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使用线性和非线性连接性标记量化阿尔茨海默病患者脑电图中的同步模式。

Quantifying synchrony patterns in the EEG of Alzheimer's patients with linear and non-linear connectivity markers.

作者信息

Waser Markus, Garn Heinrich, Schmidt Reinhold, Benke Thomas, Dal-Bianco Peter, Ransmayr Gerhard, Schmidt Helena, Seiler Stephan, Sanin Günter, Mayer Florian, Caravias Georg, Grossegger Dieter, Frühwirt Wolfgang, Deistler Manfred

机构信息

AIT Austrian Institute of Technology GmbH, Vienna, Austria.

Department of Neurology, Clinical Section of Neurogeriatrics, Graz Medical University, Graz, Austria.

出版信息

J Neural Transm (Vienna). 2016 Mar;123(3):297-316. doi: 10.1007/s00702-015-1461-x. Epub 2015 Sep 28.

Abstract

We analyzed the relation of several synchrony markers in the electroencephalogram (EEG) and Alzheimer's disease (AD) severity as measured by Mini-Mental State Examination (MMSE) scores. The study sample consisted of 79 subjects diagnosed with probable AD. All subjects were participants in the PRODEM-Austria study. Following a homogeneous protocol, the EEG was recorded both in resting state and during a cognitive task. We employed quadratic least squares regression to describe the relation between MMSE and the EEG markers. Factor analysis was used for estimating a potentially lower number of unobserved synchrony factors. These common factors were then related to MMSE scores as well. Most markers displayed an initial increase of EEG synchrony with MMSE scores from 26 to 21 or 20, and a decrease below. This effect was most prominent during the cognitive task and may be owed to cerebral compensatory mechanisms. Factor analysis provided interesting insights in the synchrony structures and the first common factors were related to MMSE scores with coefficients of determination up to 0.433. We conclude that several of the proposed EEG markers are related to AD severity for the overall sample with a wide dispersion for individual subjects. Part of these fluctuations may be owed to fluctuations and day-to-day variability associated with MMSE measurements. Our study provides a systematic analysis of EEG synchrony based on a large and homogeneous sample. The results indicate that the individual markers capture different aspects of EEG synchrony and may reflect cerebral compensatory mechanisms in the early stages of AD.

摘要

我们分析了脑电图(EEG)中的几种同步性标志物与通过简易精神状态检查表(MMSE)评分衡量的阿尔茨海默病(AD)严重程度之间的关系。研究样本包括79名被诊断为可能患有AD的受试者。所有受试者均为奥地利PRODEM研究的参与者。按照统一方案,在静息状态和认知任务期间均记录EEG。我们采用二次最小二乘回归来描述MMSE与EEG标志物之间的关系。因子分析用于估计潜在数量较少的未观察到的同步性因素。这些共同因素随后也与MMSE评分相关。大多数标志物显示,随着MMSE评分从26降至21或20,EEG同步性最初会增加,之后则会下降。这种效应在认知任务期间最为显著,可能归因于大脑的代偿机制。因子分析为同步性结构提供了有趣的见解,第一个共同因素与MMSE评分相关,决定系数高达0.433。我们得出结论,对于总体样本而言,几种提议的EEG标志物与AD严重程度相关,但个体受试者之间差异较大。这些波动部分可能归因于与MMSE测量相关的波动和日常变异性。我们的研究基于一个大型且统一的样本对EEG同步性进行了系统分析。结果表明,各个标志物捕捉到了EEG同步性的不同方面,可能反映了AD早期阶段的大脑代偿机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fee/4766239/a9305255bd82/702_2015_1461_Fig1_HTML.jpg

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