Isolation of epileptiform discharges from unaveraged EEG by independent component analysis

Objective: We propose a method that allows the separation of epileptiform discharges (EDs) from the EEG background, including the ED's waveform and spatial distribution. The method even allows to separate a spike in two components occurring at approximately the same time but having different wa...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Clinical neurophysiology 1999-10, Vol.110 (10), p.1755-1763
Hauptverfasser: Kobayashi, K., James, C.J., Nakahori, T., Akiyama, T., Gotman, J.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1763
container_issue 10
container_start_page 1755
container_title Clinical neurophysiology
container_volume 110
creator Kobayashi, K.
James, C.J.
Nakahori, T.
Akiyama, T.
Gotman, J.
description Objective: We propose a method that allows the separation of epileptiform discharges (EDs) from the EEG background, including the ED's waveform and spatial distribution. The method even allows to separate a spike in two components occurring at approximately the same time but having different waveforms and spatial distributions. Methods: The separation employs independent component analysis (ICA) and is not based on any assumption regarding generator model. A simulation study was performed by generating ten EEG data matrices by computer: each matrix included real background activity from a normal subject to which was added an array of simulated unaveraged EDs. Each discharge was a summation of two transients having slightly different potential field distributions and small jitters in time and amplitude. Real EEG data were also obtained from three epileptic patients. Results: Through ICA, we could isolate the two epileptiform transients in every simulation matrix, and the retrieved transients were almost identical as the originals, especially in their spatial distributions. Two epileptic components were isolated by ICA in all patients. Each estimated epileptic component had a consistent time course. Conclusion: ICA appears promising for the separation of unaveraged spikes from the EEG background and their decomposition in independent spatio-temporal components.
doi_str_mv 10.1016/S1388-2457(99)00134-0
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_69294236</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1388245799001340</els_id><sourcerecordid>69294236</sourcerecordid><originalsourceid>FETCH-LOGICAL-c456t-1d7935805224d4a3736d1b14cd06c1cc7cb5c871946897dcefb43589530fec333</originalsourceid><addsrcrecordid>eNqFkE1v1DAQhi0EoqXwE0A-IASHFH_G8QmhamkrVeJQuHCxnPGkGCV2sLOV9t-T7S6CWy8zc3hm5tVDyGvOzjnj7cdbLruuEUqb99Z-YIxL1bAn5JR3RjSd1eLpOv9FTsiLWn8xxgxT4jk54UwbJSw7JT-uax79EnOieaA4xxHnJQ65TDTECj99ucNKh5Inuk3-Hou_w0A3m0va72hMAWdcS1oo5GnOaT_55MddjfUleTb4seKrYz8j379svl1cNTdfL68vPt80oHS7NDwYK3XHtBAqKC-NbAPvuYLAWuAABnoNneFWtZ01AXDo1cpbLdmAIKU8I-8Od-eSf2-xLm5ak-M4-oR5W11rhVVCtiuoDyCUXGvBwc0lTr7sHGduL9U9SHV7Y85a9yDVsXXvzfHBtp8w_Ld1sLgCb4-Ar-DHofgEsf7jhDKd3Qf9dMBwtXEfsbgKERNgiAVhcSHHR5L8AdTek8U</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>69294236</pqid></control><display><type>article</type><title>Isolation of epileptiform discharges from unaveraged EEG by independent component analysis</title><source>MEDLINE</source><source>Access via ScienceDirect (Elsevier)</source><creator>Kobayashi, K. ; James, C.J. ; Nakahori, T. ; Akiyama, T. ; Gotman, J.</creator><creatorcontrib>Kobayashi, K. ; James, C.J. ; Nakahori, T. ; Akiyama, T. ; Gotman, J.</creatorcontrib><description>Objective: We propose a method that allows the separation of epileptiform discharges (EDs) from the EEG background, including the ED's waveform and spatial distribution. The method even allows to separate a spike in two components occurring at approximately the same time but having different waveforms and spatial distributions. Methods: The separation employs independent component analysis (ICA) and is not based on any assumption regarding generator model. A simulation study was performed by generating ten EEG data matrices by computer: each matrix included real background activity from a normal subject to which was added an array of simulated unaveraged EDs. Each discharge was a summation of two transients having slightly different potential field distributions and small jitters in time and amplitude. Real EEG data were also obtained from three epileptic patients. Results: Through ICA, we could isolate the two epileptiform transients in every simulation matrix, and the retrieved transients were almost identical as the originals, especially in their spatial distributions. Two epileptic components were isolated by ICA in all patients. Each estimated epileptic component had a consistent time course. Conclusion: ICA appears promising for the separation of unaveraged spikes from the EEG background and their decomposition in independent spatio-temporal components.