Spontaneous MEG activity of the cerebral cortex during eyes closed and open discriminates Alzheimer’s disease from cognitively normal older adults
This study aimed to examine whether magnetoencephalography (MEG) is useful to detect early stage Alzheimer’s disease (AD). We analyzed MEG data from the early stage AD group (n = 20; 6 with mild cognitive impairment due to AD and 14 with AD dementia) and cognitively normal control group (NC, n = 27)...
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| Veröffentlicht in: | Scientific reports 2020-06, Vol.10 (1), p.9132, Article 9132 |
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| creator | Ikeda, Yoshihisa Kikuchi, Mitsuru Noguchi-Shinohara, Moeko Iwasa, Kazuo Kameya, Masafumi Hirosawa, Tetsu Yoshita, Mitsuhiro Ono, Kenjiro Samuraki-Yokohama, Miharu Yamada, Masahito |
| description | This study aimed to examine whether magnetoencephalography (MEG) is useful to detect early stage Alzheimer’s disease (AD). We analyzed MEG data from the early stage AD group (n = 20; 6 with mild cognitive impairment due to AD and 14 with AD dementia) and cognitively normal control group (NC, n = 27). MEG was recorded during resting eyes closed (EC) and eyes open (EO), and the following 6 values for each of 5 bands (θ1: 4-6, θ2: 6-8, α1: 8-10, α2: 10-13, β: 13-20 Hz) in the cerebral 68 regions were compared between the groups: (1) absolute power during EC and (2) EO, (3) whole cerebral normalization (WCN) power during EC and (4) EO, (5) difference of the absolute powers between the EC and EO conditions (the EC-EO difference), and (6) WCN value of the EC-EO difference. We found significant differences between the groups in the WCN powers during the EO condition, and the EC-EO differences. Using a Support Vector Machine classifier, a discrimination accuracy of 83% was obtained and an AUC in an ROC analysis was 0.91. This study demonstrates that MEG during resting EC and EO is useful in discriminating between early stage AD and NC. |
| doi_str_mv | 10.1038/s41598-020-66034-5 |
| format | Article |
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We analyzed MEG data from the early stage AD group (n = 20; 6 with mild cognitive impairment due to AD and 14 with AD dementia) and cognitively normal control group (NC, n = 27). MEG was recorded during resting eyes closed (EC) and eyes open (EO), and the following 6 values for each of 5 bands (θ1: 4-6, θ2: 6-8, α1: 8-10, α2: 10-13, β: 13-20 Hz) in the cerebral 68 regions were compared between the groups: (1) absolute power during EC and (2) EO, (3) whole cerebral normalization (WCN) power during EC and (4) EO, (5) difference of the absolute powers between the EC and EO conditions (the EC-EO difference), and (6) WCN value of the EC-EO difference. We found significant differences between the groups in the WCN powers during the EO condition, and the EC-EO differences. Using a Support Vector Machine classifier, a discrimination accuracy of 83% was obtained and an AUC in an ROC analysis was 0.91. This study demonstrates that MEG during resting EC and EO is useful in discriminating between early stage AD and NC.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-020-66034-5</identifier><identifier>PMID: 32499487</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/378 ; 692/308 ; 692/617 ; 692/699 ; Accuracy ; Aged ; Aged, 80 and over ; Alzheimer Disease - pathology ; Alzheimer's disease ; Area Under Curve ; Case-Control Studies ; Cerebral cortex ; Cerebral Cortex - physiology ; Cognitive ability ; Cognitive Dysfunction - pathology ; Dementia ; Dementia disorders ; Eye ; Female ; Humanities and Social Sciences ; Humans ; Magnetic resonance imaging ; Magnetoencephalography ; Male ; Middle Aged ; multidisciplinary ; Neurobiology ; Neurodegenerative diseases ; Neurosciences ; Older people ; ROC Curve ; Science ; Science (multidisciplinary) ; Severity of Illness Index ; Support Vector Machine ; Support vector machines ; University graduates</subject><ispartof>Scientific reports, 2020-06, Vol.10 (1), p.9132, Article 9132</ispartof><rights>The Author(s) 2020</rights><rights>The Author(s) 2020. 