Code has become central to neuroscience, and the neuroscience community must take steps to ensure its reproducibility and best coding practices. Improving code readability benefits individual researchers and the wider neuroscience community.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$189.00 per year
only $15.75 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
References
Hettrick, S. It’s impossible to conduct research without software, say 7 out of 10 UK researchers. Software Sustainability Institute, https://software.ac.uk/blog/2014-12-04-its-impossible-conduct-research-without-software-say-7-out-10-uk-researchers (2014).
Miller, G. A scientist’s nightmare: software problem leads to five retractions. Science 314, 1856–1857 (2006).
Mumford J., et al. Keep calm and scan on. Organization for Human Brain Mapping, https://www.ohbmbrainmappingblog.com/blog/keep-calm-and-scan-on (2016).
Eglen, S., Marwick, B., Halchenko, Y. et al. Toward standard practices for sharing computer code and programs in neuroscience. Nat. Neurosci. 20, 770–773 (2017).
Singh Chawla, D. Critiqued coronavirus simulation gets thumbs up from code-checking efforts. Nature 582, 323–324 (2020).
Martin, R. C. Clean code: a handbook of agile software craftsmanship. Pearson Education (2009).
Wilson, G. et al. Good enough practices in scientific computing. PLoS Comput. Biol. 13, e1005510 (2017).
Hagan, A. K. et al. Ten simple rules to increase computational skills among biologists with Code Clubs. PLoS Comput. Biol. 16, e1008119 (2020).
Reviewing computational methods. Nat. Methods 12, 1099 (2015).
Acknowledgements
The authors gratefully acknowledge S. Eglen, J. Kirchner and G. Laurent for helpful feedback.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Related links
FENS (Federation of European Neuroscience Societies) Job Market: https://www.fens.org/News-Activities/Jobs/?pid=509%7C508&key=python%7Cmatlab%7Cprogramming
Git: https://git-scm.com/
Guide for reproducible research: https://the-turing-way.netlify.app/reproducible-research/reproducible-research.html
How to cite and describe software: https://www.software.ac.uk/how-cite-software
Jupyter: https://jupyter.org/
Nature journals’ reporting standards and availability: https://www.nature.com/nature-research/editorial-policies/reporting-standards
NEST: https://www.nest-simulator.org/publications/index.php
Research software engineers: https://researchsoftware.org/
The Carpentries: https://carpentries.org/
Rights and permissions
About this article
Cite this article
Riquelme, J.L., Gjorgjieva, J. Towards readable code in neuroscience. Nat Rev Neurosci 22, 257–258 (2021). https://doi.org/10.1038/s41583-021-00450-y
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41583-021-00450-y