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MEG and EEG dipole clusters from extended cortical sources
Data from magnetoencephalography (MEG) and electroencephalography (EEG) suffer from a rather limited signal-to-noise-ratio (SNR) due to cortical background activities and other artifacts. In order to study the effect of the SNR on the size and distribution of dipole clusters reconstructed from inter...
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Published in: | Biomedical engineering letters 2017, 7(3), , pp.185-191 |
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description | Data from magnetoencephalography (MEG) and electroencephalography (EEG) suffer from a rather limited signal-to-noise-ratio (SNR) due to cortical background activities and other artifacts. In order to study the effect of the SNR on the size and distribution of dipole clusters reconstructed from interictal epileptic spikes, we performed simulations using realistically shaped volume conductor models and extended cortical sources with different sensor configurations. Head models and cortical surfaces were derived from an averaged magnetic resonance image dataset (Montreal Neurological Institute). Extended sources were simulated by spherical patches with Gaussian current distributions on the folded cortical surface. Different patch sizes were used to investigate cancellation effects from opposing walls of sulcal foldings and to estimate corresponding changes in MEG and EEG sensitivity distributions. Finally, white noise was added to the simulated fields and equivalent current dipole reconstructions were performed to determine size and shape of the resulting dipole clusters. Neuronal currents are oriented perpendicular to the local cortical surface and show cancellation effects of source components on opposing sulcal walls. Since these mostly tangential aspects from large cortical patches cancel out, large extended sources exhibit more radial components in the head geometry. This effect has a larger impact on MEG data as compared to EEG, because in a spherical head model radial currents do not yield any magnetic field. Confidence volumes of single reconstructed dipoles from simulated data at different SNRs show a good correlation with the extension of clusters from repeated dipole reconstructions. Size and shape of dipole clusters reconstructed from extended cortical sources do not only depend on spike and timepoint selection, but also strongly on the SNR of the measured interictal MEG or EEG data. In a linear approximation the size of the clusters is proportional to the inverse SNR. |
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In order to study the effect of the SNR on the size and distribution of dipole clusters reconstructed from interictal epileptic spikes, we performed simulations using realistically shaped volume conductor models and extended cortical sources with different sensor configurations. Head models and cortical surfaces were derived from an averaged magnetic resonance image dataset (Montreal Neurological Institute). Extended sources were simulated by spherical patches with Gaussian current distributions on the folded cortical surface. Different patch sizes were used to investigate cancellation effects from opposing walls of sulcal foldings and to estimate corresponding changes in MEG and EEG sensitivity distributions. Finally, white noise was added to the simulated fields and equivalent current dipole reconstructions were performed to determine size and shape of the resulting dipole clusters. Neuronal currents are oriented perpendicular to the local cortical surface and show cancellation effects of source components on opposing sulcal walls. Since these mostly tangential aspects from large cortical patches cancel out, large extended sources exhibit more radial components in the head geometry. This effect has a larger impact on MEG data as compared to EEG, because in a spherical head model radial currents do not yield any magnetic field. Confidence volumes of single reconstructed dipoles from simulated data at different SNRs show a good correlation with the extension of clusters from repeated dipole reconstructions. Size and shape of dipole clusters reconstructed from extended cortical sources do not only depend on spike and timepoint selection, but also strongly on the SNR of the measured interictal MEG or EEG data. In a linear approximation the size of the clusters is proportional to the inverse SNR.