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Identification of nonlinear features in cortical and subcortical signals of Parkinson's Disease patients via a novel efficient measure
NeuroImage ( IF 4.7 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.neuroimage.2020.117356
Tolga Esat Özkurt 1 , Harith Akram 2 , Ludvic Zrinzo 2 , Patricia Limousin 2 , Tom Foltynie 2 , Ashwini Oswal 3 , Vladimir Litvak 4
Affiliation  

This study offers a novel and efficient measure based on a higher order version of autocorrelative signal memory that can identify nonlinearities in a single time series. The suggested method was applied to simultaneously recorded subthalamic nucleus (STN) local field potentials (LFP) and magnetoencephalography (MEG) from fourteen Parkinson's Disease (PD) patients who underwent surgery for deep brain stimulation. Recordings were obtained during rest for both OFF and ON dopaminergic medication states. We analyzed the bilateral LFP channels that had the maximum beta power in the OFF state and the cortical sources that had the maximum coherence with the selected LFP channels in the alpha band. Our findings revealed the inherent nonlinearity in the PD data as subcortical high beta (20 - 30 Hz) band and cortical alpha (8 - 12 Hz) band activities. While the former was discernible without medication (p=0.015), the latter was induced upon the dopaminergic medication (p<6.10-4). The degree of subthalamic nonlinearity was correlated with contralateral tremor severity (r=0.45, p=0.02). Conversely, for the cortical signals nonlinearity was present for the ON medication state with a peak in the alpha band and correlated with contralateral akinesia and rigidity (r=0.46, p=0.02). This correlation appeared to be independent from that of alpha power and the two measures combined explained 34 % of the variance in contralateral akinesia scores. Our findings suggest that particular frequency bands and brain regions display nonlinear features closely associated with distinct motor symptoms and functions.

中文翻译:


通过一种新颖的有效方法识别帕金森病患者皮质和皮质下信号的非线性特征



这项研究提供了一种基于自相关信号存储器的高阶版本的新颖有效的测量方法,可以识别单个时间序列中的非线性。建议的方法适用于同时记录 14 名接受深部脑刺激手术的帕金森病 (PD) 患者的丘脑底核 (STN) 局部场电位 (LFP) 和脑磁图 (MEG)。在休息期间获得多巴胺能药物关闭和开启状态的记录。我们分析了在关闭状态下具有最大 β 功率的双边 LFP 通道以及与 α 波段中选定的 LFP 通道具有最大一致性的皮质源。我们的研究结果揭示了 PD 数据中固有的非线性,即皮质下高 β (20 - 30 Hz) 频带和皮质 α (8 - 12 Hz) 频带活动。虽然前者无需药物治疗即可辨别(p=0.015),但后者是在多巴胺能药物治疗后诱导的(p<6.10-4)。丘脑底非线性程度与对侧震颤严重程度相关(r=0.45,p=0.02)。相反,对于皮质信号,ON 药物状态存在非线性,在 α 波段出现峰值,并与对侧运动不能和僵化相关(r=0.46,p=0.02)。这种相关性似乎与 α 功率的相关性无关,这两种测量结合起来解释了对侧运动不能得分的 34% 的方差。我们的研究结果表明,特定频段和大脑区域表现出与不同运动症状和功能密切相关的非线性特征。
更新日期:2020-12-01
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