Oscillation suppression effects of intermittent noisy deep brain stimulation induced by coordinated reset pattern based on a computational model

Noisy stimulation (NS) has been proposed to alleviate the pathological state in a computational model of Parkinson's disease. Based on a resonance effect, NS modulates the neural firing pattern so as to suppress the excessive beta (12-35 Hz) synchronization and improve the relay reliability of the thalamus. However, in common with clinically-used pulsed high-frequency stimulation, the use of a continuous stimulation waveform for NS still may require an energy expenditure that is greater than necessary. A coordinated reset (CR) method to optimize NS is explored in this work that considers that the neural nature of the Parkinsonian condition is the enhancement of synchronization. CR methods has an advantage in disturbing the abnormal synchronous rhythm. The simulation results show that coordinated reset noisy stimulation (CRNS) can further inhibit the enhanced pathological synchronization in a basal ganglia-thalamus network model with lower energy expenditure, as compared to basic NS. Moreover, two kinds of intermittent CRNS strategies are further derived by adding and adjusting the stimulation-off phases in the CRNS strategy. It is found that m:n ON-OFF CRNS strategies and delayed CRNS may further reduce the stimulation energy cost by 21.2% and 15.3% without compromising control performance, respectively. This work provides a new insight into the optimization of deep brain stimulation and may guide a new approach to treating Parkinson's disease by optimizing the noise-induced improvement of the basal ganglia dysfunction.