Independent Components Analysis “Artifact Correction” Distorts EEG Phase in Artifact Free Segments

Thatcher Rw, Palmero-Soler E, North Dm, Otte G
{"title":"Independent Components Analysis “Artifact Correction” Distorts EEG Phase in Artifact Free Segments","authors":"Thatcher Rw, Palmero-Soler E, North Dm, Otte G","doi":"10.16966/2379-7150.172","DOIUrl":null,"url":null,"abstract":"EEG artifact is defined as any electrical potential that is not produced by the brain, e.g., eye movement or head movement or muscle, 50 Hz-60 Hz line noise, etc. The most commonly used method of artifact elimination from an EEG recording is to delete the parts of the EEG recording that contain artifact and thereby leave the artifact free parts of the recording unchanged. Recently, Independent Components Analysis (ICA) has been used to decompose the original EEG into a set of components and then subjectively identify components that statistically load on one or more Independent Components (ICs) and using a smaller set of ICs then replace the original EEG recording with a different time series referred to as the ICA replacement or ICA-R. The purpose of this study is to mathematically and empirically test the distortion of the artifact free parts of the EEG when using ICA-R to replace the entire EEG digital record. The results of Joint-Time-Frequency-Analysis (JTFA) and the FFT spectral analyses demonstrated that ICA-Replacement of the original EEG produced phase distortions at each and every time point of the recording between all channel pairs. In contrast, the standard method of deleting the segments of an EEG recording that contain artifact did not distort the artifact free segments of the EEG recording. Conclusions are that ICA Replacement (ICA-R) is a severe distortion of the phase differences and time differences of the electrophysiology of the human scalp recorded Electroencephalogram (EEG) and invalidates all subsequent analyses that rely upon the imaginary part of the crossspectrum including scalp coherence, phase and network analyses that are dependent on the physics of electrical and magnetic fields.","PeriodicalId":91328,"journal":{"name":"Journal of neurology and neurobiology","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of neurology and neurobiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.16966/2379-7150.172","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

EEG artifact is defined as any electrical potential that is not produced by the brain, e.g., eye movement or head movement or muscle, 50 Hz-60 Hz line noise, etc. The most commonly used method of artifact elimination from an EEG recording is to delete the parts of the EEG recording that contain artifact and thereby leave the artifact free parts of the recording unchanged. Recently, Independent Components Analysis (ICA) has been used to decompose the original EEG into a set of components and then subjectively identify components that statistically load on one or more Independent Components (ICs) and using a smaller set of ICs then replace the original EEG recording with a different time series referred to as the ICA replacement or ICA-R. The purpose of this study is to mathematically and empirically test the distortion of the artifact free parts of the EEG when using ICA-R to replace the entire EEG digital record. The results of Joint-Time-Frequency-Analysis (JTFA) and the FFT spectral analyses demonstrated that ICA-Replacement of the original EEG produced phase distortions at each and every time point of the recording between all channel pairs. In contrast, the standard method of deleting the segments of an EEG recording that contain artifact did not distort the artifact free segments of the EEG recording. Conclusions are that ICA Replacement (ICA-R) is a severe distortion of the phase differences and time differences of the electrophysiology of the human scalp recorded Electroencephalogram (EEG) and invalidates all subsequent analyses that rely upon the imaginary part of the crossspectrum including scalp coherence, phase and network analyses that are dependent on the physics of electrical and magnetic fields.
独立分量分析“伪影校正”使无伪影段的脑电信号相位失真
EEG伪影被定义为不是由大脑产生的任何电位,例如,眼球运动或头部运动或肌肉,50 Hz-60 Hz线路噪声等。从脑电图记录中消除伪影最常用的方法是删除脑电图记录中包含伪影的部分,从而使记录中不含伪影的部分保持不变。近年来,独立分量分析(Independent Components Analysis, ICA)被用于将原始EEG分解为一组分量,然后主观地识别出统计上负载在一个或多个独立分量(Independent Components, ic)上的分量,然后使用较小的独立分量(Independent Components, ic)集用不同的时间序列替换原始EEG记录,称为ICA替换或ICA- r。本研究的目的是在数学上和经验上测试使用ICA-R取代整个EEG数字记录时脑电图无伪影部分的失真。联合时频分析(joint time - frequency analysis, JTFA)和FFT频谱分析的结果表明,ICA-Replacement对原始脑电图在记录的所有信道对之间的每个时间点都会产生相位畸变。相反,删除包含伪影的EEG记录片段的标准方法不会扭曲EEG记录的无伪影片段。结论是ICA替代(ICA- r)是对人类头皮脑电图(EEG)电生理学记录的相位差和时间差的严重扭曲,并使所有依赖于交叉谱虚部的后续分析无效,包括依赖于电场和磁场物理的头皮相干性、相位和网络分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信