</description><identifier>ISSN: 1388-2457</identifier><identifier>EISSN: 1872-8952</identifier><identifier>DOI: 10.1016/S1388-2457(99)00134-0</identifier><identifier>PMID: 10574290</identifier><language>eng</language><publisher>Shannon: Elsevier B.V</publisher><subject>Algorithms ; Biological and medical sciences ; Computer Simulation ; EEG ; Electrodiagnosis. Electric activity recording ; Electroencephalography - methods ; Epilepsy - diagnosis ; Epilepsy - physiopathology ; Epileptiform discharge ; Humans ; Independent component analysis ; Investigative techniques, diagnostic techniques (general aspects) ; Medical sciences ; Nervous system ; Principal component analysis ; Signal Processing, Computer-Assisted</subject><ispartof>Clinical neurophysiology, 1999-10, Vol.110 (10), p.1755-1763</ispartof><rights>1999 Elsevier Science Ireland Ltd</rights><rights>2000 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c456t-1d7935805224d4a3736d1b14cd06c1cc7cb5c871946897dcefb43589530fec333</citedby><cites>FETCH-LOGICAL-c456t-1d7935805224d4a3736d1b14cd06c1cc7cb5c871946897dcefb43589530fec333</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/S1388-2457(99)00134-0$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=1247893$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/10574290$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kobayashi, K.</creatorcontrib><creatorcontrib>James, C.J.</creatorcontrib><creatorcontrib>Nakahori, T.</creatorcontrib><creatorcontrib>Akiyama, T.</creatorcontrib><creatorcontrib>Gotman, J.</creatorcontrib><title>Isolation of epileptiform discharges from unaveraged EEG by independent component analysis</title><title>Clinical neurophysiology</title><addtitle>Clin Neurophysiol</addtitle><description>Objective: We propose a method that allows the separation of epileptiform discharges (EDs) from the EEG background, including the ED's waveform and spatial distribution. The method even allows to separate a spike in two components occurring at approximately the same time but having different waveforms and spatial distributions. Methods: The separation employs independent component analysis (ICA) and is not based on any assumption regarding generator model. A simulation study was performed by generating ten EEG data matrices by computer: each matrix included real background activity from a normal subject to which was added an array of simulated unaveraged EDs. Each discharge was a summation of two transients having slightly different potential field distributions and small jitters in time and amplitude. Real EEG data were also obtained from three epileptic patients. Results: Through ICA, we could isolate the two epileptiform transients in every simulation matrix, and the retrieved transients were almost identical as the originals, especially in their spatial distributions. Two epileptic components were isolated by ICA in all patients. Each estimated epileptic component had a consistent time course. Conclusion: ICA appears promising for the separation of unaveraged spikes from the EEG background and their decomposition in independent spatio-temporal components.</description><subject>Algorithms</subject><subject>Biological and medical sciences</subject><subject>Computer Simulation</subject><subject>EEG</subject><subject>Electrodiagnosis. Electric activity recording</subject><subject>Electroencephalography - methods</subject><subject>Epilepsy - diagnosis</subject><subject>Epilepsy - physiopathology</subject><subject>Epileptiform discharge</subject><subject>Humans</subject><subject>Independent component analysis</subject><subject>Investigative techniques, diagnostic techniques (general aspects)</subject><subject>Medical sciences</subject><subject>Nervous system</subject><subject>Principal component analysis</subject><subject>Signal Processing, Computer-Assisted</subject><issn>1388-2457</issn><issn>1872-8952</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1999</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE1v1DAQhi0EoqXwE0A-IASHFH_G8QmhamkrVeJQuHCxnPGkGCV2sLOV9t-T7S6CWy8zc3hm5tVDyGvOzjnj7cdbLruuEUqb99Z-YIxL1bAn5JR3RjSd1eLpOv9FTsiLWn8xxgxT4jk54UwbJSw7JT-uax79EnOieaA4xxHnJQ65TDTECj99ucNKh5Inuk3-Hou_w0A3m0va72hMAWdcS1oo5GnOaT_55MddjfUleTb4seKrYz8j379svl1cNTdfL68vPt80oHS7NDwYK3XHtBAqKC-NbAPvuYLAWuAABnoNneFWtZ01AXDo1cpbLdmAIKU8I-8Od-eSf2-xLm5ak-M4-oR5W11rhVVCtiuoDyCUXGvBwc0lTr7sHGduL9U9SHV7Y85a9yDVsXXvzfHBtp8w_Ld1sLgCb4-Ar-DHofgEsf7jhDKd3Qf9dMBwtXEfsbgKERNgiAVhcSHHR5L8AdTek8U</recordid><startdate>19991001</startdate><enddate>19991001</enddate><creator>Kobayashi, K.</creator><creator>James, C.J.</creator><creator>Nakahori, T.</creator><creator>Akiyama, T.</creator><creator>Gotman, J.