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#脑电图多实验室研究:探究有影响力的脑电图实验的可重复性

#EEGManyLabs: Investigating the replicability of influential EEG experiments.

作者信息

Pavlov Yuri G, Adamian Nika, Appelhoff Stefan, Arvaneh Mahnaz, Benwell Christopher S Y, Beste Christian, Bland Amy R, Bradford Daniel E, Bublatzky Florian, Busch Niko A, Clayson Peter E, Cruse Damian, Czeszumski Artur, Dreber Anna, Dumas Guillaume, Ehinger Benedikt, Ganis Giorgio, He Xun, Hinojosa José A, Huber-Huber Christoph, Inzlicht Michael, Jack Bradley N, Johannesson Magnus, Jones Rhiannon, Kalenkovich Evgenii, Kaltwasser Laura, Karimi-Rouzbahani Hamid, Keil Andreas, König Peter, Kouara Layla, Kulke Louisa, Ladouceur Cecile D, Langer Nicolas, Liesefeld Heinrich R, Luque David, MacNamara Annmarie, Mudrik Liad, Muthuraman Muthuraman, Neal Lauren B, Nilsonne Gustav, Niso Guiomar, Ocklenburg Sebastian, Oostenveld Robert, Pernet Cyril R, Pourtois Gilles, Ruzzoli Manuela, Sass Sarah M, Schaefer Alexandre, Senderecka Magdalena, Snyder Joel S, Tamnes Christian K, Tognoli Emmanuelle, van Vugt Marieke K, Verona Edelyn, Vloeberghs Robin, Welke Dominik, Wessel Jan R, Zakharov Ilya, Mushtaq Faisal

机构信息

University of Tuebingen, Germany; Ural Federal University, Russia.

University of Aberdeen, UK.

出版信息

Cortex. 2021 Nov;144:213-229. doi: 10.1016/j.cortex.2021.03.013. Epub 2021 Apr 2.

Abstract

There is growing awareness across the neuroscience community that the replicability of findings about the relationship between brain activity and cognitive phenomena can be improved by conducting studies with high statistical power that adhere to well-defined and standardised analysis pipelines. Inspired by recent efforts from the psychological sciences, and with the desire to examine some of the foundational findings using electroencephalography (EEG), we have launched #EEGManyLabs, a large-scale international collaborative replication effort. Since its discovery in the early 20th century, EEG has had a profound influence on our understanding of human cognition, but there is limited evidence on the replicability of some of the most highly cited discoveries. After a systematic search and selection process, we have identified 27 of the most influential and continually cited studies in the field. We plan to directly test the replicability of key findings from 20 of these studies in teams of at least three independent laboratories. The design and protocol of each replication effort will be submitted as a Registered Report and peer-reviewed prior to data collection. Prediction markets, open to all EEG researchers, will be used as a forecasting tool to examine which findings the community expects to replicate. This project will update our confidence in some of the most influential EEG findings and generate a large open access database that can be used to inform future research practices. Finally, through this international effort, we hope to create a cultural shift towards inclusive, high-powered multi-laboratory collaborations.

摘要

神经科学界越来越意识到,通过开展具有高统计效力且遵循明确和标准化分析流程的研究,可以提高关于大脑活动与认知现象之间关系的研究结果的可重复性。受心理学领域近期工作的启发,并出于使用脑电图(EEG)检验一些基础研究结果的愿望,我们发起了#EEGManyLabs,这是一项大规模的国际合作重复研究工作。自20世纪初被发现以来,脑电图对我们理解人类认知产生了深远影响,但对于一些被高度引用的发现的可重复性,证据有限。经过系统的搜索和筛选过程,我们确定了该领域27项最具影响力且被持续引用的研究。我们计划在至少三个独立实验室组成的团队中,直接检验其中20项研究的关键结果的可重复性。每项重复研究工作的设计和方案将作为预注册报告提交,并在数据收集前进行同行评审。面向所有脑电图研究人员的预测市场将用作一种预测工具,以检验该领域预期哪些结果能够被重复。这个项目将更新我们对一些最具影响力的脑电图研究结果的信心,并生成一个大型开放获取数据库,可用于为未来的研究实践提供参考。最后,通过这项国际努力,我们希望营造一种文化转变,朝着包容性、高效力的多实验室合作方向发展。

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