PD-闭环小组/神经调控治疗/Sixty-Hertz Stimulation Improves Bradykinesia and Amplifies Subthalamic Low-Frequency Oscillations

推荐理由

文章研究了不同频率的电刺激下患者的运动迟缓改善与电生理变化，推断低beta和高beta特征来自不同的神经环路，通过对不同频率刺激的响应调节生理活动。为运动迟缓的脑网络机制研究以及闭环DBS的调频策略提供了思路

文章简介
期刊	Movement Disorders
发表年份	2017
DOI	10.1002/mds.26837
类型	研究性工作
领域	神经调控治疗
引用量	{{{Citation_}}}

推荐信息
推荐人	吴雨暄
审核	於慧龄
推荐小组	PD-闭环小组

摘要

Background: The objective of this study was to investigate the hypothesis that attenuation of subthalamic nucleus (STN) alpha-/beta-band oscillations is causal to improvement in bradykinesia.

Methods: STN local field potentials from a sensing neurostimulator (Activa® PC+S; Medtronic, Inc.) and kinematics from wearable sensors were recorded simultaneously during 60- and 140-Hz deep brain stimulation (DBS) in 9 freely moving PD subjects (15 STNs) performing repetitive wrist flexion-extension. Kinematics were recorded during 20-Hz DBS in a subgroup.

Results: Both 60- and 140-Hz DBS improved the angular velocity and frequency of movement (P = 0.002 and P = 0.029, respectively, for 60 Hz; P < 0.001 and P < 0.001, respectively, for 140 Hz), but 60-Hz DBS did not attenuate beta-band power (13-30 Hz). In fact, 60-Hz DBS amplified alpha/low-beta (11-15 Hz, P = 0.007) and attenuated high-beta power (19-27 Hz, P < 0.001), whereas 140-Hz DBS broadly attenuated beta power (15-30 Hz, P < 0.001). Only 60-Hz DBS improved the regularity of angular range (P = 0.046) and 20-Hz DBS did not worsen bradykinesia. There was no correlation between beta-power modulation and bradykinesia.

Conclusions: These novel results obtained from freely moving PD subjects demonstrated that both 140- and 60-Hz DBS improved bradykinesia and attenuated high beta oscillations; however, 60-Hz DBS amplified a subband of alpha/low-beta oscillations, and DBS at a beta-band frequency did not worsen bradykinesia. Based on recent literature, we suggest that both 140- and 60-Hz DBS decouple the cortico-STN hyperdirect pathway, whereas 60-Hz DBS increases coupling within striato-STN circuitry. These results inform future algorithms for closed-loop DBS in PD.

细分领域

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