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#EEGManyLabs: Investigating the Replicability of Influential EEG Experiments

Pavlov, Yuri G and Adamian, Nika and Appelhoff, Stefan and Arvaneh, Mahnaz and Benwell, Christopher SY and Beste, Christian and Bland, Amy R and Bradford, Daniel E and Bublatzky, Florian and Busch, Niko A and Clayson, Peter E and Cruse, Damian and Czeszumski, Artur and Dreber, Anna and Dumas, Guillaume and Ehinger, Benedikt and Giorgio, Ganis and He, Xun and Hinojosa, José A and Huber-Huber, Christoph and Inzlicht, Michael and Jack, Bradley N and Johannesson, Magnus and Jones, Rhiannon and Kalenkovich, Evgenii and Kaltwasser, Laura and Karimi-Rouzbahani, Hamid and Keil, Andreas and König, Peter and Kouara, Layla and Kulke, Louisa and Ladouceur, Cecile D and Langer, Nicolas and Liesefeld, Heinrich R and Luque, David and MacNamara, Annmarie and Mudrik, Liad and Muthuraman, Muthuraman and Neal, Lauren B and Nilsonne, Gustav and Niso, Guiomar and Ocklenburg, Sebastian and Oostenveld, Robert and Pernet, Cyril R and Pourtois, Gilles and Ruzzoli, Manuela and Sass, Sarah M and Schaefer, Alexandre and Senderecka, Magdalena and Snyder, Joel S and Tamnes, Christian K and Tognoli, Emmanuelle and van Vugt, Marieke K and Verona, Edelyn and Vloeberghs, Robin and Welke, Dominik and Wessel, Jan R and Zakharov, Ilya and Mushtaq, Faisal (2021) #EEGManyLabs: Investigating the Replicability of Influential EEG Experiments. Cortex. ISSN 0010-9452

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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.

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