Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: A commentary on Glaser and Ruchkin, and Donchin and Heffley
Identifieur interne : 000A11 ( Istex/Corpus ); précédent : 000A10; suivant : 000A12Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: A commentary on Glaser and Ruchkin, and Donchin and Heffley
Auteurs : Wilfried ColletSource :
- Biological Psychology [ 0301-0511 ] ; 1989.
Abstract
Glaser and Ruchkin (1976) as well as Donchin and Heffley (1978) have proposed principal component varimax analysis (PCVA) for identification of event-related potential (ERP) components. In the present commentary, the assumptions on the ERP data structure of this procedure are considered. They are formalized and compared with a simpler and more restrictive hypothesized ERP data structure containing autoregressive properties. Referring to the principle of parsimony, the comparison of the two models shows the superiority of the hypothesized autoregressive structure: to fit a set of ERP data equally well, the autoregressive structure does so with considerably more parsimonious assumptions, i.e. with fewer parameters to be estimated, than the structure induced by PCVA. It is concluded that an appropriate model for the ERP data structure should take the autocorrelated nature of the ERP into account.
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DOI: 10.1016/0301-0511(89)90098-7
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<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title>Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: A commentary on Glaser and Ruchkin, and Donchin and Heffley</title><author><name sortKey="Collet, Wilfried" sort="Collet, Wilfried" uniqKey="Collet W" first="Wilfried" last="Collet">Wilfried Collet</name><affiliation><mods:affiliation>Institut für Psychologie, Rheinisch-Westfälische Technische Hochschule Aachen, D-5100 Aachen, F.R.G.</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:34F7992B52A93A74AD9840A665A3B4A2193E0F7F</idno><date when="1989" year="1989">1989</date><idno type="doi">10.1016/0301-0511(89)90098-7</idno><idno type="url">https://api.istex.fr/document/34F7992B52A93A74AD9840A665A3B4A2193E0F7F/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000A11</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000A11</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a">Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: A commentary on Glaser and Ruchkin, and Donchin and Heffley</title><author><name sortKey="Collet, Wilfried" sort="Collet, Wilfried" uniqKey="Collet W" first="Wilfried" last="Collet">Wilfried Collet</name><affiliation><mods:affiliation>Institut für Psychologie, Rheinisch-Westfälische Technische Hochschule Aachen, D-5100 Aachen, F.R.G.</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Biological Psychology</title><title level="j" type="abbrev">BIOPSY</title><idno type="ISSN">0301-0511</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1989">1989</date><biblScope unit="volume">28</biblScope><biblScope unit="issue">2</biblScope><biblScope unit="page" from="163">163</biblScope><biblScope unit="page" to="172">172</biblScope></imprint><idno type="ISSN">0301-0511</idno></series><idno type="istex">34F7992B52A93A74AD9840A665A3B4A2193E0F7F</idno><idno type="DOI">10.1016/0301-0511(89)90098-7</idno><idno type="PII">0301-0511(89)90098-7</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0301-0511</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Glaser and Ruchkin (1976) as well as Donchin and Heffley (1978) have proposed principal component varimax analysis (PCVA) for identification of event-related potential (ERP) components. In the present commentary, the assumptions on the ERP data structure of this procedure are considered. They are formalized and compared with a simpler and more restrictive hypothesized ERP data structure containing autoregressive properties. Referring to the principle of parsimony, the comparison of the two models shows the superiority of the hypothesized autoregressive structure: to fit a set of ERP data equally well, the autoregressive structure does so with considerably more parsimonious assumptions, i.e. with fewer parameters to be estimated, than the structure induced by PCVA. It is concluded that an appropriate model for the ERP data structure should take the autocorrelated nature of the ERP into account.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>Wilfried Collet</name><affiliations><json:string>Institut für Psychologie, Rheinisch-Westfälische Technische Hochschule Aachen, D-5100 Aachen, F.R.G.</json:string></affiliations></json:item></author><language><json:string>eng</json:string></language><originalGenre><json:string>Discussion</json:string></originalGenre><abstract>Glaser and Ruchkin (1976) as well as Donchin and Heffley (1978) have proposed principal component varimax analysis (PCVA) for identification of event-related potential (ERP) components. In the present commentary, the assumptions on the ERP data structure of this procedure are considered. They are formalized and compared with a simpler and more restrictive hypothesized ERP data structure containing autoregressive properties. Referring to the principle of parsimony, the comparison of the two models shows the superiority of the hypothesized autoregressive structure: to fit a set of ERP data equally well, the autoregressive structure does so with considerably more parsimonious assumptions, i.e. with fewer parameters to be estimated, than the structure induced by PCVA. It is concluded that an appropriate model for the ERP data structure should take the autocorrelated nature of the ERP into account.