Parameter selection drives electrophysiological responses to adaptive deep brain stimulation in Parkinson’s disease

Abstract Introduction: Adaptive deep brain stimulation (DBS) aims at improving DBS therapy by adjusting amplitude in response to biomarkers tracked real-time. In Parkinson’s Disease (PD), one type of aDBS exploits fast fluctuations beta power (beta bursts) local field potentials. With this method, is applied as soon bursts a given magnitude and duration are detected. However, it unknown how performance influenced changes parameters movement states. Objectives: To explore the parameter space characterize selection affects level subthalamic activity rest during movement. Methods: A configurable LFP burst driven system was designed. This setup used conduct closed-loop 12 externalized PD patients undergoing surgery for DBS. Recordings were done with both short motor task. By systematically changing onset time upon which triggered amount smoothing real-time power, algorithm explored. Electrophysiological responses assessed frequency range. Results: Immediate stimulation-induced suppression independent from selection. patterns governed combination higher leading less frequent stimulation, especially when no applied. Global stronger shorter times but did not reach achieved continuous Beta degraded responsivity diminished parameter-dependent effects stimulation. Conclusion: The choice strongly influences neurophysiological responses. related interacts aDBS, diminishing system’s responsivity. Our results may guide thereby facilitate clinical translation Research Category Technology Methods Translational Research: 1. Deep Brain Stimulation Keywords: LFP, bursts, Parkinson's disease