M. Grosse-Wentrup, S. Harmeling, T. Zander, N. Hill, B. Scholkopf
{"title":"如何在独立分量分析(ICA)中检测重构源的质量","authors":"M. Grosse-Wentrup, S. Harmeling, T. Zander, N. Hill, B. Scholkopf","doi":"10.1109/PRNI.2013.35","DOIUrl":null,"url":null,"abstract":"We provide a simple method, based on volume conduction models, to quantify the neurophysiological plausibility of independent components (ICs) reconstructed from EEG/MEG data. We evaluate the method on EEG data recorded from 19 subjects and compare the results with two established procedures for judging the quality of ICs. We argue that our procedure provides a sound empirical basis for the inclusion or exclusion of ICs in the analysis of experimental data.","PeriodicalId":144007,"journal":{"name":"2013 International Workshop on Pattern Recognition in Neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"How to Test the Quality of Reconstructed Sources in Independent Component Analysis (ICA) of EEG/MEG Data\",\"authors\":\"M. Grosse-Wentrup, S. Harmeling, T. Zander, N. Hill, B. Scholkopf\",\"doi\":\"10.1109/PRNI.2013.35\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We provide a simple method, based on volume conduction models, to quantify the neurophysiological plausibility of independent components (ICs) reconstructed from EEG/MEG data. We evaluate the method on EEG data recorded from 19 subjects and compare the results with two established procedures for judging the quality of ICs. We argue that our procedure provides a sound empirical basis for the inclusion or exclusion of ICs in the analysis of experimental data.\",\"PeriodicalId\":144007,\"journal\":{\"name\":\"2013 International Workshop on Pattern Recognition in Neuroimaging\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Workshop on Pattern Recognition in Neuroimaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PRNI.2013.35\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Workshop on Pattern Recognition in Neuroimaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRNI.2013.35","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
How to Test the Quality of Reconstructed Sources in Independent Component Analysis (ICA) of EEG/MEG Data
We provide a simple method, based on volume conduction models, to quantify the neurophysiological plausibility of independent components (ICs) reconstructed from EEG/MEG data. We evaluate the method on EEG data recorded from 19 subjects and compare the results with two established procedures for judging the quality of ICs. We argue that our procedure provides a sound empirical basis for the inclusion or exclusion of ICs in the analysis of experimental data.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
