The analytical flexibility of EEG has called into question the robustness of EEG findings. Because there is myriad of ways to process and analyze EEG data, analysis pipelines differ a lot from study to study. To what extent different, but plausible pipelines create various conclusions and assumptions is still unknown. The EEGManyPipelines project is inspired by other recent projects involving many independent analysis teams to investigate a) how different analysts approach a given data set and

more »

... ) how analysis approaches affect the obtained results. Participants in this project will be given access to an EEG dataset and will be asked to analyze it using an analysis pipeline that they consider suitable for their research. Participants will then send us their findings as well as a thorough description of the analysis pipeline. These reports will be used to map the variety of analytic pipelines as well as the impact of pipeline parameters on the final results. EEGManyPipelines will assist examine the robustness of EEG findings across alternative studies, identify potential (sub)optimal analysis pipelines, and suggest standards for describing EEG analyses in publications in this way. As a result, we believe that EEGManyPipelines will contribute to increasing the credibility of EEG research and the quality of analysis, as well as inspiring new guidelines for conducting and publishing EEG investigations.