期刊
CLINICAL NEUROPHYSIOLOGY PRACTICE
卷 2, 期 -, 页码 206-213出版社
ELSEVIER
DOI: 10.1016/j.cnp.2017.09.003
关键词
Graph theory; Functional connectivity; EEG; eLORETA; Resting-state networks
Network science and graph theory applications have recently spread widely to help in understanding how human cognitive functions are linked to neuronal network structure, thus providing a conceptual frame that can help in reducing the analytical brain complexity and underlining how network topology can be used to characterize and model vulnerability and resilience to brain disease and dysfunction. The present review focuses on few pivotal recent studies of our research team regarding graph theory application in functional dynamic connectivity investigated by electroencephalographic (EEG) analysis. The article is divided into two parts. The first describes the methodological approach to EEG functional connectivity data analysis. In the second part, network studies of physiological aging and neurological disorders are explored, with a particular focus on epilepsy and neurodegenerative dementias, such as Alzheimer's disease. (C) 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据