Comparative effectiveness of electroencephalogram-neurofeedback training of 3-45 frequency band on memory in healthy population: a network meta-analysis with systematic literature search.

IF 5.2 2区 医学 Q1 ENGINEERING, BIOMEDICAL
Wen-Hsiu Yeh, Ya-Ju Ju, Fu-Zen Shaw, Yu-Ting Liu
{"title":"Comparative effectiveness of electroencephalogram-neurofeedback training of 3-45 frequency band on memory in healthy population: a network meta-analysis with systematic literature search.","authors":"Wen-Hsiu Yeh, Ya-Ju Ju, Fu-Zen Shaw, Yu-Ting Liu","doi":"10.1186/s12984-025-01634-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To investigate which brain activity frequency of electroencephalogram (EEG)-neurofeedback training (NFT) was the most effective for enhancing working memory (WM) and episodic memory (EM) in healthy participants through network meta-analysis (NMA).</p><p><strong>Methods: </strong>Searched PubMed, Embase, and Cochrane Library for studies published from January 1990 to January 2025. We performed Bayesian NMA, pooling continuous outcome data using the standardized mean difference effect size (ES). Global and local evaluations of inconsistency were conducted using the chi-square test, side-splitting, and loop-specific approaches. A consistency model was applied and the global approach to inconsistency showed no significance. Efficacy ranks were determined using the surface under the cumulative ranking curve (SUCRA) for each intervention. Publication bias was assessed using the comparison-adjusted funnel plot and Egger's test. Finally, sensitivity analysis confirmed our findings' robustness.</p><p><strong>Results: </strong>Sixty studies were included, comprising 50 trials on WM and 24 trials on EM. While the global inconsistency analysis showed no significant inconsistency for WM (χ<sup>2</sup>(22) = 30.89, p = 0.10) and EM (χ<sup>2</sup>(10) = 13.48, p = 0.19), the consistency model exhibited the most significant difference between active control (AC) and alpha combined with working memory training (WMT) (ES of 6.64, p < 0.001) for WM, and between AC and alpha (ES of 0.84, p = 0.01) for EM. Alpha combined with WMT for WM (100%) and alpha NFT for EM (87.0%) also showed the highest efficacy according to the SUCRA. No publication bias was found for either type of memory. The sensitivity analysis for WM and EM aligns with the original results.</p><p><strong>Conclusion: </strong>Through NMA, alpha activity (7-13 Hz) may be a crucial frequency impacting memory. Brain activity combined with other training methods requires more robust studies for future investigation. This study registered with www.crd.york.ac.uk/prospero/ (CRD42024539656).</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"94"},"PeriodicalIF":5.2000,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020070/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of NeuroEngineering and Rehabilitation","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1186/s12984-025-01634-8","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: To investigate which brain activity frequency of electroencephalogram (EEG)-neurofeedback training (NFT) was the most effective for enhancing working memory (WM) and episodic memory (EM) in healthy participants through network meta-analysis (NMA).

Methods: Searched PubMed, Embase, and Cochrane Library for studies published from January 1990 to January 2025. We performed Bayesian NMA, pooling continuous outcome data using the standardized mean difference effect size (ES). Global and local evaluations of inconsistency were conducted using the chi-square test, side-splitting, and loop-specific approaches. A consistency model was applied and the global approach to inconsistency showed no significance. Efficacy ranks were determined using the surface under the cumulative ranking curve (SUCRA) for each intervention. Publication bias was assessed using the comparison-adjusted funnel plot and Egger's test. Finally, sensitivity analysis confirmed our findings' robustness.

Results: Sixty studies were included, comprising 50 trials on WM and 24 trials on EM. While the global inconsistency analysis showed no significant inconsistency for WM (χ2(22) = 30.89, p = 0.10) and EM (χ2(10) = 13.48, p = 0.19), the consistency model exhibited the most significant difference between active control (AC) and alpha combined with working memory training (WMT) (ES of 6.64, p < 0.001) for WM, and between AC and alpha (ES of 0.84, p = 0.01) for EM. Alpha combined with WMT for WM (100%) and alpha NFT for EM (87.0%) also showed the highest efficacy according to the SUCRA. No publication bias was found for either type of memory. The sensitivity analysis for WM and EM aligns with the original results.

Conclusion: Through NMA, alpha activity (7-13 Hz) may be a crucial frequency impacting memory. Brain activity combined with other training methods requires more robust studies for future investigation. This study registered with www.crd.york.ac.uk/prospero/ (CRD42024539656).

3-45频带脑电图-神经反馈训练对健康人群记忆的比较效果:系统文献检索的网络meta分析。
目的:通过网络荟萃分析(NMA)探讨脑电图-神经反馈训练(NFT)对健康被试的工作记忆(WM)和情景记忆(EM)最有效的脑活动频率。方法:检索PubMed、Embase和Cochrane图书馆1990年1月至2025年1月发表的研究。我们使用贝叶斯NMA,使用标准化平均差异效应大小(ES)汇集连续结果数据。使用卡方检验、侧分裂和环特异性方法对不一致性进行全局和局部评估。一致性模型的应用和全局方法的不一致性显示没有意义。采用累积排名曲线下曲面(SUCRA)确定每种干预措施的疗效等级。采用比较校正漏斗图和Egger检验评估发表偏倚。最后,敏感性分析证实了我们的发现的稳健性。结果:共纳入60项研究,其中WM试验50项,EM试验24项。整体不一致性分析显示,WM (χ2(22) = 30.89, p = 0.10)和EM (χ2(10) = 13.48, p = 0.19)无显著不一致性,一致性模型显示主动控制(AC)和α结合工作记忆训练(WMT) (ES为6.64,p)之间差异最显著。大脑活动与其他训练方法相结合,需要对未来的研究进行更有力的研究。本研究注册于www.crd.york.ac.uk/prospero/ (CRD42024539656)。
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 求助全文
来源期刊
Journal of NeuroEngineering and Rehabilitation
Journal of NeuroEngineering and Rehabilitation 工程技术-工程:生物医学
CiteScore
9.60
自引率
3.90%
发文量
122
审稿时长
24 months
期刊介绍: Journal of NeuroEngineering and Rehabilitation considers manuscripts on all aspects of research that result from cross-fertilization of the fields of neuroscience, biomedical engineering, and physical medicine & rehabilitation.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信