</description><identifier>ISSN: 2093-9868</identifier><identifier>EISSN: 2093-985X</identifier><identifier>DOI: 10.1007/s13534-017-0019-2</identifier><identifier>PMID: 30603165</identifier><language>eng</language><publisher>Korea: The Korean Society of Medical and Biological Engineering</publisher><subject>Background noise ; Biological and Medical Physics ; Biomagnetism ; Biomedical Engineering and Bioengineering ; Biomedicine ; Biophysics ; Clusters ; Computer simulation ; Conductors ; Confidence intervals ; Cortex ; Dipoles ; EEG ; Electroencephalography ; Engineering ; Epilepsy ; Magnetic fields ; Magnetic resonance imaging ; Magnetoencephalography ; Medical and Radiation Physics ; Noise sensitivity ; Original ; Original Article ; Patches (structures) ; Surface chemistry ; White noise ; 의공학</subject><ispartof>Biomedical Engineering Letters (BMEL), 2017, 7(3), , pp.185-191</ispartof><rights>Korean Society of Medical and Biological Engineering and Springer 2017</rights><rights>Copyright Springer Science & Business Media 2017</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c504t-6fc57c6711bf13335364ca0298e18017a35f84b86ab3f77143093d0656c1d72a3</citedby><cites>FETCH-LOGICAL-c504t-6fc57c6711bf13335364ca0298e18017a35f84b86ab3f77143093d0656c1d72a3</cites><orcidid>0000-0002-3562-9832</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6208502/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6208502/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30603165$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002276140$$DAccess content in National Research Foundation of Korea (NRF)$$Hfree_for_read</backlink></links><search><creatorcontrib>Fuchs, Manfred</creatorcontrib><creatorcontrib>Kastner, Jörn</creatorcontrib><creatorcontrib>Tech, Reyko</creatorcontrib><creatorcontrib>Wagner, Michael</creatorcontrib><creatorcontrib>Gasca, Fernando</creatorcontrib><title>MEG and EEG dipole clusters from extended cortical sources</title><title>Biomedical engineering letters</title><addtitle>Biomed. Eng. Lett</addtitle><addtitle>Biomed Eng Lett</addtitle><description>Data from magnetoencephalography (MEG) and electroencephalography (EEG) suffer from a rather limited signal-to-noise-ratio (SNR) due to cortical background activities and other artifacts. In order to study the effect of the SNR on the size and distribution of dipole clusters reconstructed from interictal epileptic spikes, we performed simulations using realistically shaped volume conductor models and extended cortical sources with different sensor configurations. Head models and cortical surfaces were derived from an averaged magnetic resonance image dataset (Montreal Neurological Institute). Extended sources were simulated by spherical patches with Gaussian current distributions on the folded cortical surface. Different patch sizes were used to investigate cancellation effects from opposing walls of sulcal foldings and to estimate corresponding changes in MEG and EEG sensitivity distributions. Finally, white noise was added to the simulated fields and equivalent current dipole reconstructions were performed to determine size and shape of the resulting dipole clusters. Neuronal currents are oriented perpendicular to the local cortical surface and show cancellation effects of source components on opposing sulcal walls. Since these mostly tangential aspects from large cortical patches cancel out, large extended sources exhibit more radial components in the head geometry. This effect has a larger impact on MEG data as compared to EEG, because in a spherical head model radial currents do not yield any magnetic field. Confidence volumes of single reconstructed dipoles from simulated data at different SNRs show a good correlation with the extension of clusters from repeated dipole reconstructions. Size and shape of dipole clusters reconstructed from extended cortical sources do not only depend on spike and timepoint selection, but also strongly on the SNR of the measured interictal MEG or EEG data. In a linear approximation the size of the clusters is proportional to the inverse SNR.</description><subject>Background noise</subject><subject>Biological and Medical Physics</subject><subject>Biomagnetism</subject><subject>Biomedical Engineering and Bioengineering</subject><subject>Biomedicine</subject><subject>Biophysics</subject><subject>Clusters</subject><subject>Computer simulation</subject><subject>Conductors</subject><subject>Confidence intervals</subject><subject>Cortex</subject><subject>Dipoles</subject><subject>EEG</subject><subject>Electroencephalography</subject><subject>Engineering</subject><subject>Epilepsy</subject><subject>Magnetic fields</subject><subject>Magnetic resonance imaging</subject><subject>Magnetoencephalography</subject><subject>Medical and Radiation Physics</subject><subject>Noise sensitivity</subject><subject>Original</subject><subject>Original Article</subject><subject>Patches (structures)</subject><subject>Surface chemistry</subject><subject>White noise</subject><subject>의공학</subject><issn>2093-9868</issn><issn>2093-985X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp1UU1LxDAQDaKorP4AL1LwoofqTNOkrQdBZP0ARRAFbyGbplrtNmvSiv57Z60uKpjLC8ybN2_mMbaFsI8A2UFALngaA2YxABZxssTWEyh4XOTifnnxl_ka2wzhCegJFAXnq2yNgwSOUqyzw6vxWaTbMhoTlvXMNTYyTR8660NUeTeN7Ftn29KWkXG-q41uouB6b2zYYCuVboLd_MIRuzsd356cx5fXZxcnx5exEZB2sayMyIzMECcVck6mZWo0JEVuMSf3mosqTye51BNeZRmmnIyXIIU0WGaJ5iO2N-i2vlLPplZO15_44NSzV8c3txeKli0k5sQ9GrizfjK1pbFt53WjZr6eav_-2fm70taPpPOqZAK5gIQEdr8EvHvpbejUtA7GNo1ureuDSlByII8EI7bzh_pEh2npFAoLWgIlpHNBHFjGuxC8rRZmENQ8SDUEqegUah6kmvds_9xi0fEdGxGSgRCo1D5Y_2P0v6ofw7ilNg</recordid><startdate>20170801</startdate><enddate>20170801</enddate><creator>Fuchs, Manfred</creator><creator>Kastner, Jörn</creator><creator>Tech, Reyko</creator><creator>Wagner, Michael</creator><creator>Gasca, Fernando</creator><general>The Korean Society of Medical and Biological