独立分量分析及其在脑电逆问题中的应用

Independent component analysis and its application on EEG inverse problem

由大脑头皮电压推断大脑内活动源的信息,称之为脑电逆问题。脑电逆问题的解决对于脑认识功能的研究有重要的科学意义和临床应用价值。本文首先对脑电逆问题及其主要解决方法作了简要介绍,然后介绍了独立分量分析(ICA)的工作原理、算法及其在脑电逆问题中的应用,分析了尚未解决的问题,提出ICA是一个在脑电逆问题中值得注意的研究方向。

Estimating the location and distribution of electric curren t source within the brain from the electroencephalographic(EEG)recordings is th e so called EEG inverse problem.Accurate solutions to such problem could make n eurologists gain noninvasive access to patient-specific cortical activity.This article first give a general review of EEG inverse problem and some of its mai nly solutions.Then introduces a signal process method-independent component analysis(ICA)about its theories,algorithms and applications on EEG inverse problem.At last this article points out that ICA is a useful method in deali ng with EEG inverse problem.