Algorithms for programming DBS systems for Essential Tremor

项目摘要和摘要 特发性震颤(ET)是美国最常见的运动障碍，影响4%的成年人 年龄在40岁以上。适用于运动症状对药物难以治疗并严重损害的个人 他们的日常生活，脑深部刺激(DBS)被认为是唯一的双边治疗选择。尽管 DBS技术的最新进展，相当一部分植入DBS的ET患者将收到 由于DBS导联放置不当，震颤控制不足，而其他患者将失去治疗效果 1-2年后，部分原因是神经刺激器编程选择不灵活。有一种强大的、不断增长的 临床需要植入式DBS引导设计和编程算法，使临床医生能够更好地 在大脑内塑造电场，特别是在通过位置不佳的DBS导线进行刺激的情况下 导致低阈值副作用。我们提议的研究将整合高场磁共振成像， 纤维通路的组织神经示踪、DBS的计算模型和单细胞电生理学 一种新的半自动机器学习算法的进一步开发和实验验证方法 这有助于在假设驱动下通过定向确定特定于对象的神经刺激器设置 星展银行领衔。具体地说，我们将：1)确定与动作和姿势减少有关的神经通路 基于定向DBS导联的震颤和基于特定主题的粒子群优化算法 解剖学；2)量化与震动相关的信息在单细胞、群体和网络上的调制方式 治疗性DBS在临床前大动物模型中的水平；以及3)研究 治疗窗口(即体位和动作之间的阈值差)如何消除震颤和 副作用的出现)随着时间的推移，人类DBS治疗靶向于 小脑-丘脑-皮质网络。总而言之，该项目将(A)试验性地评估和翻译一个 为人类ET患者提供新的DBS编程算法，(B)提供更详细的神经图谱 DBS的治疗作用(对姿势和动作震颤)和副作用的潜在途径(ON 构音障碍、感觉异常、共济失调)，(C)严格研究DBS治疗震颤的机制 大脑中的单个细胞和网络水平，以及(D)探索与恶化有关的神经通路 随着时间的推移，ET患者的震颤症状。

PROJECT SUMMARY AND ABSTRACT Essential tremor (ET) is the most common movement disorder in the United States, affecting 4% of all adults over the age of 40. For individuals whose motor symptoms are refractory to medication and significantly impair their daily living, deep brain stimulation (DBS) is considered to be the only bilateral therapeutic option. Despite recent advances in DBS technology, a significant portion of ET patients with DBS implants will receive inadequate tremor control because of poorly placed DBS leads, while others will lose efficacy of the therapy after 1-2 years due in part to inflexible neurostimulator programming options. There is a strong and growing clinical need for implantable DBS lead designs and programming algorithms that can enable clinicians to better sculpt electric fields within the brain, especially in cases where stimulation through a poorly placed DBS lead results in low-threshold side-effects. Our proposed study will integrate high-field magnetic resonance imaging, histological neurotracing of fiber pathways, computational modeling of DBS, and single-cell electrophysiology methods to further develop and experimentally-validate a novel semi-automated machine learning algorithm that facilitates hypothesis-driven determination of subject-specific neurostimulator settings through directional DBS leads. Specifically, we will: 1) identify the neural pathways involved in the reduction of action and postural tremor using directional DBS leads and a novel particle swarm optimization algorithm based on subject-specific anatomy; 2) quantify how tremor-related information is modulated on the single-cell, population, and network levels by therapeutic DBS in a preclinical large-animal model of harmline-induced tremor; and 3) investigate how therapeutic windows (i.e. the threshold difference between postural and action tremor abolishment and side effect emergence) change over time with human DBS therapy targeting one or more pathways within the cerebello-thalamoc-cortical network. Together, this project will (a) experimentally evaluate and translate a novel DBS programming algorithm to human ET patients, (b) provide a much more detailed map of the neural pathways underlying the therapeutic effects of DBS (on postural and action tremor) and side effects of DBS (on dysarthria, paresthesia, ataxia), (c) rigorously investigate how DBS for treating tremor works mechanistically at the single cell and network levels within the brain, and (d) probe the neural pathways involved in the worsening of tremor symptoms for ET patients over time.