Scanning the horizon: towards transparent and reproducible neuroimaging research. Poldrack, R. A., Baker, C. I., Durnez, J., Gorgolewski, K. J., Matthews, P. M., Munafò, M. R., Nichols, T. E., Poline, J., Vul, E., & Yarkoni, T. Nature Reviews Neuroscience, 18(2):115–126, February, 2017. ![Scanning the horizon: towards transparent and reproducible neuroimaging research [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{poldrack_scanning_2017,
title = {Scanning the horizon: towards transparent and reproducible neuroimaging research},
volume = {18},
issn = {1471-003X, 1471-0048},
shorttitle = {Scanning the horizon},
url = {https://www.nature.com/articles/nrn.2016.167},
doi = {10.1038/nrn.2016.167},
abstract = {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.},
language = {en},
number = {2},
urldate = {2023-06-02},
journal = {Nature Reviews Neuroscience},
author = {Poldrack, Russell A. and Baker, Chris I. and Durnez, Joke and Gorgolewski, Krzysztof J. and Matthews, Paul M. and Munafò, Marcus R. and Nichols, Thomas E. and Poline, Jean-Baptiste and Vul, Edward and Yarkoni, Tal},
month = feb,
year = {2017},
keywords = {Meta-research, Methodology, Replication, unread},
pages = {115--126},
}
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