Enhancing specialization of attention-related EEG power and phase synchronism brain patterns by meditation
Abstract Meditation, mental training that aims to improve one’s ability to regulate their cognition, has been widely applied in clinical medicine. However, the mechanism by which meditation affects brain activity is still unclear. To explore this question, electroencephalogram data were recorded in...
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Veröffentlicht in: | Cerebral cortex (New York, N.Y. 1991) N.Y. 1991), 2024-07, Vol.34 (7) |
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container_title | Cerebral cortex (New York, N.Y. 1991) |
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creator | Han, Yupeng Du, Lizhao Huang, Qiyun Cui, Donghong Li, Yuanqing |
description | Abstract
Meditation, mental training that aims to improve one’s ability to regulate their cognition, has been widely applied in clinical medicine. However, the mechanism by which meditation affects brain activity is still unclear. To explore this question, electroencephalogram data were recorded in 20 long-term meditators and 20 nonmeditators during 2 high-level cognitive tasks (meditation and mental calculation) and a relaxed resting state (control). Then, the power spectral density and phase synchronization of the electroencephalogram were extracted and compared between these 2 groups. In addition, machine learning was used to discriminate the states within each group. We found that the meditation group showed significantly higher classification accuracy and calculation efficiency than the control group. Then, during the calculation task, both the power and global phase synchronism of the gamma response decreased in meditators compared to their relaxation state; yet, no such change was observed in the control group. A potential explanation for our observations is that meditation improved the flexibility of the brain through neural plastic mechanism. In conclusion, we provided robust evidence that long-term meditation experience could produce detectable neurophysiological changes in brain activity, which possibly enhance the functional segregation and/or specialization in the brain. |
doi_str_mv | 10.1093/cercor/bhae288 |
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Meditation, mental training that aims to improve one’s ability to regulate their cognition, has been widely applied in clinical medicine. However, the mechanism by which meditation affects brain activity is still unclear. To explore this question, electroencephalogram data were recorded in 20 long-term meditators and 20 nonmeditators during 2 high-level cognitive tasks (meditation and mental calculation) and a relaxed resting state (control). Then, the power spectral density and phase synchronization of the electroencephalogram were extracted and compared between these 2 groups. In addition, machine learning was used to discriminate the states within each group. We found that the meditation group showed significantly higher classification accuracy and calculation efficiency than the control group. Then, during the calculation task, both the power and global phase synchronism of the gamma response decreased in meditators compared to their relaxation state; yet, no such change was observed in the control group. A potential explanation for our observations is that meditation improved the flexibility of the brain through neural plastic mechanism. In conclusion, we provided robust evidence that long-term meditation experience could produce detectable neurophysiological changes in brain activity, which possibly enhance the functional segregation and/or specialization in the brain.</description><identifier>ISSN: 1047-3211</identifier><identifier>ISSN: 1460-2199</identifier><identifier>EISSN: 1460-2199</identifier><identifier>DOI: 10.1093/cercor/bhae288</identifier><identifier>PMID: 39024158</identifier><language>eng</language><publisher>United States: Oxford University Press</publisher><subject>Adult ; Attention - physiology ; Brain - physiology ; Electroencephalography ; Female ; Humans ; Machine Learning ; Male ; Meditation ; Middle Aged</subject><ispartof>Cerebral cortex (New York, N.Y. 1991), 2024-07, Vol.34 (7)</ispartof><rights>The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com. 2024</rights><rights>The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c214t-41aaf42ff0c6f238ae87e8d48444caf8dc57251c8ffd4d6afd3415465984dc3e3</cites><orcidid>0000-0002-5160-2998</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,781,785,1585,27929,27930</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39024158$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Han, Yupeng</creatorcontrib><creatorcontrib>Du, Lizhao</creatorcontrib><creatorcontrib>Huang, Qiyun</creatorcontrib><creatorcontrib>Cui, Donghong</creatorcontrib><creatorcontrib>Li, Yuanqing</creatorcontrib><title>Enhancing specialization of attention-related EEG power and phase synchronism brain patterns by meditation</title><title>Cerebral cortex (New York, N.Y. 1991)</title><addtitle>Cereb Cortex</addtitle><description>Abstract
