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基于多尺度熵的阿尔茨海默病连续体的脑电图特征分析

EEG Characterization of the Alzheimer's Disease Continuum by Means of Multiscale Entropies.

作者信息

Maturana-Candelas Aarón, Gómez Carlos, Poza Jesús, Pinto Nadia, Hornero Roberto

机构信息

Biomedical Engineering Group, E.T.S.I. de Telecomunicación, Universidad de Valladolid, 47011 Valladolid, Spain.

Instituto de Investigación en Matemáticas (IMUVA), Universidad de Valladolid, 47011 Valladolid, Spain.

出版信息

Entropy (Basel). 2019 May 28;21(6):544. doi: 10.3390/e21060544.

DOI:10.3390/e21060544
PMID:33267258
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7515033/
Abstract

Alzheimer's disease (AD) is a neurodegenerative disorder with high prevalence, known for its highly disabling symptoms. The aim of this study was to characterize the alterations in the irregularity and the complexity of the brain activity along the AD continuum. Both irregularity and complexity can be studied applying entropy-based measures throughout multiple temporal scales. In this regard, multiscale sample entropy (MSE) and refined multiscale spectral entropy (rMSSE) were calculated from electroencephalographic (EEG) data. Five minutes of resting-state EEG activity were recorded from 51 healthy controls, 51 mild cognitive impaired (MCI) subjects, 51 mild AD patients (AD), 50 moderate AD patients (AD), and 50 severe AD patients (AD). Our results show statistically significant differences (-values < 0.05, FDR-corrected Kruskal-Wallis test) between the five groups at each temporal scale. Additionally, average slope values and areas under MSE and rMSSE curves revealed significant changes in complexity mainly for controls vs. MCI, MCI vs. AD and AD vs. AD comparisons (-values < 0.05, FDR-corrected Mann-Whitney -test). These findings indicate that MSE and rMSSE reflect the neuronal disturbances associated with the development of dementia, and may contribute to the development of new tools to track the AD progression.

摘要

阿尔茨海默病(AD)是一种患病率很高的神经退行性疾病,以其高度致残的症状而闻名。本研究的目的是描述在AD疾病连续过程中大脑活动的不规则性和复杂性的变化。不规则性和复杂性都可以通过在多个时间尺度上应用基于熵的测量方法来进行研究。在这方面,从脑电图(EEG)数据中计算出多尺度样本熵(MSE)和精细多尺度谱熵(rMSSE)。记录了51名健康对照者、51名轻度认知障碍(MCI)受试者、51名轻度AD患者、50名中度AD患者和50名重度AD患者5分钟的静息态EEG活动。我们的结果显示,在每个时间尺度上,五组之间存在统计学上的显著差异(p值<0.05,经FDR校正的Kruskal-Wallis检验)。此外,MSE和rMSSE曲线下的平均斜率值和面积显示,主要在对照与MCI、MCI与AD以及AD与重度AD的比较中,复杂性有显著变化(p值<0.05,经FDR校正的Mann-Whitney U检验)。这些发现表明,MSE和rMSSE反映了与痴呆症发展相关的神经元紊乱,可能有助于开发追踪AD进展的新工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/7515033/35bf5bfac208/entropy-21-00544-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/7515033/94ebc635f6cd/entropy-21-00544-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/7515033/ac237f18ff4d/entropy-21-00544-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/7515033/3ea59d11c22f/entropy-21-00544-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/7515033/35bf5bfac208/entropy-21-00544-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/7515033/94ebc635f6cd/entropy-21-00544-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/7515033/ac237f18ff4d/entropy-21-00544-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/7515033/3ea59d11c22f/entropy-21-00544-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/7515033/35bf5bfac208/entropy-21-00544-g004.jpg

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