Suppression of Beta Oscillations in a Parkinson's Disease Model by Dynamic Delayed Feedback Control

Deep brain stimulation (DBS) is the main technique for the treatment of Parkinson's disease (PD) at present. In this paper, we propose a DBS scheme based on dynamic delayed feedback control for suppression of beta oscillations in a PD model. First, we simulate normal and PD states of cerebral cortex basal nucleus thalamic neural circuit using a simplified subthalamic nucleus (STN)-external globus pallidus (GPe) neural network computational model. Then, a dynamic delayed feedback control scheme is designed to optimize the DBS technique for suppression of beta oscillations in PD state. Finally, two evaluation indexes, inhibition index and control energy index, are proposed to evaluate the control performance. It is found that, in a large range of control parameter space, the dynamic delayed feedback control scheme based DBS can effectively suppress the oscillations in the beta band of Parkinson's state.