Engineering</general><general>Springer Nature B.V</general><general>대한의용생체공학회</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>ACYCR</scope><orcidid>https://orcid.org/0000-0002-3562-9832</orcidid></search><sort><creationdate>20170801</creationdate><title>MEG and EEG dipole clusters from extended cortical sources</title><author>Fuchs, Manfred ; Kastner, Jörn ; Tech, Reyko ; Wagner, Michael ; Gasca, Fernando</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c504t-6fc57c6711bf13335364ca0298e18017a35f84b86ab3f77143093d0656c1d72a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Background noise</topic><topic>Biological and Medical Physics</topic><topic>Biomagnetism</topic><topic>Biomedical Engineering and Bioengineering</topic><topic>Biomedicine</topic><topic>Biophysics</topic><topic>Clusters</topic><topic>Computer simulation</topic><topic>Conductors</topic><topic>Confidence intervals</topic><topic>Cortex</topic><topic>Dipoles</topic><topic>EEG</topic><topic>Electroencephalography</topic><topic>Engineering</topic><topic>Epilepsy</topic><topic>Magnetic fields</topic><topic>Magnetic resonance imaging</topic><topic>Magnetoencephalography</topic><topic>Medical and Radiation Physics</topic><topic>Noise sensitivity</topic><topic>Original</topic><topic>Original Article</topic><topic>Patches (structures)</topic><topic>Surface chemistry</topic><topic>White noise</topic><topic>의공학</topic><toplevel>online_resources</toplevel><creatorcontrib>Fuchs, Manfred</creatorcontrib><creatorcontrib>Kastner, Jörn</creatorcontrib><creatorcontrib>Tech, Reyko</creatorcontrib><creatorcontrib>Wagner, Michael</creatorcontrib><creatorcontrib>Gasca, Fernando</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Korean Citation Index</collection><jtitle>Biomedical engineering letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fuchs, Manfred</au><au>Kastner, Jörn</au><au>Tech, Reyko</au><au>Wagner, Michael</au><au>Gasca, Fernando</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MEG and EEG dipole clusters from extended cortical sources</atitle><jtitle>Biomedical engineering letters</jtitle><stitle>Biomed. Eng. Lett</stitle><addtitle>Biomed Eng Lett</addtitle><date>2017-08-01</date><risdate>2017</risdate><volume>7</volume><issue>3</issue><spage>185</spage><epage>191</epage><pages>185-191</pages><issn>2093-9868</issn><eissn>2093-985X</eissn><abstract>Data from magnetoencephalography (MEG) and electroencephalography (EEG) suffer from a rather limited signal-to-noise-ratio (SNR) due to cortical background activities and other artifacts. In order to study the effect of the SNR on the size and distribution of dipole clusters reconstructed from interictal epileptic spikes, we performed simulations using realistically shaped volume conductor models and extended cortical sources with different sensor configurations. Head models and cortical surfaces were derived from an averaged magnetic resonance image dataset (Montreal Neurological Institute). Extended sources were simulated by spherical patches with Gaussian current distributions on the folded cortical surface. Different patch sizes were used to investigate cancellation effects from opposing walls of sulcal foldings and to estimate corresponding changes in MEG and EEG sensitivity distributions. Finally, white noise was added to the simulated fields and equivalent current dipole reconstructions were performed to determine size and shape of the resulting dipole clusters. Neuronal currents are oriented perpendicular to the local cortical surface and show cancellation effects of source components on opposing sulcal walls. Since these mostly tangential aspects from large cortical patches cancel out, large extended sources exhibit more radial components in the head geometry. This effect has a larger impact on MEG data as compared to EEG, because in a spherical head model radial currents do not yield any magnetic field. Confidence volumes of single reconstructed dipoles from simulated data at different SNRs show a good correlation with the extension of clusters from repeated dipole reconstructions. Size and shape of dipole clusters reconstructed from extended cortical sources do not only depend on spike and timepoint selection, but also strongly on the SNR of the measured interictal MEG or EEG data. In a linear approximation the size of the clusters is proportional to the inverse SNR.</abstract><cop>Korea</cop><pub>The Korean Society of Medical and Biological Engineering</pub><pmid>30603165</pmid><doi>10.1007/s13534-017-0019-2</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-3562-9832</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Background noise Biological and Medical Physics Biomagnetism Biomedical Engineering and Bioengineering Biomedicine Biophysics Clusters Computer simulation Conductors Confidence intervals Cortex Dipoles EEG Electroencephalography Engineering Epilepsy Magnetic fields Magnetic resonance imaging Magnetoencephalography Medical and Radiation Physics Noise sensitivity Original Original Article Patches (structures) Surface chemistry White noise 의공학 |
title | MEG and EEG dipole clusters from extended cortical sources |
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