Dipole source localization of mouse electroencephalogram using the Fieldtrip toolbox
The mouse model is an important research tool in neurosciences to examine brain function and diseases with genetic perturbation in different brain regions. However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model...
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| Veröffentlicht in: | PloS one 2013-11, Vol.8 (11), p.e79442-e79442 |
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| creator | Lee, Chungki Oostenveld, Robert Lee, Soo Hyun Kim, Lae Hyun Sung, Hokun Choi, Jee Hyun |
| description | The mouse model is an important research tool in neurosciences to examine brain function and diseases with genetic perturbation in different brain regions. However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model compared to human functional brain mapping. Here, we present a functional brain mapping method for fast and robust in vivo brain mapping of the mouse brain. The method is based on the acquisition of high density electroencephalography (EEG) with a microarray and EEG source estimation to localize the electrophysiological origins. We adapted the Fieldtrip toolbox for the source estimation, taking advantage of its software openness and flexibility in modeling the EEG volume conduction. Three source estimation techniques were compared: Distribution source modeling with minimum-norm estimation (MNE), scanning with multiple signal classification (MUSIC), and single-dipole fitting. Known sources to evaluate the performance of the localization methods were provided using optogenetic tools. The accuracy was quantified based on the receiver operating characteristic (ROC) analysis. The mean detection accuracy was high, with a false positive rate less than 1.3% and 7% at the sensitivity of 90% plotted with the MNE and MUSIC algorithms, respectively. The mean center-to-center distance was less than 1.2 mm in single dipole fitting algorithm. Mouse microarray EEG source localization using microarray allows a reliable method for functional brain mapping in awake mouse opening an access to cross-species study with human brain. |
| doi_str_mv | 10.1371/journal.pone.0079442 |
| format | Article |
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However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model compared to human functional brain mapping. Here, we present a functional brain mapping method for fast and robust in vivo brain mapping of the mouse brain. The method is based on the acquisition of high density electroencephalography (EEG) with a microarray and EEG source estimation to localize the electrophysiological origins. We adapted the Fieldtrip toolbox for the source estimation, taking advantage of its software openness and flexibility in modeling the EEG volume conduction. Three source estimation techniques were compared: Distribution source modeling with minimum-norm estimation (MNE), scanning with multiple signal classification (MUSIC), and single-dipole fitting. Known sources to evaluate the performance of the localization methods were provided using optogenetic tools. The accuracy was quantified based on the receiver operating characteristic (ROC) analysis. The mean detection accuracy was high, with a false positive rate less than 1.3% and 7% at the sensitivity of 90% plotted with the MNE and MUSIC algorithms, respectively. The mean center-to-center distance was less than 1.2 mm in single dipole fitting algorithm. Mouse microarray EEG source localization using microarray allows a reliable method for functional brain mapping in awake mouse opening an access to cross-species study with human brain.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0079442</identifier><identifier>PMID: 24244506</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Animal cognition ; Animals ; Biomedical research ; Brain ; Brain - physiology ; Brain mapping ; Brain Mapping - methods ; Brain research ; Comparative analysis ; Computer Simulation ; Conduction ; Dipoles ; EEG ; Electroencephalography ; Electroencephalography - methods ; Gene mapping ; In vivo methods and tests ; Inverse problems ; Localization ; Male ; Mapping ; Medical imaging ; Mice ; Modelling ; Models, Neurological ; Neurosciences ; Neurosurgery ; NMR ; Nuclear magnetic resonance ; Recording equipment ; Reproducibility of Results ; Rodents ; Science ; Signal classification ; Signal processing</subject><ispartof>PloS one, 2013-11, Vol.8 (11), p.e79442-e79442</ispartof><rights>COPYRIGHT 2013 Public Library of Science</rights><rights>2013 Lee et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013 Lee et al 2013 Lee et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-b72f0007020db735e2dac44dff0830800d8466e79f320cf838e4cc1e3b48aa453</citedby><cites>FETCH-LOGICAL-c692t-b72f0007020db735e2dac44dff0830800d8466e79f320cf838e4cc1e3b48aa453</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3828402/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3828402/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2100,2926,23865,27923,27924,53790,53792,79371,79372</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24244506$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Annala, Alexander</contributor><creatorcontrib>Lee, Chungki</creatorcontrib><creatorcontrib>Oostenveld, Robert</creatorcontrib><creatorcontrib>Lee, Soo