The methodology and dataset of the coscience eeg-personality project – a large-scale, multi-laboratory project grounded in cooperative forking paths analysis

Katharina Paul, C. Short, A. Beauducel, Hannes Per Carsten, Kai Härpfer, J. Hennig, J. Hewig, A. Hildebrandt, Corinna Kührt, E. M. Mueller, A. Munk, Roman Osinsky, Elisa Porth, A. Riesel, J. Rodrigues, Christoph Scheffel, J. Stahl, A. Strobel, Jan Wacker
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Abstract

Despite a plethora of research, associations between individual differences in personality and electroencephalogram (EEG) parameters remain poorly understood due to concerns of low replicability and insufficiently powered data analyses due to relatively small effect sizes. The present article describes how a multi-laboratory team of EEG-personality researchers aims to alleviate this unsatisfactory status quo. In particular, the present article outlines the design and methodology of the project, provides a detailed overview of the resulting large-scale dataset that is available for use by future collaborators, and forms the basis for consistency and depth to the methodology of all resulting empirical articles. Through this article, we aim to inform researchers in the field of Personality Neuroscience of the freely available dataset. Furthermore, we assume that researchers will generally benefit from this detailed example of the implementation of cooperative forking paths analysis.
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coscience eye -personality项目的方法论和数据集-一个基于合作分叉路径分析的大型多实验室项目
尽管有大量的研究,但由于考虑到低可复制性和由于相对较小的效应量而导致的数据分析不足,人们对个性和脑电图(EEG)参数之间的个体差异之间的关联仍然知之甚少。本文描述了一个由脑电图人格研究人员组成的多实验室团队如何缓解这种不令人满意的现状。特别是,本文概述了该项目的设计和方法,提供了未来合作者可使用的大规模数据集的详细概述,并形成了所有最终实证文章方法一致性和深度的基础。通过这篇文章,我们的目标是告知人格神经科学领域的研究人员免费可用的数据集。此外,我们假设研究人员通常会从这个详细的实现合作分叉路径分析的例子中受益。
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