Beyond theta: analyzing oscillations across the frequency spectrum in patients with dystonia implanted with sensing-enabled pulse generators

超越 theta：分析植入传感脉冲发生器的肌张力障碍患者的整个频谱振荡

• 批准号: 10569467
• 负责人: Stephanie Lynn Cernera
• 金额: $ 6.91万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10569467
• 关键词: Acceleration; Accelerometer; Algorithms; Basal Ganglia; Behavior; Behavioral; Biological Markers; Brain; Chronic; Clinic; Complex; Data; Data Collection; Deep Brain Stimulation; Development; Devices; Disease; Dyskinetic syndrome; Dystonia; Electric Stimulation; Electrodes; Electrophysiology (science); Frequencies; Functional disorder; Ganglia; Generations; Globus Pallidus; Goals; Home; Human; Implant; Implanted Electrodes; Label; Lead; Monitor; Motor; Motor Cortex; Movement; Movement Disorders; Muscle; Neurologic; Pathologic; Patients; Perioperative; Physiologic pulse; Physiology; Posture; Process; Quality of life; Research; Severities; Signal Transduction; Site; Structure; Symptoms; Techniques; commercialization; improved; innovation; insight; kinematics; machine learning method; motor symptom; multimodal data; multimodality; nervous system disorder; neural; neuroregulation; next generation; novel; potential biomarker; programs; supervised learning; symptomatic improvement; wearable device

Project Summary/Abstract Dystonia is a disabling neurological condition characterized by sustained or repetitive muscle movements causing abnormal movements or postures. Studies that have investigated local field potentials (LFPs) recorded from deep brain stimulation (DBS) – direct electrical stimulation of subcortical brain structures using chronically implanted electrodes – leads in dystonia patients have been in-clinic or perioperative recordings while the patient was performing constrained movements. These studies have characterized pathologically increased low- frequency activity [i.e., theta (3-8 Hz)] and its relationship to dystonic symptoms. However, the functional relevance of this activity remains elusive and recent findings have implicated that additional oscillations (e.g., finely-tuned or narrowband gamma) may be related to pathophysiology. The objective of this application is to identify individualized LFP biomarkers of dystonia in a data-driven manner across the basal ganglia and cortex, while revealing the relationship between fluctuations in biomarkers to symptom suppression during DBS. We will accomplish this using a second-generation investigational, bidirectional device (Medtronic RC+S), which allows us to chronically sense LFPs and deliver DBS therapy while patients are in at-home settings. These novel recordings and devices provide insights into complex biomarkers and naturalistic behaviors, allowing a direct comparison of individualized biomarkers to symptom monitoring or suppression. This will advance our understanding of neural changes associated with dystonia and DBS, ultimately improving current neurostimulation therapy. Our central hypothesis is that naturalistic neural recordings, specifically those recorded both cortically and subcortically in conjunction with multimodal signal acquisition (i.e., video kinematics and acceleration), can detect personalized biomarkers of dystonic symptoms that can illuminate our network understanding of the disease and its symptom manifestation, while aiding in the optimization of DBS therapy. In Aim 1, we will identify and characterize individualized power bands associated with pathological activity in patients with dystonia using chronic subcortical and cortical recordings. We will decode pathological states using supervised and self-supervised machine learning techniques. In Aim 2, we will determine personalized power bands modulated during deep brain stimulation in patients with dystonia using chronic subcortical and cortical recordings and utilize these relationships to optimize stimulation programming. This research is significant and innovative because it will be the first chronic, multisite LFP recording paradigm to study effects of dystonic symptoms and DBS on pallidal LFPs, cortical LFPs, and subcortical-cortical interactions using the Medtronic RC+S, providing ample information about basal ganglia and cortical functions, network interactions in dystonia and the mechanisms of DBS. Lastly, our goal is to expand this paradigm into commercialized, sensing-enabled DBS devices – the preliminary steps towards personalized neuromodulation.

项目概要/摘要 肌张力障碍是一种致残性神经系统疾病，其特征是持续或重复的肌肉运动 导致动作或姿势异常。记录了调查局部场电位 (LFP) 的研究 来自深部脑刺激（DBS）——长期使用直接电刺激皮层下大脑结构 植入电极——肌张力障碍患者的导联已在临床或围手术期记录，而患者 正在执行受限的动作。这些研究的特点是病理性增加的低 频率活动 [即 theta (3-8 Hz)] 及其与张力障碍症状的关系。然而，功能性 这项活动的相关性仍然难以捉摸，最近的研究结果表明，额外的振荡（例如， 微调或窄带伽玛）可能与病理生理学有关。该应用程序的目的是 以数据驱动的方式识别基底神经节和皮质的个体化肌张力障碍 LFP 生物标志物， 同时揭示了 DBS 期间生物标志物波动与症状抑制之间的关系。我们将 使用第二代研究性双向设备 (Medtronic RC+S) 来实现这一目标，该设备允许 当患者在家时，我们可以长期感知 LFP 并提供 DBS 治疗。这些小说 记录和设备提供了对复杂生物标志物和自然行为的洞察，允许直接 个体化生物标志物与症状监测或抑制的比较。这将推进我们的 了解与肌张力障碍和 DBS 相关的神经变化，最终改善当前的情况 神经刺激疗法。我们的中心假设是自然神经记录，特别是那些 结合多模态信号采集（即视频运动学）记录皮质和皮质下 和加速度），可以检测肌张力障碍症状的个性化生物标志物，从而照亮我们的网络 了解疾病及其症状表现，同时帮助优化 DBS 治疗。在 目标 1，我们将识别并表征与病理活动相关的个体化功率带 使用慢性皮质下和皮质记录的肌张力障碍患者。我们将使用解码病理状态 监督和自监督机器学习技术。在目标 2 中，我们将确定个性化的力量 使用慢性皮层下和皮质对肌张力障碍患者进行深部脑刺激期间调制的条带 记录并利用这些关系来优化刺激编程。这项研究意义重大且 创新，因为它将是第一个长期、多部位 LFP 记录范式，用于研究肌张力障碍的影响 使用美敦力 (Medtronic) 评估苍白球 LFP、皮质 LFP 和皮质下-皮质相互作用的症状和 DBS RC+S，提供有关基底神经节和皮质功能、肌张力障碍的网络相互作用的充足信息 以及星展银行的机制。最后，我们的目标是将这种范例扩展到商业化、传感功能 DBS 设备——个性化神经调节的初步步骤。