Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Technical University of Madrid (UPM), Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain.
Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Technical University of Madrid (UPM), Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain.
Prog Mol Biol Transl Sci. 2019;165:25-61. doi: 10.1016/bs.pmbts.2019.04.007. Epub 2019 May 23.
Magnetoencephalography (MEG) is a relatively modern neuroimaging technique able to study normal and pathological brain functioning with temporal resolution in the order of milliseconds and adequate spatial resolution. Although its clinical applications are still relatively limited, great advances have been made in recent years in the field of dementia and Alzheimer's disease (AD) in particular. In this chapter, we briefly describe the physiological phenomena underlying MEG brain signals and the different metrics that can be computed from these data in order to study the alterations disrupting brain activity not only in demented patients, but also in the preclinical and prodromal stages of the disease. Changes in non-linear brain dynamics, power spectral properties, functional connectivity and network topological changes observed in AD are narratively summarized in the context of the pathophysiology of the disease. Furthermore, the potential of MEG as a potential biomarker to identify AD pathology before dementia onset is discussed in the light of current knowledge and the relationship between potential MEG biomarkers and current established hallmarks of the disease is also reviewed. To this aim, findings from different approaches such as resting state or during the performance of different cognitive paradigms are discussed.Lastly, there is an increasing interest in current scientific literature in promoting interventions aimed at modifying certain lifestyles, such as nutrition or physical activity among others, thought to reduce or delay AD risk. We discuss the utility of MEG as a potential marker of the success of such interventions from the available literature.
脑磁图（MEG）是一种相对较新的神经影像学技术，能够以毫秒级的时间分辨率和足够的空间分辨率研究正常和病理脑功能。尽管其临床应用仍然相对有限，但近年来在痴呆症和阿尔茨海默病（AD）领域取得了重大进展。在本章中，我们简要描述了 MEG 脑信号背后的生理现象，以及可以从这些数据中计算出的不同指标，以便研究不仅在痴呆患者中，而且在疾病的临床前和前驱阶段扰乱大脑活动的改变。AD 中观察到的非线性大脑动力学、功率谱特性、功能连接和网络拓扑变化的变化在疾病的病理生理学背景下进行了叙述性总结。此外，还根据当前知识讨论了 MEG 作为在痴呆症发作前识别 AD 病理的潜在生物标志物的潜力，以及潜在的 MEG 生物标志物与当前确立的疾病标志物之间的关系。为此，讨论了不同方法（如静息状态或在执行不同认知范式期间）的研究结果。最后，当前科学文献中越来越关注促进旨在改变某些生活方式的干预措施，例如营养或体育活动等，这些措施被认为可以降低或延迟 AD 的风险。我们从现有文献中讨论了 MEG 作为此类干预措施成功的潜在标志物的效用。
