Understanding Circuit Dynamics in Parkinson's Disease using Real-Time Neural Control

摘要（催化剂项目） 虽然许多研究致力于了解帕金森病（PD）的病理生理学， 运动信号表现背后的神经回路动力学仍有待确定。目前的理论 建议β波段（11-35 Hz）振荡的功率和发生率，在整个基底层同步 丘脑皮质神经节（BGTC）回路与运动体征的严重程度相关。虽然变化 与左旋多巴和脑深部电刺激（DBS）相关的运动迟缓和僵硬已被证明与 关于丘脑底核（subthalamic nucleus，简称NRN）局部场电位（local field potential，简称LFP）振荡的功率， 演绎地证明了它们之间的因果关系。澄清这种关系是否是因果关系， 副现象是至关重要的，以促进我们的理解PD的病理生理。该催化剂的目标是 该项目旨在描述刚性和运动迟缓与β带振荡的关系， 它们在BGTC电路中的传播动力学。我们将利用一种新的神经控制方法， 抑制或放大特定频率的神经振荡在实时使用DBS导线。这 一种称为诱发干扰闭环DBS（eiDBS）的技术，基于以下概念： 具有精确幅度和定时的刺激可以引起调节自发神经反应 通过相长干涉或相消干涉的活动。我们将描述如何控制抑制或 通过eiDBS扩增苍白球（GPi）或延髓内段中的β带活性 与PD患者的僵硬和运动迟缓的严重程度相关。我们还将检验假设， 在β波段振荡（信息流）在GPi、PMP 1、运动（MC）、前运动（PMC） 和背外侧前额叶（DLPFC）皮质与僵硬和运动迟缓的相关性比 单独的β波段振荡幅度（目标1、2）。此外，我们将描述光谱，时间， 和空间动力学的神经反应在BGTC电路中诱发的刺激在GPi和ESTA。通过 结合诱发反应（ER）数据与高分辨率成像和计算建模，我们将 描述了GPi和GPi中不同神经元通路的激活如何影响ER动力学， 不仅优化eiDBS，而且还提供DBS作用机制的见解（目的3）。

ABSTRACT (CATALYST PROJECT) While much research has been dedicated to understanding the pathophysiology of Parkinson’s disease (PD), the neural circuit dynamics underlying the manifestation of motor signs remain to be determined. Current theories propose that the power and incidence of beta band (11-35 Hz) oscillations, synchronized throughout the basal ganglia thalamocortical (BGTC) circuit, are associated with the severity of motor signs. Although changes in bradykinesia and rigidity related to levodopa and deep brain stimulation (DBS) have been shown to correlate with the power of local field potential (LFP) oscillations in the subthalamic nucleus (STN), no study has deductively demonstrated their causal relationship. Clarifying whether this relationship is causal or epiphenomenon is critical to advance our understanding of PD pathophysiology. The goal of this Catalyst Project is to characterize the relationship of rigidity and bradykinesia with beta band oscillations and their propagation dynamics in the BGTC circuit. We will leverage a new neural control approach capable of suppressing or amplifying frequency-specific neural oscillations in real-time using DBS leads. This technique, referred to as evoked-interference closed-loop DBS (eiDBS), is based on the concept that electrical stimulation with precise amplitude and timing can evoke neural responses that modulate spontaneous neural activity via constructive or destructive interference. We will characterize how controlled suppression or amplification of beta band activity in the internal segment of the globus pallidus (GPi) or the STN via eiDBS relates to the severity of rigidity and bradykinesia in PD patients. We will also test the hypothesis that changes in the propagation of beta band oscillations (information flow) across the GPi, STN, motor (MC), premotor (PMC), and dorsolateral prefrontal (DLPFC) cortices will be better correlated with rigidity and bradykinesia than the amplitude of beta band oscillations alone (Aims 1,2). Furthermore, we will characterize the spectral, temporal, and spatial dynamics of neural responses in the BGTC circuit evoked by stimulation in the GPi and STN. By combining the evoked response (ER) data with high-resolution imaging and computational modeling, we will delineate how activation of distinct neuronal pathways in the GPi and STN influences ER dynamics, critical not only to optimize eiDBS, but also to provide insights into the mechanism(s) of action of DBS (Aim 3).