脑电图
计算机科学
神经影像学
头皮
人工智能
同步脑电与功能磁共振
鉴定(生物学)
模式识别(心理学)
计算机视觉
神经科学
心理学
医学
植物
生物
解剖
作者
Christoph M. Michel,Bin He
出处
期刊:Oxford University Press eBooks
[Oxford University Press]
日期:2017-11-01
被引量:11
标识
DOI:10.1093/med/9780190228484.003.0045
摘要
This chapter describes methods to analyze the scalp electric field recorded with multichannel electroencephalography (EEG). With advances in high-density EEG, systems now allow fast and easy recording from 64 to 256 channels simultaneously. Pattern-recognition algorithms can characterize the topography of scalp electric fields and detect changes in topography over time and between experimental or clinical conditions. Methods for estimating the sources underlying the recorded scalp potential maps have increased the spatial resolution of EEG. The use of anatomical information in EEG source reconstruction has increased the precision of EEG source localization. Algorithms of functional connectivity applied to the source space allow determination of communication between large-scale brain networks in certain frequencies and identification of the directionality of this information flow and detection of crucial drivers in these networks. These methods have boosted the use of EEG as a functional neuroimaging method in experimental and clinical applications.
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