Recording Evoked Potentials for Closed-Loop DBS

记录闭环 DBS 诱发电位

• 批准号: 8335751
• 负责人: Warren M. Grill
• 金额: $ 33.97万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8335751
• 关键词: Action Potentials; Adult; Animal Model; Animals; Axon; Biological Markers; Brain; Cells; Characteristics; Clinical; Computer Simulation; Deep Brain Stimulation; Devices; Disease; Dose; Dystonia; Effectiveness; Electrodes; Electroencephalography; Elements; Epilepsy; Essential Tremor; Evoked Potentials; Exhibits; FDA approved; Feedback; Felis catus; Frequencies; Future; Harmaline; Human; Implant; Implanted Electrodes; Indium; Lead; Measures; Mental Depression; Modeling; Monitor; Morphologic artifacts; Movement Disorders; Operating System; Operative Surgical Procedures; Outcome; Pacemakers; Parkinson Disease; Participant; Patients; Persons; Pharmaceutical Preparations; Physiologic pulse; Population; Process; Proxy; Relative (related person); Signal Transduction; Source; Stimulus; Study models; Symptoms; Synapses; System; Testing; Thalamic structure; Time; Tremor; Validation; base; brain electrical activity; clinical efficacy; design; effective therapy; human subject; improved; innovation; insight; novel; presynaptic; relating to nervous system; research study; response; simulation

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.

描述（由申请人提供）：深部脑刺激是一种临床上有效的治疗方法，但刺激参数的选择仍然是一个重大的临床挑战，许多接受者由于参数选择非最佳而被剥夺了获益。该项目将推进一种创新方法，基于刺激过程中大脑神经信号的监测来自动选择刺激参数。我们建议首先对人类大脑信号进行记录，并将其作为深部脑刺激（DBS）有效性的可能生物标志物进行评估。 DBS - 一种植入式脑起搏器 - 是治疗特发性震颤和帕金森病的有效疗法。目前的 DBS 系统以开环方式运行；临床医生设置刺激参数，患者每天 24 小时无限期地接受不变的刺激。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，并且常常会导致次优的结果。此外，在癫痫或抑郁症的治疗等应用中，可能没有明显或立即的变化来指导刺激参数的选择。闭环 DBS 系统会自动调整参数，并以响应患者需求的方式进行调整，随着疾病的进展或对 DBS 的反应发生变化，在药物状态波动期间维持治疗，有可能改善结果随着时间的推移。该项目的目标是确定使用神经记录的可行性 活动，使用植入的相同电极来传递刺激，作为 DBS 闭环控制的反馈信号。我们将在 DBS 期间记录类似脑电图的大脑活动，并将这些信号的幅度和特征的变化与症状的变化联系起来。这些实验使用我们在动物研究中开发和验证的创新硬件以及允许直接连接 DBS 脑导联的新颖的术中设置。该结果将为脑电活动作为 DBS 有效性生物标志物的适用性提供临床验证。我们还将进行补充动物研究和计算模型，以确定构成生物标志物的神经信号的来源。研究结果将深入了解与未来 DBS 系统设计相关的 DBS 作用机制。 公共健康相关性：深部脑刺激是一种临床上有效的治疗方法，但刺激参数的选择仍然是一个重大的临床挑战，许多接受者由于参数选择非最佳而被剥夺了获益。该项目将推进一种创新方法，基于刺激过程中大脑神经信号的监测来自动选择刺激参数。