脑电图
计算机科学
预处理器
神经影像学
人工智能
信号处理
神经科学
模式识别(心理学)
心理学
电信
雷达
作者
Mahmoud Hassan,Fabrice Wendling
标识
DOI:10.1109/msp.2017.2777518
摘要
The human brain is a large-scale network the function of which depends on dynamic interactions between spatially distributed regions. In the rapidly evolving field of network neuroscience, two unresolved challenges hold the promise of potential breakthroughs. First, functional brain networks should be identified using noninvasive and easy-to-use neuroimaging techniques. Second, the time-space resolution of these techniques should be good enough to assess the dynamics of the identified networks. Emerging evidence suggests that the electroencephalography (EEG) source-connectivity method may offer solutions to both issues, provided that scalp EEG signals are appropriately processed. Therefore, this technique's performance strongly depends on signal processing that involves various methods, such as preprocessing approaches, inverse solutions, statistical couplings between signals, and network science.
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