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A Comprehensive Review of Magnetoencephalography (MEG) Studies for Brain Functionality in Healthy Aging and Alzheimers Disease (AD)

机译:磁脑电图(MEG)研究对健康衰老和阿尔茨海默氏病(AD)的大脑功能的全面综述

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摘要

Neural oscillations were established with their association with neurophysiological activities and the altered rhythmic patterns are believed to be linked directly to the progression of cognitive decline. Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal activity due to excellent temporal and fair amount of spatial resolution. Single channel, connectivity as well as brain network analysis using MEG data in resting state and task-based experiments were analyzed from existing literature. Single channel analysis studies reported a less complex, more regular and predictable oscillations in Alzheimer's disease (AD) primarily in the left parietal, temporal and occipital regions. Investigations on both functional connectivity (FC) and effective (EC) connectivity analysis demonstrated a loss of connectivity in AD compared to healthy control (HC) subjects found in higher frequency bands. It has been reported from multiplex network of MEG study in AD in the affected regions of hippocampus, posterior default mode network (DMN) and occipital areas, however, conclusions cannot be drawn due to limited availability of clinical literature. Potential utilization of high spatial resolution in MEG likely to provide information related to in-depth brain functioning and underlying factors responsible for changes in neuronal waves in AD. This review is a comprehensive report to investigate diagnostic biomarkers for AD may be identified by from MEG data. It is also important to note that MEG data can also be utilized for the same pursuit in combination with other imaging modalities.
机译:建立了神经振荡,并将其与神经生理活动相关联,并且据信改变的节奏模式与认知能力下降的进展直接相关。磁脑电图(MEG)是一种非侵入性技术,可记录这种神经元活动,这是由于其出色的时间和相当大的空间分辨率。从现有文献中分析了单通道,连通性以及在静止状态下使用MEG数据进行的脑网络分析以及基于任务的实验。单通道分析研究报告,阿尔茨海默氏病(AD)的振荡较不复杂,更规则且可预测,主要发生在左顶叶,颞叶和枕叶区域。对功能连通性(FC)和有效(EC)连通性分析的研究表明,与在较高频段中发现的健康对照(HC)受试者相比,AD的连通性丧失。据报道,在患海马区,后默认模式网络(DMN)和枕骨区的AD中,MEG研究的多重网络已被报道,但是由于临床文献的可用性有限,无法得出结论。 MEG中高空间分辨率的潜在利用可能会提供与深度大脑功能和AD中神经元波变化负责的潜在因素有关的信息。这篇综述是一份全面的报告,旨在研究可通过MEG数据识别出的AD诊断生物标志物。同样重要的是要注意,MEG数据也可以与其他成像方式结合用于同一追踪。

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