Beta Oscillations Suppression in a Population Model of Parkinson’s Disease by Linear Delayed Feedback Control

Parkinson’s disease (PD) is the second most prevalent degenerative neurological illness. Beta oscillations in electroencephalogram (EEG) are produced when a patient is suffering from PD. Deep brain stimulation (DBS) is one of the most successful treatments for PD, however, DBS control schemes still need improvement. In this paper, we test linear delay feedback control for DBS targeted the subthalamic nucleus (STN) or the internal globus pallidus (GPi) in a neural computing population model, describing dynamics of the cortex thalamocortical basal ganglia network. The numerical simulations show that both STNDBS and GPI-DBS can efficiently control beta oscillations of the PD state in term of frequency decrease.