Extracting multisource brain activity from a single electromagnetic channel
Extracting multisource brain activity from a single electromagnetic channel
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DOI：
10.1016/s0933-3657(03)00037-x
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发表时间：
2003-05-01
影响因子：
7.5
通讯作者：
Lowe, D
中科院分区：
文献类型：
--
作者：
James, CJ;Lowe, D
本文开发了一种方法，用于提取多个频段的脑活动，仅使用单通道记录的电磁（EM）脑信号。测量的脑电图（EEG）和脑磁图（MEG）信号被用来证明从单通道记录提取多个脑电活动的方法的实用性。该方法的核心是动态嵌入（DE），其中首先从测量信号的一系列延迟向量中构造出适当的嵌入矩阵。嵌入矩阵包含了我们需要的信息，但它是一种混合形式，因此需要被解构。特别是，我们演示了如何一种形式的独立成分分析（伊卡）上执行的嵌入矩阵可以解构成其潜在的信息组件的单通道记录。组件被视为一个方便的扩展基础，然后使用主观方法来识别与应用程序相关的感兴趣的组件。该框架已被应用于单通道的EEG和MEG记录，并显示出隔离多个来源的活动，其中包括：（i）人为成分，如眼睛，心电图和电极伪影，（ii）癫痫发作的EEG记录的组成部分，和（iii）θ波段，投票率相关，活动在MEG记录。结果在神经生理学环境中是直观和有意义的。(C)2003 Elsevier Science B.V.保留所有权利。
This paper develops a methodology for the extraction of multisource brain activity using only single channel recordings of electromagnetic (EM) brain signals. Measured electroencephalogram (EEG) and magnetoencephalogram (MEG) signals are used to demonstrate the utility of the method on extracting multisource activity from a single channel recording. At the heart of the method is dynamical embedding (DE) where first an appropriate embedding matrix is constructed out of a series of delay vectors from the measured signal. The embedding matrix contains the information we require, but in a mixed form which therefore needs to be deconstructed. In particular, we demonstrate how one form of independent component analysis (ICA) performed on the embedding matrix can deconstruct the single channel recording into its underlying informative components. The components are treated as a convenient expansion basis and subjective methods are then used to identify components of interest relevant to the application. The framework has been applied to single channels of both EEG and MEG recordings and is shown to isolate multiple sources of activity which includes: (i) artifactual components such as ocular, electrocardiographic and electrode artefact, (ii) seizure components in epileptic EEG recordings, and (iii) theta band, turnout related, activity in MEG recordings. The results are intuitive and meaningful in a neurophysiological setting. (C) 2003 Elsevier Science B.V. All rights reserved.