Hyun</creatorcontrib><creatorcontrib>Kim, Lae Hyun</creatorcontrib><creatorcontrib>Sung, Hokun</creatorcontrib><creatorcontrib>Choi, Jee Hyun</creatorcontrib><title>Dipole source localization of mouse electroencephalogram using the Fieldtrip toolbox</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>The mouse model is an important research tool in neurosciences to examine brain function and diseases with genetic perturbation in different brain regions. However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model compared to human functional brain mapping. Here, we present a functional brain mapping method for fast and robust in vivo brain mapping of the mouse brain. The method is based on the acquisition of high density electroencephalography (EEG) with a microarray and EEG source estimation to localize the electrophysiological origins. We adapted the Fieldtrip toolbox for the source estimation, taking advantage of its software openness and flexibility in modeling the EEG volume conduction. Three source estimation techniques were compared: Distribution source modeling with minimum-norm estimation (MNE), scanning with multiple signal classification (MUSIC), and single-dipole fitting. Known sources to evaluate the performance of the localization methods were provided using optogenetic tools. The accuracy was quantified based on the receiver operating characteristic (ROC) analysis. The mean detection accuracy was high, with a false positive rate less than 1.3% and 7% at the sensitivity of 90% plotted with the MNE and MUSIC algorithms, respectively. The mean center-to-center distance was less than 1.2 mm in single dipole fitting algorithm. Mouse microarray EEG source localization using microarray allows a reliable method for functional brain mapping in awake mouse opening an access to cross-species study with human brain.</description><subject>Algorithms</subject><subject>Animal cognition</subject><subject>Animals</subject><subject>Biomedical research</subject><subject>Brain</subject><subject>Brain - physiology</subject><subject>Brain mapping</subject><subject>Brain Mapping - methods</subject><subject>Brain research</subject><subject>Comparative analysis</subject><subject>Computer Simulation</subject><subject>Conduction</subject><subject>Dipoles</subject><subject>EEG</subject><subject>Electroencephalography</subject><subject>Electroencephalography - methods</subject><subject>Gene mapping</subject><subject>In vivo methods and tests</subject><subject>Inverse problems</subject><subject>Localization</subject><subject>Male</subject><subject>Mapping</subject><subject>Medical 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using the Fieldtrip toolbox</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2013-11-14</date><risdate>2013</risdate><volume>8</volume><issue>11</issue><spage>e79442</spage><epage>e79442</epage><pages>e79442-e79442</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>The mouse model is an important research tool in neurosciences to examine brain function and diseases with genetic perturbation in different brain regions. However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model compared to human functional brain mapping. Here, we present a functional brain mapping method for fast and robust in vivo brain mapping of the mouse brain. The method is based on the acquisition of high density electroencephalography (EEG) with a microarray and EEG source estimation to localize the electrophysiological origins. We adapted the Fieldtrip toolbox for the source estimation, taking advantage of its software openness and flexibility in modeling the EEG volume conduction. Three source estimation techniques were compared: Distribution source modeling with minimum-norm estimation (MNE), scanning with multiple signal classification (MUSIC), and single-dipole fitting. Known sources to evaluate the performance of the localization methods were provided using optogenetic tools. The accuracy was quantified based on the receiver operating characteristic (ROC) analysis. The mean detection accuracy was high, with a false positive rate less than 1.3% and 7% at the sensitivity of 90% plotted with the MNE and MUSIC algorithms, respectively. The mean center-to-center distance was less than 1.2 mm in single dipole fitting algorithm. Mouse microarray EEG source localization using microarray allows a reliable method for functional brain mapping in awake mouse opening an access to cross-species study with human brain.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24244506</pmid><doi>10.1371/journal.pone.0079442</doi><tpages>e79442</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Algorithms Animal cognition Animals Biomedical research Brain Brain - physiology Brain mapping Brain Mapping - methods Brain research Comparative analysis Computer Simulation Conduction Dipoles EEG Electroencephalography Electroencephalography - methods Gene mapping In vivo methods and tests Inverse problems Localization Male Mapping Medical imaging Mice Modelling Models, Neurological Neurosciences Neurosurgery NMR Nuclear magnetic resonance Recording equipment Reproducibility of Results Rodents Science Signal classification Signal processing |
| title | Dipole source localization of mouse electroencephalogram using the Fieldtrip toolbox |
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