Meditation, mental training that aims to improve one’s ability to regulate their cognition, has been widely applied in clinical medicine. However, the mechanism by which meditation affects brain activity is still unclear. To explore this question, electroencephalogram data were recorded in 20 long-term meditators and 20 nonmeditators during 2 high-level cognitive tasks (meditation and mental calculation) and a relaxed resting state (control). Then, the power spectral density and phase synchronization of the electroencephalogram were extracted and compared between these 2 groups. In addition, machine learning was used to discriminate the states within each group. We found that the meditation group showed significantly higher classification accuracy and calculation efficiency than the control group. Then, during the calculation task, both the power and global phase synchronism of the gamma response decreased in meditators compared to their relaxation state; yet, no such change was observed in the control group. A potential explanation for our observations is that meditation improved the flexibility of the brain through neural plastic mechanism. In conclusion, we provided robust evidence that long-term meditation experience could produce detectable neurophysiological changes in brain activity, which possibly enhance the functional segregation and/or specialization in the brain.</description><subject>Adult</subject><subject>Attention - physiology</subject><subject>Brain - physiology</subject><subject>Electroencephalography</subject><subject>Female</subject><subject>Humans</subject><subject>Machine Learning</subject><subject>Male</subject><subject>Meditation</subject><subject>Middle Aged</subject><issn>1047-3211</issn><issn>1460-2199</issn><issn>1460-2199</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkDFPwzAQRi0EoqWwMiKPMITajpM6I6pKQarEAnN0tc_UVWoHOxUqv56UFlamu5PefdL3CLnm7J6zKh9rjDrE8XIFKJQ6IUMuS5YJXlWn_c7kJMsF5wNykdKaMT4RhTgng7xiQvJCDcl65lfgtfPvNLWoHTTuCzoXPA2WQteh3x9ZxAY6NHQ2m9M2fGKk4A1tV5CQpp3Xqxi8Sxu6jOA8bfeP0Se63NENGtf9JF6SMwtNwqvjHJG3x9nr9ClbvMyfpw-LTAsuu0xyACuFtUyXVuQKUE1QGamklBqsMrroW3CtrDXSlGBN3leRZVEpaXSO-YjcHnLbGD62mLp645LGpgGPYZvqnClRikJOih69P6A6hpQi2rqNbgNxV3NW7_3WB7_10W__cHPM3i77Zn_4r9AeuDsAYdv-F_YNG-OJRw</recordid><startdate>20240703</startdate><enddate>20240703</enddate><creator>Han, Yupeng</creator><creator>Du, Lizhao</creator><creator>Huang, Qiyun</creator><creator>Cui, Donghong</creator><creator>Li, Yuanqing</creator><general>Oxford University Press</general><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><orcidid>https://orcid.org/0000-0002-5160-2998</orcidid></search><sort><creationdate>20240703</creationdate><title>Enhancing specialization of attention-related EEG power and phase synchronism brain patterns by meditation</title><author>Han, Yupeng ; Du, Lizhao ; Huang, Qiyun ; Cui, Donghong ; Li, Yuanqing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c214t-41aaf42ff0c6f238ae87e8d48444caf8dc57251c8ffd4d6afd3415465984dc3e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adult</topic><topic>Attention - physiology</topic><topic>Brain - physiology</topic><topic>Electroencephalography</topic><topic>Female</topic><topic>Humans</topic><topic>Machine Learning</topic><topic>Male</topic><topic>Meditation</topic><topic>Middle Aged</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Han, Yupeng</creatorcontrib><creatorcontrib>Du, Lizhao</creatorcontrib><creatorcontrib>Huang, Qiyun</creatorcontrib><creatorcontrib>Cui, Donghong</creatorcontrib><creatorcontrib>Li, Yuanqing</creatorcontrib><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>Cerebral cortex (New York, N.Y. 1991)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Han, Yupeng</au><au>Du, Lizhao</au><au>Huang, Qiyun</au><au>Cui, Donghong</au><au>Li, Yuanqing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Enhancing specialization of attention-related EEG power and phase synchronism brain patterns by meditation</atitle><jtitle>Cerebral cortex (New York, N.Y. 1991)</jtitle><addtitle>Cereb Cortex</addtitle><date>2024-07-03</date><risdate>2024</risdate><volume>34</volume><issue>7</issue><issn>1047-3211</issn><issn>1460-2199</issn><eissn>1460-2199</eissn><abstract>Abstract
Meditation, mental training that aims to improve one’s ability to regulate their cognition, has been widely applied in clinical medicine. However, the mechanism by which meditation affects brain activity is still unclear. To explore this question, electroencephalogram data were recorded in 20 long-term meditators and 20 nonmeditators during 2 high-level cognitive tasks (meditation and mental calculation) and a relaxed resting state (control). Then, the power spectral density and phase synchronization of the electroencephalogram were extracted and compared between these 2 groups. In addition, machine learning was used to discriminate the states within each group. We found that the meditation group showed significantly higher classification accuracy and calculation efficiency than the control group. Then, during the calculation task, both the power and global phase synchronism of the gamma response decreased in meditators compared to their relaxation state; yet, no such change was observed in the control group. A potential explanation for our observations is that meditation improved the flexibility of the brain through neural plastic mechanism. In conclusion, we provided robust evidence that long-term meditation experience could produce detectable neurophysiological changes in brain activity, which possibly enhance the functional segregation and/or specialization in the brain.</abstract><cop>United States</cop><pub>Oxford University Press</pub><pmid>39024158</pmid><doi>10.1093/cercor/bhae288</doi><orcidid>https://orcid.org/0000-0002-5160-2998</orcidid></addata></record> |
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source | MEDLINE; Oxford University Press Journals All Titles (1996-Current) |
subjects | Adult Attention - physiology Brain - physiology Electroencephalography Female Humans Machine Learning Male Meditation Middle Aged |
title | Enhancing specialization of attention-related EEG power and phase synchronism brain patterns by meditation |
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