</creator><general>Elsevier B.V</general><general>Elsevier Science</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>19991001</creationdate><title>Isolation of epileptiform discharges from unaveraged EEG by independent component analysis</title><author>Kobayashi, K. ; James, C.J. ; Nakahori, T. ; Akiyama, T. ; Gotman, J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c456t-1d7935805224d4a3736d1b14cd06c1cc7cb5c871946897dcefb43589530fec333</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Algorithms</topic><topic>Biological and medical sciences</topic><topic>Computer Simulation</topic><topic>EEG</topic><topic>Electrodiagnosis. Electric activity recording</topic><topic>Electroencephalography - methods</topic><topic>Epilepsy - diagnosis</topic><topic>Epilepsy - physiopathology</topic><topic>Epileptiform discharge</topic><topic>Humans</topic><topic>Independent component analysis</topic><topic>Investigative techniques, diagnostic techniques (general aspects)</topic><topic>Medical sciences</topic><topic>Nervous system</topic><topic>Principal component analysis</topic><topic>Signal Processing, Computer-Assisted</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kobayashi, K.</creatorcontrib><creatorcontrib>James, C.J.</creatorcontrib><creatorcontrib>Nakahori, T.</creatorcontrib><creatorcontrib>Akiyama, T.</creatorcontrib><creatorcontrib>Gotman, J.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical neurophysiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kobayashi, K.</au><au>James, C.J.</au><au>Nakahori, T.</au><au>Akiyama, T.</au><au>Gotman, J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Isolation of epileptiform discharges from unaveraged EEG by independent component analysis</atitle><jtitle>Clinical neurophysiology</jtitle><addtitle>Clin Neurophysiol</addtitle><date>1999-10-01</date><risdate>1999</risdate><volume>110</volume><issue>10</issue><spage>1755</spage><epage>1763</epage><pages>1755-1763</pages><issn>1388-2457</issn><eissn>1872-8952</eissn><abstract>Objective: We propose a method that allows the separation of epileptiform discharges (EDs) from the EEG background, including the ED's waveform and spatial distribution. The method even allows to separate a spike in two components occurring at approximately the same time but having different waveforms and spatial distributions. Methods: The separation employs independent component analysis (ICA) and is not based on any assumption regarding generator model. A simulation study was performed by generating ten EEG data matrices by computer: each matrix included real background activity from a normal subject to which was added an array of simulated unaveraged EDs. Each discharge was a summation of two transients having slightly different potential field distributions and small jitters in time and amplitude. Real EEG data were also obtained from three epileptic patients. Results: Through ICA, we could isolate the two epileptiform transients in every simulation matrix, and the retrieved transients were almost identical as the originals, especially in their spatial distributions. Two epileptic components were isolated by ICA in all patients. Each estimated epileptic component had a consistent time course. Conclusion: ICA appears promising for the separation of unaveraged spikes from the EEG background and their decomposition in independent spatio-temporal components.</abstract><cop>Shannon</cop><pub>Elsevier B.V</pub><pmid>10574290</pmid><doi>10.1016/S1388-2457(99)00134-0</doi><tpages>9</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1388-2457
ispartof Clinical neurophysiology, 1999-10, Vol.110 (10), p.1755-1763
issn 1388-2457
1872-8952
language eng
recordid cdi_proquest_miscellaneous_69294236
source MEDLINE; Access via ScienceDirect (Elsevier)
subjects Algorithms
Biological and medical sciences
Computer Simulation
EEG
Electrodiagnosis. Electric activity recording
Electroencephalography - methods
Epilepsy - diagnosis
Epilepsy - physiopathology
Epileptiform discharge
Humans
Independent component analysis
Investigative techniques, diagnostic techniques (general aspects)
Medical sciences
Nervous system
Principal component analysis
Signal Processing, Computer-Assisted
title Isolation of epileptiform discharges from unaveraged EEG by independent component analysis
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T18%3A29%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Isolation%20of%20epileptiform%20discharges%20from%20unaveraged%20EEG%20by%20independent%20component%20analysis&rft.jtitle=Clinical%20neurophysiology&rft.au=Kobayashi,%20K.&rft.date=1999-10-01&rft.volume=110&rft.issue=10&rft.spage=1755&rft.epage=1763&rft.pages=1755-1763&rft.issn=1388-2457&rft.eissn=1872-8952&rft_id=info:doi/10.1016/S1388-2457(99)00134-0&rft_dat=%3Cproquest_cross%3E69294236%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=69294236&rft_id=info:pmid/10574290&rft_els_id=S1388245799001340&rfr_iscdi=true