters for generating the characteristic rhythm of the EEG were obtained by simulation,and then the multi-dynamic neural mass model was constructed.Then,the experimental platform of transcranial ultrasonic stimulation is introduced,and the meaning of each parameter in the ultrasonic pulse sequence and the experimental flow of ultrasonic stimulation are described.The LFP signals under different ultrasonic stimulation parameters were collected.Wavelet time-frequency and power spectrum analysis were used to analyze the response induced by ultrasonic stimulation and the energy distribution and power changes of EEG signals before and after stimulation,which were used as the basis for the selection of signal duration and fitting features for subsequent parameter estimation.Finally,we used the parameter estimation method of neural mass model based on the particle swarm algorithm proposed in this paper and selected reasonable model estimation parameter set and fitness function and constructed effective neuron group model,and the LFP signals before and under different ultrasonic stimulation parameters were fitted and estimated respectively.The results of parameter estimation showed that the change of average synaptic gain reflected the excitatory effect of ultrasonic stimulation on the motor cortex,and the change of membrane time constant indicated that the ultrasonic stimulation could have a neuroregulatory effect on the motor cortex by affecting the ion channels and membrane structure.