预处理器
计算机科学
脑电图
脑磁图
软件
工作流程
R包
数据挖掘
软件包
文档
人工智能
模式识别(心理学)
心理学
数据库
程序设计语言
计算科学
精神科
作者
Alexandre Gramfort,Martin Luessi,Eric B. Larson,Denis A. Engemann,Daniel Strohmeier,Christian Brodbeck,Lauri Parkkonen,Matti Hämäläinen
出处
期刊:NeuroImage
[Elsevier]
日期:2013-10-24
卷期号:86: 446-460
被引量:1694
标识
DOI:10.1016/j.neuroimage.2013.10.027
摘要
Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time–frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne.
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