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Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c584t-5cc742ac5202bde55959828b37ea9d434f7c92a6388de3c16dca9fedd99cecdc3</citedby><cites>FETCH-LOGICAL-c584t-5cc742ac5202bde55959828b37ea9d434f7c92a6388de3c16dca9fedd99cecdc3</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/PMC7272642/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7272642/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,27924,27925,41120,42189,51576,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32499487$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ikeda, Yoshihisa</creatorcontrib><creatorcontrib>Kikuchi, Mitsuru</creatorcontrib><creatorcontrib>Noguchi-Shinohara, Moeko</creatorcontrib><creatorcontrib>Iwasa, Kazuo</creatorcontrib><creatorcontrib>Kameya, Masafumi</creatorcontrib><creatorcontrib>Hirosawa, Tetsu</creatorcontrib><creatorcontrib>Yoshita, Mitsuhiro</creatorcontrib><creatorcontrib>Ono, Kenjiro</creatorcontrib><creatorcontrib>Samuraki-Yokohama, Miharu</creatorcontrib><creatorcontrib>Yamada, Masahito</creatorcontrib><title>Spontaneous MEG activity of the cerebral cortex during eyes closed and open discriminates Alzheimer’s disease from cognitively normal older adults</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>This study aimed to examine whether magnetoencephalography (MEG) is useful to detect early stage Alzheimer’s disease (AD). We analyzed MEG data from the early stage AD group (n = 20; 6 with mild cognitive impairment due to AD and 14 with AD dementia) and cognitively normal control group (NC, n = 27). MEG was recorded during resting eyes closed (EC) and eyes open (EO), and the following 6 values for each of 5 bands (θ1: 4-6, θ2: 6-8, α1: 8-10, α2: 10-13, β: 13-20 Hz) in the cerebral 68 regions were compared between the groups: (1) absolute power during EC and (2) EO, (3) whole cerebral normalization (WCN) power during EC and (4) EO, (5) difference of the absolute powers between the EC and EO conditions (the EC-EO difference), and (6) WCN value of the EC-EO difference. We found significant differences between the groups in the WCN powers during the EO condition, and the EC-EO differences. Using a Support Vector Machine classifier, a discrimination accuracy of 83% was obtained and an AUC in an ROC analysis was 0.91. This study demonstrates that MEG during resting EC and EO is useful in discriminating between early stage AD and NC.</description><subject>631/378</subject><subject>692/308</subject><subject>692/617</subject><subject>692/699</subject><subject>Accuracy</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Alzheimer Disease - pathology</subject><subject>Alzheimer's disease</subject><subject>Area Under Curve</subject><subject>Case-Control Studies</subject><subject>Cerebral cortex</subject><subject>Cerebral Cortex - physiology</subject><subject>Cognitive ability</subject><subject>Cognitive Dysfunction - pathology</subject><subject>Dementia</subject><subject>Dementia disorders</subject><subject>Eye</subject><subject>Female</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>Magnetic resonance imaging</subject><subject>Magnetoencephalography</subject><subject>Male</subject><subject>Middle Aged</subject><subject>multidisciplinary</subject><subject>Neurobiology</subject><subject>Neurodegenerative diseases</subject><subject>Neurosciences</subject><subject>Older people</subject><subject>ROC Curve</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><subject>Severity of Illness Index</subject><subject>Support Vector Machine</subject><subject>Support vector machines</subject><subject>University graduates</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kc9uFSEUxonR2KbtC7gwJK5HGf7MwMakaWo1qXFRXRMunLmXZgZGYBpvV30IN76eTyLXW2vdyAaS853vO4cfQi9a8rolTL7JvBVKNoSSpusI4414gg4p4aKhjNKnj94H6CTna1KPoIq36jk6YJQrxWV_iL5fzTEUEyAuGX88v8DGFn_jyxbHAZcNYAsJVsmM2MZU4Bt2S_JhjWELGdsxZnDYBIfjDAE7n23ykw-m1OrpeLsBP0H6efcj72pgMuAhxal6rYOvOTBucYhpqvZxdJCwcctY8jF6Npgxw8n9fYS-vDv_fPa-ufx08eHs9LKxQvLSCGt7To0VlNCVAyFU_REqV6wHoxxnfOitoqZjUjpgtu2cNWoA55SyYJ1lR-jt3ndeVhM4C6HUTfVcdzBpq6Px-t9K8Bu9jje6pz3tOK0Gr-4NUvy6QC76Oi4p1Jk15UR1RHZcVhXdq2yKOScYHhJaoncw9R6mrjD1b5ha1KaXj2d7aPmDrgrYXpDnHRFIf7P_Y_sLC1ywlQ</recordid><startdate>20200604</startdate><enddate>20200604</enddate><creator>Ikeda, Yoshihisa</creator><creator>Kikuchi, Mitsuru</creator><creator>Noguchi-Shinohara, Moeko</creator><creator>Iwasa, Kazuo</creator><creator>Kameya, Masafumi</creator><creator>Hirosawa, Tetsu</creator><creator>Yoshita, Mitsuhiro</creator><creator>Ono, Kenjiro</creator><creator>Samuraki-Yokohama, Miharu</creator><creator>Yamada, Masahito</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</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>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>5PM</scope></search><sort><creationdate>20200604</creationdate><title>Spontaneous MEG activity of the cerebral cortex during eyes closed and open discriminates Alzheimer’s disease from cognitively normal older adults</title><author>Ikeda, Yoshihisa ; Kikuchi, Mitsuru ; Noguchi-Shinohara, Moeko ; Iwasa, Kazuo ; Kameya, Masafumi ; Hirosawa, Tetsu ; Yoshita, Mitsuhiro ; Ono, Kenjiro ; Samuraki-Yokohama, Miharu ; Yamada, Masahito</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c584t-5cc742ac5202bde55959828b37ea9d434f7c92a6388de3c16dca9fedd99cecdc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>631/378</topic><topic>692/308</topic><topic>692/617</topic><topic>692/699</topic><topic>Accuracy</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Alzheimer Disease - pathology</topic><topic>Alzheimer's disease</topic><topic>Area Under Curve</topic><topic>Case-Control Studies</topic><topic>Cerebral cortex</topic><topic>Cerebral Cortex - physiology</topic><topic>Cognitive ability</topic><topic>Cognitive Dysfunction - pathology</topic><topic>Dementia</topic><topic>Dementia disorders</topic><topic>Eye</topic><topic>Female</topic><topic>Humanities and Social Sciences</topic><topic>Humans</topic><topic>Magnetic resonance imaging</topic><topic>Magnetoencephalography</topic><topic>Male</topic><topic>Middle Aged</topic><topic>multidisciplinary</topic><topic>Neurobiology</topic><topic>Neurodegenerative diseases</topic><topic>Neurosciences</topic><topic>Older people</topic><topic>ROC Curve</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><topic>Severity of Illness Index</topic><topic>Support Vector Machine</topic><topic>Support vector machines</topic><topic>University graduates</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ikeda, Yoshihisa</creatorcontrib><creatorcontrib>Kikuchi, Mitsuru</creatorcontrib><creatorcontrib>Noguchi-Shinohara, Moeko</creatorcontrib><creatorcontrib>Iwasa, Kazuo</creatorcontrib><creatorcontrib>Kameya, Masafumi</creatorcontrib><creatorcontrib>Hirosawa, Tetsu</creatorcontrib><creatorcontrib>Yoshita, Mitsuhiro</creatorcontrib><creatorcontrib>Ono, Kenjiro</creatorcontrib><creatorcontrib>Samuraki-Yokohama, Miharu</creatorcontrib><creatorcontrib>Yamada, Masahito</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ikeda, Yoshihisa</au><au>Kikuchi, Mitsuru</au><au>Noguchi-Shinohara, Moeko</au><au>Iwasa, Kazuo</au><au>Kameya, Masafumi</au><au>Hirosawa, Tetsu</au><au>Yoshita, Mitsuhiro</au><au>Ono, Kenjiro</au><au>Samuraki-Yokohama, Miharu</au><au>Yamada, Masahito</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spontaneous MEG activity of the cerebral cortex during eyes closed and open discriminates Alzheimer’s disease from cognitively normal older adults</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2020-06-04</date><risdate>2020</risdate><volume>10</volume><issue>1</issue><spage>9132</spage><pages>9132-</pages><artnum>9132</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>This study aimed to examine whether magnetoencephalography (MEG) is useful to detect early stage Alzheimer’s disease (AD). We analyzed MEG data from the early stage AD group (n = 20; 6 with mild cognitive impairment due to AD and 14 with AD dementia) and cognitively normal control group (NC, n = 27). MEG was recorded during resting eyes closed (EC) and eyes open (EO), and the following 6 values for each of 5 bands (θ1: 4-6, θ2: 6-8, α1: 8-10, α2: 10-13, β: 13-20 Hz) in the cerebral 68 regions were compared between the groups: (1) absolute power during EC and (2) EO, (3) whole cerebral normalization (WCN) power during EC and (4) EO, (5) difference of the absolute powers between the EC and EO conditions (the EC-EO difference), and (6) WCN value of the EC-EO difference. We found significant differences between the groups in the WCN powers during the EO condition, and the EC-EO differences. Using a Support Vector Machine classifier, a discrimination accuracy of 83% was obtained and an AUC in an ROC analysis was 0.91. This study demonstrates that MEG during resting EC and EO is useful in discriminating between early stage AD and NC.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>32499487</pmid><doi>10.1038/s41598-020-66034-5</doi><oa>free_for_read</oa></addata></record> |
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| subjects | 631/378 692/308 692/617 692/699 Accuracy Aged Aged, 80 and over Alzheimer Disease - pathology Alzheimer's disease Area Under Curve Case-Control Studies Cerebral cortex Cerebral Cortex - physiology Cognitive ability Cognitive Dysfunction - pathology Dementia Dementia disorders Eye Female Humanities and Social Sciences Humans Magnetic resonance imaging Magnetoencephalography Male Middle Aged multidisciplinary Neurobiology Neurodegenerative diseases Neurosciences Older people ROC Curve Science Science (multidisciplinary) Severity of Illness Index Support Vector Machine Support vector machines University graduates |
| title | Spontaneous MEG activity of the cerebral cortex during eyes closed and open discriminates Alzheimer’s disease from cognitively normal older adults |
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