帕金森病静息态 EEG 的频谱特征：一项基于功能数据分析的多中心研究。
Spectral features of resting-state EEG in Parkinson's Disease: A multicenter study using functional data analysis.
机构信息
Centre for Age-Related Medicine (SESAM), Stavanger University Hospital. Stavanger, Norway; Faculty of Health Sciences, University of Stavanger. Stavanger, Norway; Grupo de Neurociencias de Antioquia, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Semillero de Investigación SINAPSIS, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Semillero de Investigación NeuroCo, Universidad de Antioquia, School of Medicine & School of Engenieering. Medellín, Colombia.
Centre for Age-Related Medicine (SESAM), Stavanger University Hospital. Stavanger, Norway; Faculty of Health Sciences, University of Stavanger. Stavanger, Norway; Universidad del Valle, Grupo de Investigación en Estadística Aplicada - INFERIR, Faculty of Engineering, Santiago de Cali, Colombia; Universidad del Valle, Prevención y Control de la Enfermedad Crónica - PRECEC, Faculty of Health, Santiago de Cali, Colombia.
出版信息
Clin Neurophysiol. 2023 Jul;151:28-40. doi: 10.1016/j.clinph.2023.03.363. Epub 2023 Apr 24.
OBJECTIVE
This study aims 1) To analyse differences in resting-state electroencephalogram (rs-EEG) spectral features of Parkinson's Disease (PD) and healthy subjects (non-PD) using Functional Data Analysis (FDA) and 2) To explore, in four independent cohorts, the external validity and reproducibility of the findings using both epoch-to-epoch FDA and averaged-epochs approach.
METHODS
We included 169 subjects (85 non-PD; 84 PD) from four centres. Rs-EEG signals were preprocessed with a combination of automated pipelines. Sensor-level relative power spectral density (PSD), dominant frequency (DF), and DF variability (DFV) features were extracted. Differences in each feature were compared between PD and non-PD on averaged epochs and using FDA to model the epoch-to-epoch change of each feature.
RESULTS
For averaged epochs, significantly higher theta relative PSD in PD was found across all datasets. Also, higher pre-alpha relative PSD was observed in three of four datasets in PD patients. For FDA, similar findings were achieved in theta, but all datasets showed consistently significant posterior pre-alpha differences across multiple epochs.
CONCLUSIONS
Increased generalised theta, with posterior pre-alpha relative PSD, was the most reproducible finding in PD.
SIGNIFICANCE
Rs-EEG theta and pre-alpha findings are generalisable in PD. FDA constitutes a reliable and powerful tool to analyse epoch-to-epoch the rs-EEG.
目的
本研究旨在：1）使用功能数据分析（FDA）分析帕金森病（PD）和健康受试者（非 PD）静息态脑电图（rs-EEG）光谱特征的差异；2）在四个独立队列中，通过逐epoch FDA 和平均 epochs 方法，探索这些发现的外部有效性和可重复性。
方法
我们纳入了来自四个中心的 169 名受试者（85 名非 PD；84 名 PD）。rs-EEG 信号经过自动化流水线的组合预处理。提取传感器级相对功率谱密度（PSD）、主频（DF）和 DF 变异性（DFV）特征。在平均 epochs 上和使用 FDA 对每个特征的逐 epoch 变化建模，比较 PD 和非 PD 之间每个特征的差异。
结果
对于平均 epochs，在所有数据集上，PD 患者的 theta 相对 PSD 明显更高。此外，在四个数据集的三个中，PD 患者的前 alpha 相对 PSD 更高。对于 FDA，在 theta 中也得到了类似的发现，但所有数据集都显示了多个 epochs 中一致显著的后前 alpha 差异。
结论
广泛的 theta 增加，以及前 alpha 相对 PSD，是 PD 中最具可重复性的发现。
意义
rs-EEG theta 和前 alpha 发现可在 PD 中推广。FDA 是分析 rs-EEG 逐 epoch 的可靠且强大的工具。
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