Research On Closed-Loop DBS Method Based On Network Model

China is a large country in the production and use of pesticides.The use of pesticides can reduce the occurrence of pests and diseases,but long-term use can lead to the occurrence of neurological diseases,such as Parkinson’s disease（PD）and Alzheimer’s disease.PD is a common neurological disease that seriously endangers human health.The main cause of the disease is the loss of dopaminergic neurons in the substantia nigra.Deep brain stimulation（DBS）is the application of continuous high-frequency pulses to the brain area to relieve the symptoms of PD.At present,DBS is mainly in an open-loop form,that is,stimulation is applied with fixed-parameter high-frequency pulses,parameters cannot be adjusted in real time according to state changes.Therefore,this paper builds a closed-loop DBS control system based on the network model,selects the appropriate stimulation parameters according to the feedback signal,and realizes the automatic regulation of PD state with the optimal parameters and the least energy consumption.The main research contents of this paper are as follows:（1）Establishment of pesticide-induced PD rat mode and model validation.Introduce PD animal models and changes in related electrophysiological activities.The cortex-basal gangliathalamus network model is established,and the neuron membrane potential equation,parameter values and synaptic conductance values are defined.The neuron firing rate,firing pattern and oscillatory power of the network model are analyzed,and the cortex-basal ganglia-thalamic network is verified by comparing it with the existing PD animal models.（2）Select the closed-loop DBS feedback signal.Studies have shown that compared with the normal state,the abnormal beta band（13-35 Hz）oscillatory activity of the Globus Pallidus internal（GPi）in the PD state is increased,and the local field potential（LFP）power of the cortical characteristic frequency band is increased.Therefore,GPi nucleus beta band oscillation power and cortical characteristic band LFP power are selected as biomarkers of PD state,he feedback signal of closed-loop DBS control system.（3）The selection of closed-loop DBS controller and predictor.The fuzzy controller is selected to construct the closed-loop DBS control system;the control autoregressive model is selected as the predictor,and the difference between the beta power and the expected power at the next moment is used as the input of the fuzzy controller,which improves the closed-loop control accuracy and response speed.（4）Tracking performance test of closed-loop DBS control system.Taking the beta power of the GPi nucleus and the cortical LFP power as the feedback signals,the constant and dynamically changing reference signals are tracked,robustness test was also performed by changing network model parameters.The average stimulation frequency,relative error and response time are used as the performance evaluation indicators,select the closed-loop DBS control scheme with minimum energy consumption and optimal control effect.