A registered report format for Psychophysiology

Open Science in human electrophysiology

Open science practices are gaining momentum in psychophysiological research, but at the nascent stage of this special issue in the International Journal of Psychophysiology there was no systematic collection of resources to support the adoption of open science practices specific to studies of human electrophysiology (EEG). The purpose of this special issue was to gather and provide resources that identify the idiosyncratic considerations and implications of open science practices specifically for studies of human EEG and event-related potentials (ERPs). Papers also show the importance of promoting good scientific practices in the application of open science principles to EEG and ERPs. This introduction to the special issue provides a roadmap for identifying the resources necessary to begin and improve the application of open science principles to EEG and ERP research. We are optimistic that open science practices will help increase the robustness, rigor, and replicability of EEG research and ultimately become the norm in studies of EEG and ERPs.

Making ERP research more transparent: Guidelines for preregistration

A 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.

Open science in psychophysiology: An overview of challenges and emerging solutions

The present review is the result of a one-day workshop on open science, held at the Annual Meeting of the Society for Psychophysiological Research in Washington, DC, September 2019. The contributors represent psychophysiological researchers at different career stages and from a wide spectrum of institutions. The state of open science in psychophysiology is discussed from different perspectives, highlighting key challenges, potential benefits, and emerging solutions that are intended to facilitate open science practices. Three domains are emphasized: data sharing, preregistration, and multi-site studies. In the context of these broader domains, we present potential implementations of specific open science procedures such as data format harmonization, power analysis, data, presentation code and analysis pipeline sharing, suitable for psychophysiological research. Practical steps are discussed that may be taken to facilitate the adoption of open science practices in psychophysiology. These steps include (1) promoting broad and accessible training in the skills needed to implement open science practices, such as collaborative research and computational reproducibility initiatives, (2) establishing mechanisms that provide practical assistance in sharing of processing pipelines, presentation code, and data in an efficient way, and (3) improving the incentive structure for open science approaches. Throughout the manuscript, we provide references and links to available resources for those interested in adopting open science practices in their research.