</abstract><qualityIndicators><score>4.062</score><pdfVersion>1.2</pdfVersion><pdfPageSize>432 x 648 pts</pdfPageSize><refBibsNative>true</refBibsNative><keywordCount>0</keywordCount><abstractCharCount>906</abstractCharCount><pdfWordCount>2466</pdfWordCount><pdfCharCount>19091</pdfCharCount><pdfPageCount>10</pdfPageCount><abstractWordCount>133</abstractWordCount></qualityIndicators><title>Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: A commentary on Glaser and Ruchkin, and Donchin and Heffley</title><pii><json:string>0301-0511(89)90098-7</json:string></pii><refBibs><json:item><host><author></author><title>Ereigniskorrelierte Potentiale: Probleme ihrer Erfassung und der Analyse ihrer Komponenten</title></host></json:item><json:item><author><json:item><name>W. Collet</name></json:item><json:item><name>E. Naumann</name></json:item></author><host><volume>21</volume><pages><last>255</last><first>254</first></pages><author></author><title>Biological Psychology</title></host><title>Is a principal component varimax analysis (PCVA) a valid model in the analysis of event-related potentials?</title></json:item><json:item><author><json:item><name>E. Donchin</name></json:item><json:item><name>E.F. Heffley</name></json:item></author><host><author></author><title>Multidisciplinary perspectives in event-related brain potential research</title></host><serie><author></author><title>Multidisciplinary perspectives in event-related brain potential research</title></serie><title>Multivariate analysis of event-related potential data: A tutorial review</title></json:item><json:item><author><json:item><name>E. Donchin</name></json:item><json:item><name>W. Ritter</name></json:item><json:item><name>W.C. McCallum</name></json:item></author><host><author></author><title>Event-related brain potentials in man</title></host><serie><author></author><title>Event-related brain potentials in man</title></serie><title>The endogenous components of the ERP</title></json:item><json:item><author><json:item><name>W.K. Estes</name></json:item></author><host><volume>12</volume><pages><last>282</last><first>263</first></pages><author></author><title>Journal of Mathematical Psychology</title></host><title>Some targets for mathematical psychology</title></json:item><json:item><host><author></author><title>Principles of neurobiological signal analysis</title></host></json:item><json:item><author><json:item><name>K.G. Jöreskog</name></json:item><json:item><name>D. Sörbom</name></json:item></author><host><author></author><title>Research Rep. 81-8</title></host><serie><author></author><title>Research Rep. 81-8</title></serie><title>LISREL V: Analysis of linear structural relationship by maximum likelihood and least squares methods</title></json:item><json:item><author><json:item><name>N.E. Loveless</name></json:item><json:item><name>M. Simpson</name></json:item><json:item><name>R. Näätänen</name></json:item></author><host><volume>24</volume><pages><last>345</last><first>340</first></pages><author></author><title>Psychophysiology</title></host><title>Frontal negative and parietal positive components of the slow wave dissociated</title></json:item><json:item><author><json:item><name>F. Rösler</name></json:item><json:item><name>D. Manzey</name></json:item></author><host><volume>13</volume><pages><last>26</last><first>3</first></pages><author></author><title>Biological Psychology</title></host><title>Principal components and varimax-rotated components in event-related potential research: Some remarks on their interpretation</title></json:item><json:item><author><json:item><name>D.G. Wastell</name></json:item></author><host><volume>13</volume><pages><last>69</last><first>51</first></pages><author></author><title>Biological Psychology</title></host><title>On the correlated nature of evoked brain activity: Biophysical and statistical considerations</title></json:item><json:item><author><json:item><name>C.C. Wood</name></json:item><json:item><name>G. McCarthy</name></json:item></author><host><volume>59</volume><pages><last>260</last><first>249</first></pages><author></author><title>Electroencephalography and Clinical Neurophysiology</title></host><title>Principal component analysis of event-related potentials: Simulation studies demonstrate misallocation of variance across components</title></json:item></refBibs><genre><json:string>article</json:string></genre><serie><language><json:string>unknown</json:string></language><title>Multidisciplinary perspectives in event-related brain potential