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基于可靠性验证的帕金森病微状态特征分析。

Analysis of microstate features for Parkinson's disease based on reliability validation.

机构信息

Hebei Key Laboratory of Bioelectromagnetics and Neural Engineering, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300131, China; State Key Laboratory of Reliable and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China.

Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin, China.

出版信息

J Neurosci Methods. 2024 Jun;406:110115. doi: 10.1016/j.jneumeth.2024.110115. Epub 2024 Mar 24.

Abstract

BACKGROUND

Parkinson's disease (PD) is a disorder with abnormal changes in brain activity. The lack of objective indicators makes the assessment of PD progression difficult. Assessment of brain activity changes in PD may offer a potential solution.

NEW METHOD

Electroencephalogram (EEG) microstates reflect global dynamic changes in the brain. Therefore, we utilized microstates to assess changes in PD brain activity. However, the effect of epoch duration on the reliability of microstate analyses in PD is unclear. Thus, we first assessed the effect of data duration on the reliability of microstate topography and temporal features in PD and older healthy individuals. According to the reliability assessment, EEG epochs with high reliability were selected for microstate analysis in PD. Finally, we investigated the correlation between microstate features and clinical scales to determine whether these features could serve as objective indicators to evaluate PD progression.

RESULTS

Microstate analysis features that show high reliability for 3 min and above epoch durations. The topology of microstate D was significantly changed in PD compared to healthy controls, as well as the temporal features of microstates C and D. Additionally, the occurrence of C was negatively correlated with MoCA, and the duration of D was positively correlated with UPDRS.

COMPARISON WITH EXISTING METHOD(S): High reliability of PD microstate features obtained by our approach.

CONCLUSION

EEG for PD microstate analysis should be at least 3 min. Microstate analysis is expected to provide new ideas and objective indicators for assessing Parkinson's disease progression in the clinical setting.

摘要

背景

帕金森病(PD)是一种大脑活动异常的疾病。由于缺乏客观指标,PD 进展的评估较为困难。评估 PD 患者大脑活动的变化可能是一种潜在的解决方案。

新方法

脑电图(EEG)微状态反映了大脑的全局动态变化。因此,我们利用微状态来评估 PD 患者大脑活动的变化。然而,时段持续时间对 PD 患者微状态分析可靠性的影响尚不清楚。因此,我们首先评估了数据持续时间对 PD 和老年健康个体中微状态地形图和时间特征可靠性的影响。根据可靠性评估,选择具有高可靠性的 EEG 时段进行 PD 的微状态分析。最后,我们研究了微状态特征与临床量表之间的相关性,以确定这些特征是否可以作为评估 PD 进展的客观指标。

结果

微状态分析特征在 3 分钟及以上的时段持续时间内具有高可靠性。与健康对照组相比,PD 患者的微状态 D 的拓扑结构发生了显著变化,微状态 C 和 D 的时间特征也发生了变化。此外,C 的出现与 MoCA 呈负相关,D 的持续时间与 UPDRS 呈正相关。

与现有方法的比较

我们的方法获得的 PD 微状态特征具有较高的可靠性。

结论

PD 的 EEG 微状态分析应该至少持续 3 分钟。微状态分析有望为临床评估帕金森病进展提供新的思路和客观指标。

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