Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland.
Department of Psychology, Julius-Maximilians-University, Würzburg, Germany.
Elife. 2023 Aug 9;12:e85980. doi: 10.7554/eLife.85980.
Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability - in science in general, but also specifically in human neuroscience - have fueled an extensive debate. One important insight from this discourse is the need for larger samples, which naturally increases statistical power. An alternative is to increase the precision of measurements, which is the focus of this review. This option is often overlooked, even though statistical power benefits from increasing precision as much as from increasing sample size. Nonetheless, precision has always been at the heart of good scientific practice in human neuroscience, with researchers relying on lab traditions or rules of thumb to ensure sufficient precision for their studies. In this review, we encourage a more systematic approach to precision. We start by introducing measurement precision and its importance for well-powered studies in human neuroscience. Then, determinants for precision in a range of neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, and Endocrinology) are elaborated. We end by discussing how a more systematic evaluation of precision and the application of respective insights can lead to an increase in reproducibility in human neuroscience.
人类神经科学一直在探索可测量的极限。在过去的十年中,人们对科学(尤其是人类神经科学)中的统计能力和可重复性的担忧引发了广泛的争论。这场讨论的一个重要启示是需要更大的样本量,这自然会提高统计能力。另一种选择是提高测量精度,这是本篇综述的重点。尽管增加精度与增加样本量一样可以提高统计能力,但这种选择往往被忽视。尽管如此,精度一直是人类神经科学良好科学实践的核心,研究人员依赖实验室传统或经验法则来确保其研究有足够的精度。在这篇综述中,我们鼓励采取更系统的方法来提高精度。我们首先介绍测量精度及其对人类神经科学中有力研究的重要性。然后,详细阐述了一系列神经科学方法(MRI、M/EEG、EDA、眼动追踪和内分泌学)中的精度决定因素。最后,我们讨论了如何更系统地评估精度,并应用相关见解,从而提高人类神经科学的可重复性。