Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Department of Child and Adolescent Psychiatry and Psychology, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Trends Cogn Sci. 2023 Mar;27(3):282-301. doi: 10.1016/j.tics.2022.12.011. Epub 2023 Jan 30.
Network neuroscience has emerged as a leading method to study brain connectivity. The success of these investigations is dependent not only on approaches to accurately map connectivity but also on the ability to detect real effects in the data - that is, statistical power. We review the state of statistical power in the field and discuss sample size, effect size, measurement error, and network topology as key factors that influence the power of brain connectivity investigations. We use the term 'differential power' to describe how power can vary between nodes, edges, and graph metrics, leaving traces in both positive and negative connectome findings. We conclude with strategies for working with, rather than around, power in connectivity studies.
网络神经科学已成为研究大脑连接的主要方法。这些研究的成功不仅取决于准确绘制连接的方法，还取决于在数据中检测真实效应的能力，即统计功效。我们回顾了该领域的统计功效状态，并讨论了样本量、效应大小、测量误差和网络拓扑结构作为影响大脑连接研究功效的关键因素。我们使用“差异功效”一词来描述功效如何在节点、边缘和图度量之间变化，在正连通组学发现和负连通组学发现中都留下痕迹。最后，我们总结了在连接研究中处理功效而不是回避功效的策略。
