Please use this identifier to cite or link to this item:
http://elar.urfu.ru/handle/10995/111752
Title: | #EEGManyLabs: Investigating the Replicability of Influential EEG Experiments |
Authors: | Pavlov, Y. G. Adamian, N. Appelhoff, S. Arvaneh, M. Benwell, C. S. Y. Beste, C. Bland, A. R. Bradford, D. E. Bublatzky, F. Busch, N. A. Clayson, P. E. Cruse, D. Czeszumski, A. Dreber, A. Dumas, G. Ehinger, B. Ganis, G. He, X. Hinojosa, J. A. Huber-Huber, C. Inzlicht, M. Jack, B. N. Johannesson, M. Jones, R. Kalenkovich, E. Kaltwasser, L. Karimi-Rouzbahani, H. Keil, A. König, P. Kouara, L. Kulke, L. Ladouceur, C. D. Langer, N. Liesefeld, H. R. Luque, D. MacNamara, A. Mudrik, L. Muthuraman, M. Neal, L. B. Nilsonne, G. Niso, G. Ocklenburg, S. Oostenveld, R. Pernet, C. R. Pourtois, G. Ruzzoli, M. Sass, S. M. Schaefer, A. Senderecka, M. Snyder, J. S. Tamnes, C. K. Tognoli, E. van Vugt, M. K. Verona, E. Vloeberghs, R. Welke, D. Wessel, J. R. Zakharov, I. Mushtaq, F. |
Issue Date: | 2021 |
Publisher: | Masson SpA Elsevier BV |
Citation: | #EEGManyLabs: Investigating the Replicability of Influential EEG Experiments / Y. G. Pavlov, N. Adamian, S. Appelhoff et al. // Cortex. — 2021. — Vol. 144. — P. 213-229. |
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. © 2021 The Authors. |
Keywords: | COGNITIVE NEUROSCIENCE EEG ERP MANY LABS OPEN SCIENCE REPLICATION ARTICLE COGNITION CONTROLLED STUDY ELECTROENCEPHALOGRAM ELECTROENCEPHALOGRAPHY FORECASTING HUMAN HUMAN EXPERIMENT PREDICTION NEUROSCIENCE REPRODUCIBILITY HUMANS NEUROSCIENCES REPRODUCIBILITY OF RESULTS |
URI: | http://elar.urfu.ru/handle/10995/111752 |
Access: | info:eu-repo/semantics/openAccess |
RSCI ID: | 46041950 |
SCOPUS ID: | 85105281725 |
WOS ID: | 000753629200001 |
PURE ID: | 28890692 |
ISSN: | 0010-9452 |
DOI: | 10.1016/j.cortex.2021.03.013 |
Appears in Collections: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
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