Poldrack Russell A, Baker Chris I, Durnez Joke, Gorgolewski Krzysztof J, Matthews Paul M, Munafò Marcus R, Nichols Thomas E, Poline Jean-Baptiste, Vul Edward, Yarkoni Tal
Department of Psychology and Stanford Center for Reproducible Neuroscience, Stanford University, Stanford, California 94305, USA.
Laboratory of Brain and Cognition, National Institute of Mental Health, US National Institutes of Health, Maryland 20892, USA.
Nat Rev Neurosci. 2017 Feb;18(2):115-126. doi: 10.1038/nrn.2016.167. Epub 2017 Jan 5.
Functional neuroimaging techniques have transformed our ability to probe the neurobiological basis of behaviour and are increasingly being applied by the wider neuroscience community. However, concerns have recently been raised that the conclusions that are drawn from some human neuroimaging studies are either spurious or not generalizable. Problems such as low statistical power, flexibility in data analysis, software errors and a lack of direct replication apply to many fields, but perhaps particularly to functional MRI. Here, we discuss these problems, outline current and suggested best practices, and describe how we think the field should evolve to produce the most meaningful and reliable answers to neuroscientific questions.
功能神经成像技术已经改变了我们探究行为神经生物学基础的能力，并且越来越多地被更广泛的神经科学界所应用。然而，最近有人担心，一些人类神经成像研究得出的结论要么是虚假的，要么不具有普遍性。统计功效低、数据分析的灵活性、软件错误和缺乏直接重复等问题适用于许多领域，但可能尤其适用于功能磁共振成像。在这里，我们讨论这些问题，概述当前和建议的最佳实践，并描述我们认为该领域应如何发展，以便为神经科学问题提供最有意义和最可靠的答案。
