The Effects of Concentrative Meditation on the Electroencephalogram in Novice Meditators.

IF 1.6 4区 医学 Q3 CLINICAL NEUROLOGY Clinical EEG and Neuroscience Pub Date : 2023-03-01 DOI:10.1177/15500594211065897
Alexander T Duda, Adam R Clarke, Frances M De Blasio, Thomas W Rout, Robert J Barry
{"title":"The Effects of Concentrative Meditation on the Electroencephalogram in Novice Meditators.","authors":"Alexander T Duda,&nbsp;Adam R Clarke,&nbsp;Frances M De Blasio,&nbsp;Thomas W Rout,&nbsp;Robert J Barry","doi":"10.1177/15500594211065897","DOIUrl":null,"url":null,"abstract":"<p><p>Following investigations into the benefits of meditation on psychological health and well-being, research is now seeking to understand the mechanisms underlying these outcomes. This study aimed to identify natural alpha and theta frequency components during eyes-closed resting and concentrative meditation states and examined their differences within and between two testing sessions. Novice meditators had their EEG recorded during eyes-closed resting and concentrative meditation conditions, before and after engaging in a brief daily concentrative meditation practice for approximately one-month. Separate frequency Principal Components Analyses (f-PCA) yielded four spectral components of interest, congruent between both conditions and sessions: Delta-Theta-Alpha, Low Alpha, High Alpha, and Alpha-Beta. While all four components showed some increase in the meditation condition at the second session, only Low Alpha (∼9.5-10.0 Hz) showed similar increases while resting. These findings support the use of f-PCA as a novel method of data analysis in the investigation of psychophysiological states in meditation.</p>","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical EEG and Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/15500594211065897","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 2

Abstract

Following investigations into the benefits of meditation on psychological health and well-being, research is now seeking to understand the mechanisms underlying these outcomes. This study aimed to identify natural alpha and theta frequency components during eyes-closed resting and concentrative meditation states and examined their differences within and between two testing sessions. Novice meditators had their EEG recorded during eyes-closed resting and concentrative meditation conditions, before and after engaging in a brief daily concentrative meditation practice for approximately one-month. Separate frequency Principal Components Analyses (f-PCA) yielded four spectral components of interest, congruent between both conditions and sessions: Delta-Theta-Alpha, Low Alpha, High Alpha, and Alpha-Beta. While all four components showed some increase in the meditation condition at the second session, only Low Alpha (∼9.5-10.0 Hz) showed similar increases while resting. These findings support the use of f-PCA as a novel method of data analysis in the investigation of psychophysiological states in meditation.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
集中冥想对初学冥想者脑电图的影响。
在调查了冥想对心理健康和幸福的好处之后,现在的研究正在寻求理解这些结果背后的机制。本研究旨在确定闭眼休息和集中冥想状态下的自然α和θ频率成分,并检查它们在两个测试阶段内和之间的差异。研究人员记录了冥想新手在闭眼休息和集中冥想状态下的脑电图,在进行为期大约一个月的简短的日常集中冥想练习之前和之后。独立频率主成分分析(f-PCA)产生了四个感兴趣的频谱成分,在两个条件和会话之间是一致的:Delta-Theta-Alpha, Low -Alpha, High -Alpha和Alpha- beta。虽然在第二阶段的冥想条件下,所有四个成分都显示出一些增加,但只有低α (~ 9.5-10.0 Hz)在休息时显示出类似的增加。这些发现支持使用f-PCA作为一种新的数据分析方法来研究冥想中的心理生理状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Clinical EEG and Neuroscience
Clinical EEG and Neuroscience 医学-临床神经学
CiteScore
5.20
自引率
5.00%
发文量
66
审稿时长
>12 weeks
期刊介绍: Clinical EEG and Neuroscience conveys clinically relevant research and development in electroencephalography and neuroscience. Original articles on any aspect of clinical neurophysiology or related work in allied fields are invited for publication.
期刊最新文献
Deep Learning-Based Artificial Intelligence Can Differentiate Treatment-Resistant and Responsive Depression Cases with High Accuracy Deep Brain Stimulator (DBS) Artifact in the EEG of a Pediatric Patient. Classification of BCI Multiclass Motor Imagery Task Based on Artificial Neural Network. Transcranial Alternating Current Stimulation Alters Auditory Steady-State Oscillatory Rhythms and Their Cross-Frequency Couplings. Comparison of Spectral Analysis of Gamma Band Activity During Actual and Imagined Movements as a Cognitive Tool.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1