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

项目摘要/摘要 肌张力障碍是一种以持续或重复的肌肉运动为特征的致残性神经疾病。 导致不正常的动作或姿势。记录了研究局部场势(LFP)的研究 来自脑深部刺激(DBS)-使用慢性电刺激直接电刺激皮质下大脑结构 植入电极-导联在肌张力障碍患者中的临床或围手术期记录 是在执行受限的动作。这些研究的特点是病理性增加的低- 频率活动[即，θ(3-8赫兹)]及其与肌张力障碍症状的关系。然而，功能性的 这一活动的相关性仍然难以捉摸并且最近的发现已经暗示额外的振荡(例如， 微调或窄带伽马)可能与病理生理学有关。此应用程序的目标是 以数据驱动的方式确定跨基底节和皮质的肌张力障碍的个性化LFP生物标记物， 同时揭示了DBS期间生物标志物的波动与症状抑制之间的关系。我们会 使用第二代研究、双向设备(美敦力RC+S)实现这一点，该设备允许 当患者在家中时，美国将长期感知LFP并提供DBS治疗。这些小说 录音和设备提供了对复杂生物标记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，最终改善电流 神经刺激疗法。我们的中心假设是自然主义的神经记录，特别是那些 结合多模式信号采集(即视频运动学)记录大脑皮层和大脑皮层下 和加速)，可以检测到肌张力障碍症状的个性化生物标志物，这可以照亮我们的网络 了解疾病及其症状表现，同时帮助优化DBS治疗。在……里面 目的1，我们将识别和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下记录的肌张力障碍患者。我们将对病理状态进行解码 监督和自我监督的机器学习技术。在目标2中，我们将确定个性化的力量 慢性皮质下和皮质下肌张力障碍患者脑深部刺激时调节的条带 并利用这些关系来优化刺激编程。这项研究具有重要的意义 创新是因为它将是第一个研究肌张力障碍影响的慢性、多部位LFP记录范例 使用美敦力的苍白球LFP、皮质LFP和皮质下-皮质相互作用的症状和DBS RC+S，提供了有关肌张力障碍的基底节和皮质功能、网络相互作用的大量信息 以及星展银行的机制。最后，我们的目标是将这一范例扩展到商业化的、支持感知的 DBS设备--走向个性化神经调节的初步步骤。

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.