Recording Evoked Potentials for Closed-Loop DBS

描述（由申请人提供）：脑深部刺激是一种临床有效的治疗方法，但刺激参数的选择仍然是一个重大的临床挑战，许多接受者由于非最佳参数选择而被剥夺了益处。本项目将提出一种基于刺激过程中大脑神经信号监测的刺激参数自动选择的创新方法。我们建议首先在人类中进行大脑信号的记录，并评估它们作为深部脑刺激（DBS）有效性的可能生物标志物。DBS是一种植入大脑的起搏器，是治疗原发性震颤和帕金森病的有效方法。目前的DBS系统以开环方式运行；由临床医生设定刺激参数，患者每天24小时无限制地接受不变的刺激。刺激参数的选择是一个非系统的过程，需要大量的时间和临床专业知识，往往导致次优结果。此外，在治疗癫痫或抑郁症等应用中，可能没有明显或直接的变化来指导刺激参数的选择。闭环DBS，系统自动调整参数，并以响应患者需求的方式，有可能通过在药物状态波动期间，随着疾病的进展，或随着对DBS的反应随时间变化而保持治疗来改善结果。拟建项目的目的是确定使用神经信号记录的可行性

DESCRIPTION (provided by applicant): Deep brain stimulation is a clinically effective treatment, but the selection of the parameters of stimulation remains a significant clinical challenge and many recipients are deprived of benefit due to non-optimal parameter selection. This project will advance an innovative approach to automatic selection of stimulation parameters based on monitoring of neural signals in the brain during stimulation. We propose to conduct first in human recordings of brain signals and evaluate them as a possible biomarker for the effectiveness of deep brain stimulation (DBS). DBS - an implanted brain pacemaker - is an effective therapy for essential tremor and Parkinson's disease. Present DBS systems operate in an open-loop fashion; a clinician sets the stimulation parameters, and patients receive invariant stimulation 24 h/day indefinitely. Selection of stimulation parameters is a non- systematic process that requires substantial time and clinical expertise and often results in sub-optimal outcomes. Further, in applications like treatment of epilepsy or depression, there may be no overt or immediate changes to guide selection of stimulation parameters. Closed-loop DBS, where the system adjusts parameters automatically and in a manner responsive to the needs of the patient, has the potential to improve outcomes by maintaining treatment during fluctuations in medication status, as the disease progresses, or as the response to DBS changes over time. The objective of the proposed project is to determine the feasibility of using recordings of neural activity, obtained using the same electrodes implanted to deliver stimulation, as a feedback signal for closed-loop control of DBS. We will conduct recordings of EEG-like brain activity during DBS and correlate changes in the amplitude and character of these signals with changes in symptoms. These experiments use innovative hardware that we developed and validated in animal studies and a novel intraoperative setting that allows direct connection to the DBS brain lead. The outcome will provide clinical validation of the suitability of brain electrical activity s a biomarker for the effectiveness of DBS. We will also conduct complementary animal studies and computational modeling to determine the source(s) of the neural signals constituting the biomarker. The outcome will provide insight into the mechanisms of action of DBS relevant to the design of future DBS systems. PUBLIC HEALTH RELEVANCE: Deep brain stimulation is a clinically effective treatment, but the selection of the parameters of stimulation remains a significant clinical challenge and many recipients are deprived of benefit due to non-optimal parameter selection. This project will advance an innovative approach to automatic selection of stimulation parameters based on monitoring of neural signals in the brain during stimulation.