research</title></serie><host><volume>28</volume><pii><json:string>S0301-0511(00)X0118-4</json:string></pii><pages><last>172</last><first>163</first></pages><issn><json:string>0301-0511</json:string></issn><issue>2</issue><genre><json:string>journal</json:string></genre><language><json:string>unknown</json:string></language><title>Biological Psychology</title><publicationDate>1989</publicationDate></host><publicationDate>1989</publicationDate><copyrightDate>1989</copyrightDate><doi><json:string>10.1016/0301-0511(89)90098-7</json:string></doi><id>34F7992B52A93A74AD9840A665A3B4A2193E0F7F</id><score>0.028669782</score><fulltext><json:item><extension>pdf</extension><original>true</original><mimetype>application/pdf</mimetype><uri>https://api.istex.fr/document/34F7992B52A93A74AD9840A665A3B4A2193E0F7F/fulltext/pdf</uri></json:item><json:item><extension>zip</extension><original>false</original><mimetype>application/zip</mimetype><uri>https://api.istex.fr/document/34F7992B52A93A74AD9840A665A3B4A2193E0F7F/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/34F7992B52A93A74AD9840A665A3B4A2193E0F7F/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a">Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: A commentary on Glaser and Ruchkin, and Donchin and Heffley</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>ELSEVIER</publisher><availability><p>ELSEVIER</p></availability><date>1989</date></publicationStmt><notesStmt><note>Part of this research was conducted at the University of Trier (F.R.G.). The author is grateful to Helmut Peifer and Heinrich Zacher for technical assistance, and to Professor Bartussek and Dr. Naumann for valuable discussions.</note><note>Editor's note: Timely contact with potential target authors proved difficult in the case of Drs. Glaser and Ruchkin, so I am particularly grateful to Dr. Möchs (suggested by Dr. Ruchkin), who was kind enough to produce the reply which follows this comment within a couple of weeks.</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a">Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: A commentary on Glaser and Ruchkin, and Donchin and Heffley</title><author xml:id="author-1"><persName><forename type="first">Wilfried</forename><surname>Collet</surname></persName><affiliation>Institut für Psychologie, Rheinisch-Westfälische Technische Hochschule Aachen, D-5100 Aachen, F.R.G.</affiliation></author></analytic><monogr><title level="j">Biological Psychology</title><title level="j" type="abbrev">BIOPSY</title><idno type="pISSN">0301-0511</idno><idno type="PII">S0301-0511(00)X0118-4</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1989"></date><biblScope unit="volume">28</biblScope><biblScope unit="issue">2</biblScope><biblScope unit="page" from="163">163</biblScope><biblScope unit="page" to="172">172</biblScope></imprint></monogr><idno type="istex">34F7992B52A93A74AD9840A665A3B4A2193E0F7F</idno><idno type="DOI">10.1016/0301-0511(89)90098-7</idno><idno type="PII">0301-0511(89)90098-7</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>1989</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>Glaser and Ruchkin (1976) as well as Donchin and Heffley (1978) have proposed principal component varimax analysis (PCVA) for identification of event-related potential (ERP) components. In the present commentary, the assumptions on the ERP data structure of this procedure are considered. They are formalized and compared with a simpler and more restrictive hypothesized ERP data structure containing autoregressive properties. Referring to the principle of parsimony, the comparison of the two models shows the superiority of the hypothesized autoregressive structure: to fit a set of ERP data equally well, the autoregressive structure does so with considerably more parsimonious assumptions, i.e. with fewer parameters to be estimated, than the structure induced by PCVA. It is concluded that an appropriate model for the ERP data structure should take the autocorrelated nature of the ERP into account.</p></abstract></profileDesc><revisionDesc><change when="1989">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/34F7992B52A93A74AD9840A665A3B4A2193E0F7F/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Elsevier, elements deleted: tail"><istex:xmlDeclaration>version="1.0" encoding="utf-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//ES//DTD journal article DTD version 4.5.2//EN//XML" URI="art452.dtd" name="istex:docType"></istex:docType><istex:document><converted-article version="4.5.2" docsubtype="dis"><item-info><jid>BIOPSY</jid><aid>89900987</aid><ce:pii>0301-0511(89)90098-7</ce:pii><ce:doi>10.1016/0301-0511(89)90098-7</ce:doi><ce:copyright type="unknown" year="1989"></ce:copyright></item-info><head><ce:article-footnote><ce:label>☆</ce:label><ce:note-para>Part of this research was conducted at the University of Trier (F.R.G.). The author is grateful to Helmut Peifer and Heinrich Zacher for technical assistance, and to Professor Bartussek and Dr. Naumann for valuable discussions.</ce:note-para></ce:article-footnote><ce:title>Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: A commentary on Glaser and Ruchkin, and Donchin and Heffley</ce:title><ce:author-group><ce:author><ce:given-name>Wilfried</ce:given-name><ce:surname>Collet</ce:surname></ce:author><ce:affiliation><ce:textfn>Institut für Psychologie, Rheinisch-Westfälische Technische Hochschule Aachen, D-5100 Aachen, F.R.G.