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Good scientific practice in EEG and MEG research: Progress and perspectives

审查 能力(人力资源) 工程伦理学 工作(物理) 计算机科学 心理学 数据科学 知识管理 公共关系 政治学 社会心理学 机械工程 法学 工程类
作者
Guiomar Niso,Laurens R. Krol,Etienne Combrisson,Anne‐Sophie Dubarry,Madison Elliott,François Clément,Yseult Héjja-Brichard,Sophie K. Herbst,Karim Jerbi,Vanja Ković,Katia Lehongre,Steven J. Luck,Manuel Mercier,John C. Mosher,Yuri G. Pavlov,Aina Puce,Antonio Schettino,Daniele Schön,Walter Sinnott‐Armstrong,Bertille Somon,Аnđela Šoškić,Suzy J Styles,Roni Tibon,Martina G. Vilas,Marijn van Vliet,Maximilien Chaumon
出处
期刊:NeuroImage [Elsevier BV]
卷期号:257: 119056-119056 被引量:24
标识
DOI:10.1016/j.neuroimage.2022.119056
摘要

Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.
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