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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.

Original publication

DOI

10.1038/nrn.2016.167

Type

Journal article

Journal

Nature reviews. Neuroscience

Publication Date

02/2017

Volume

18

Pages

115 - 126

Addresses

Department of Psychology and Stanford Center for Reproducible Neuroscience, Stanford University, Stanford, California 94305, USA.

Keywords

Humans, Magnetic Resonance Imaging, Reproducibility of Results, Software, Statistics as Topic, Practice Guidelines as Topic, Functional Neuroimaging