Human Motor Control Section, NINDS, NIH, Bethesda, MD, USA.
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands.
Clin Neurophysiol. 2020 Jul;131(7):1621-1651. doi: 10.1016/j.clinph.2020.03.031. Epub 2020 Apr 21.
This manuscript is the second part of a two-part description of the current status of understanding of the network function of the brain in health and disease. We start with the concept that brain function can be understood only by understanding its networks, how and why information flows in the brain. The first manuscript dealt with methods for network analysis, and the current manuscript focuses on the use of these methods to understand a wide variety of neurological and psychiatric disorders. Disorders considered are neurodegenerative disorders, such as Alzheimer disease and amyotrophic lateral sclerosis, stroke, movement disorders, including essential tremor, Parkinson disease, dystonia and apraxia, epilepsy, psychiatric disorders such as schizophrenia, and phantom limb pain. This state-of-the-art review makes clear the value of networks and brain models for understanding symptoms and signs of disease and can serve as a foundation for further work.
这篇手稿是对大脑网络功能在健康和疾病中的理解现状的两部分描述中的第二部分。我们从这样一个概念开始，即只有通过理解大脑网络、信息在大脑中如何以及为何流动，才能理解大脑功能。第一篇手稿涉及网络分析方法，而当前这份手稿则侧重于使用这些方法来了解各种神经和精神疾病。所考虑的疾病包括神经退行性疾病，如阿尔茨海默病和肌萎缩侧索硬化症、中风、运动障碍，包括特发性震颤、帕金森病、肌张力障碍和失用症、癫痫、精神疾病，如精神分裂症和幻肢痛。这篇综述清楚地表明了网络和大脑模型在理解疾病症状和体征方面的价值，可为进一步的工作提供基础。
