Liu De-Feng, Zhao Bao-Tian, Zhu Guan-Yu, Liu Yu-Ye, Bai Yu-Tong, Liu Huan-Guang, Jiang Yin, Zhang Xin, Zhang Hua, Yang An-Chao, Zhang Jian-Guo
Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Front Neurosci. 2022 Mar 3;16:795417. doi: 10.3389/fnins.2022.795417. eCollection 2022.
This study aimed to describe a synchronized intracranial electroencephalogram (EEG) recording and motion capture system, which was designed to explore the neural dynamics during walking of Parkinson's disease (PD) patients with freezing of gait (FOG). Preliminary analysis was performed to test the reliability of this system.
A total of 8 patients were enrolled in the study. All patients underwent bilateral STN-DBS surgery and were implanted with a right subdural electrode covering premotor and motor area. Synchronized electrophysiological and gait data were collected using the Nihon Kohden EEG amplifier and Codamotion system when subjects performed the Timed Up and Go (TUG) test. To verify the reliability of the acquisition system and data quality, we calculated and compared the FOG index between freezing and non-freezing periods during walking. For electrophysiological data, we first manually reviewed the scaled (five levels) quality during waking. Spectra comprising broadband electrocorticography (ECoG) and local field potential (LFP) were also compared between the FOG and non-FOG states. Lastly, connectivity analysis using coherence between cortical and STN electrodes were conducted. In addition, we also use machine learning approaches to classified FOG and non-FOG.
A total of 8 patients completed 41 walking tests, 30 of which had frozen episodes, and 21 of the 30 raw data were level 1 or 2 in quality (70%). The mean ± SD walking time for the TUG test was 85.94 ± 47.68 s (range: 38 to 190.14 s); the mean ± SD freezing duration was 12.25 ± 7.35 s (range: 1.71 to 27.50 s). The FOG index significantly increased during the manually labeled FOG period ( < 0.05). The beta power of STN LFP in the FOG period was significantly higher than that in the non-FOG period ( < 0.05), while the band power of ECoG did not exhibit a significant difference between walking states. The coherence between the ECoG and STN LFP was significantly greater in high beta and gamma bands during the FOG period compared with the shuffled surrogates ( < 0.05). Lastly, STN-LFP band power features showed above-chance performance ( < 0.01, permutation test) in identifying FOG epochs.
In this study, we established and verified the synchronized ECoG/LFP and gait recording system in PD patients with FOG. Further neural substrates underlying FOG could be explored using the current system.
本研究旨在描述一种同步颅内脑电图（EEG）记录和运动捕捉系统，该系统旨在探索帕金森病（PD）步态冻结（FOG）患者行走过程中的神经动力学。进行了初步分析以测试该系统的可靠性。
共有8名患者纳入本研究。所有患者均接受双侧丘脑底核深部脑刺激（STN-DBS）手术，并在右侧硬脑膜下植入覆盖运动前区和运动区的电极。当受试者进行定时起立行走（TUG）测试时，使用日本光电EEG放大器和Codamotion系统收集同步的电生理和步态数据。为了验证采集系统的可靠性和数据质量，我们计算并比较了行走过程中冻结期和非冻结期的FOG指数。对于电生理数据，我们首先在清醒时手动检查分级（五级）质量。还比较了FOG状态和非FOG状态之间包含宽带皮层脑电图（ECoG）和局部场电位（LFP）的频谱。最后，进行了使用皮层和STN电极之间相干性的连通性分析。此外，我们还使用机器学习方法对FOG和非FOG进行分类。
共有8名患者完成了41次行走测试，其中30次有冻结发作，30次原始数据中有21次质量为1级或2级（70%）。TUG测试的平均±标准差行走时间为85.94±47.68秒（范围：38至190.14秒）；平均±标准差冻结持续时间为12.25±7.35秒（范围：1.71至27.50秒）。在手动标记的FOG期间，FOG指数显著增加（<0.05）。FOG期间STN LFP的β功率显著高于非FOG期间（<0.05），而ECoG的频段功率在行走状态之间未表现出显著差异。与随机替代物相比，FOG期间ECoG和STN LFP在高β和γ频段的相干性显著更大（<0.05）。最后，STN-LFP频段功率特征在识别FOG时段方面表现出高于机会水平的性能（<0.01，置换检验）。
在本研究中，我们建立并验证了用于PD伴FOG患者的同步ECoG/LFP和步态记录系统。使用当前系统可以进一步探索FOG潜在的神经基质。
