• Mariella Paul, Gisela H Govaart, and Antonio Schettino.
• Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraβe 1a, 04103 Leipzig, Germany; Humboldt-Universität zu Berlin, Faculty of Philosophy, Berlin School of Mind and Brain, Luisenstraße 56, 10117 Berlin, Germany; Psychology of Language Department, University of Göttingen, Goßlerstraße 14, 37073 Göttingen, Germany.
• Int J Psychophysiol. 2021 Jun 1; 164: 52-63.

AbstractA combination of confirmation bias, hindsight bias, and pressure to publish may prompt the (unconscious) exploration of various methodological options and reporting only the ones that lead to a (statistically) significant outcome. This undisclosed analytic flexibility is particularly relevant in EEG research, where a myriad of preprocessing and analysis pipelines can be used to extract information from complex multidimensional data. One solution to limit confirmation and hindsight bias by disclosing analytic choices is preregistration: researchers write a time-stamped, publicly accessible research plan with hypotheses, data collection plan, and the intended preprocessing and statistical analyses before the start of a research project. In this manuscript, we present an overview of the problems associated with undisclosed analytic flexibility, discuss why and how EEG researchers would benefit from adopting preregistration, provide guidelines and examples on how to preregister data preprocessing and analysis steps in typical ERP studies, and conclude by discussing possibilities and limitations of this open science practice.Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.

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