</ce:textfn></ce:affiliation></ce:author-group><ce:miscellaneous>Editor's note: Timely contact with potential target authors proved difficult in the case of Drs. Glaser and Ruchkin, so I am particularly grateful to Dr. Möchs (suggested by Dr. Ruchkin), who was kind enough to produce the reply which follows this comment within a couple of weeks.</ce:miscellaneous><ce:abstract><ce:section-title>Abstract</ce:section-title><ce:abstract-sec><ce:simple-para>Glaser and Ruchkin (1976) as well as Donchin and Heffley (1978) have proposed principal component varimax analysis (PCVA) for identification of event-related potential (ERP) components. In the present commentary, the assumptions on the ERP data structure of this procedure are considered. They are formalized and compared with a simpler and more restrictive hypothesized ERP data structure containing autoregressive properties. Referring to the principle of parsimony, the comparison of the two models shows the superiority of the hypothesized autoregressive structure: to fit a set of ERP data equally well, the autoregressive structure does so with considerably more parsimonious assumptions, i.e. with fewer parameters to be estimated, than the structure induced by PCVA. It is concluded that an appropriate model for the ERP data structure should take the autocorrelated nature of the ERP into account.</ce:simple-para></ce:abstract-sec></ce:abstract></head></converted-article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo><title>Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: A commentary on Glaser and Ruchkin, and Donchin and Heffley</title></titleInfo><titleInfo type="alternative" contentType="CDATA"><title>Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: A commentary on Glaser and Ruchkin, and Donchin and Heffley</title></titleInfo><name type="personal"><namePart type="given">Wilfried</namePart><namePart type="family">Collet</namePart><affiliation>Institut für Psychologie, Rheinisch-Westfälische Technische Hochschule Aachen, D-5100 Aachen, F.R.G.</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="Discussion"></genre><originInfo><publisher>ELSEVIER</publisher><dateIssued encoding="w3cdtf">1989</dateIssued><copyrightDate encoding="w3cdtf">1989</copyrightDate></originInfo><language><languageTerm type="code" authority="iso639-2b">eng</languageTerm><languageTerm type="code" authority="rfc3066">en</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Glaser and Ruchkin (1976) as well as Donchin and Heffley (1978) have proposed principal component varimax analysis (PCVA) for identification of event-related potential (ERP) components. In the present commentary, the assumptions on the ERP data structure of this procedure are considered. They are formalized and compared with a simpler and more restrictive hypothesized ERP data structure containing autoregressive properties. Referring to the principle of parsimony, the comparison of the two models shows the superiority of the hypothesized autoregressive structure: to fit a set of ERP data equally well, the autoregressive structure does so with considerably more parsimonious assumptions, i.e. with fewer parameters to be estimated, than the structure induced by PCVA. It is concluded that an appropriate model for the ERP data structure should take the autocorrelated nature of the ERP into account.</abstract><note>Part of this research was conducted at the University of Trier (F.R.G.). The author is grateful to Helmut Peifer and Heinrich Zacher for technical assistance, and to Professor Bartussek and Dr. Naumann for valuable discussions.</note><note>Editor's note: Timely contact with potential target authors proved difficult in the case of Drs. Glaser and Ruchkin, so I am particularly grateful to Dr. Möchs (suggested by Dr. Ruchkin), who was kind enough to produce the reply which follows this comment within a couple of weeks.</note><relatedItem type="host"><titleInfo><title>Biological Psychology</title></titleInfo><titleInfo type="abbreviated"><title>BIOPSY</title></titleInfo><genre type="journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">198904</dateIssued></originInfo><identifier type="ISSN">0301-0511</identifier><identifier type="PII">S0301-0511(00)X0118-4</identifier><part><date>198904</date><detail type="volume"><number>28</number><caption>vol.</caption></detail><detail type="issue"><number>2</number><caption>no.</caption></detail><extent unit="issue pages"><start>89</start><end>198</end></extent><extent unit="pages"><start>163</start><end>172</end></extent></part></relatedItem><identifier type="istex">34F7992B52A93A74AD9840A665A3B4A2193E0F7F</identifier><identifier type="DOI">10.1016/0301-0511(89)90098-7</identifier><identifier type="PII">0301-0511(89)90098-7</identifier><recordInfo><recordContentSource>ELSEVIER</recordContentSource></recordInfo></mods></metadata></istex></record>Pour manipuler ce document sous Unix (Dilib)
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