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Open and reproducible neuroimaging: From study inception to publication

Guiomar Niso, Rotem Botvinik-Nezer, Stefan Appelhoff, Alejandro De la Vega, Oscar Esteban, Joset A. Etzel, Karolina Finc, Melanie Ganz, Rémi Gau, Yaroslav O. Halchenko, Peer Herholz, Agah Karakuzu, David B. Keator, Christopher J. Markiewicz, Camille Maumet, Cyril R. Pernet, Franco Pestilli, Nazek Queder, Tina Schmitt, Weronika Sojka, Adina S. Wagner, Kirstie J. Whitaker and Jochem W. Rieger

Article (2022)

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Abstract

Empirical observations of how labs conduct research indicate that the adoption rate of open practices for transparent, reproducible, and collaborative science remains in its infancy. This is at odds with the overwhelming evidence for the necessity of these practices and their benefits for individual researchers, scientific progress, and society in general. To date, information required for implementing open science practices throughout the different steps of a research project is scattered among many different sources. Even experienced researchers in the topic find it hard to navigate the ecosystem of tools and to make sustainable choices. Here, we provide an integrated overview of community-developed resources that can support collaborative, open, reproducible, replicable, robust and generalizable neuroimaging throughout the entire research cycle from inception to publication and across different neuroimaging modalities. We review tools and practices supporting study inception and planning, data acquisition, research data management, data processing and analysis, and research dissemination. An online version of this resource can be found at https://oreoni.github.io. We believe it will prove helpful for researchers and institutions to make a successful and sustainable move towards open and reproducible science and to eventually take an active role in its future development.

Uncontrolled Keywords

open science; reproducibility; MRI; PET; MEG; EEG

Subjects: 1900 Biomedical engineering > 1900 Biomedical engineering
1900 Biomedical engineering > 1901 Biomedical technology
2500 Electrical and electronic engineering > 2500 Electrical and electronic engineering
Department: Institut de génie biomédical
Funders: AXA Reseach Fund, NIH CRCNS : US-France Data Sharing Proposal, Weizmann Institute of Science -Israel National Postdoctoral Award Program for Advancing Women in Science, National Institutes of Health Grant, Swiss National Science Foundation (SNSF) - Project 185872, Polish National Agency for Academic Exchange - Bekker Programme, Elsass Foundation, Canada First Research Excellence Fund, NIH National Institute Of Mental Health, Unifying Neuroscience and Artificial Intelligence - Québec, TransMedTech Intitute - Postdoc Fellowship, Nordisk Fonden, National Science Foundation, NIH National Institute of Biomedical Imaging and Bioengineering (NIBIB), Microsoft Investigator Fellowship, EPSRC Grant - UK Research and Innovation Strategic Priorities Fund, EPSRC Grant - The Alan Turing Institute, DFG Device Center Grant, DFG Grant of the Excellence Strategy
Grant number: NIBIB (USA) R01 EB030896, ANR-20-NEUC-0004-01, 5R01MH109682, 185872, RF1MH121867, R37MH066078, PPN/BEK/2020/1/00279/U/00001, 18-3-0147, 1P41EB019936-01A1, NIH-NIBIB P41 EB019936, R01MH096906, RF1 MH120021, NNF20OC0063277, IIS 1636893, BCS 1734853, 1R01EB029272, NIH NIMH 1R01MH126699, 1RF1MH120021, EP/T001569/1, EP/N510129/1, INST 184/216-1, 390895286, EXC 2177/1
PolyPublie URL: https://publications.polymtl.ca/52127/
Journal Title: NeuroImage (vol. 263)
Publisher: Elsevier
DOI: 10.1016/j.neuroimage.2022.119623
Official URL: https://doi.org/10.1016/j.neuroimage.2022.119623
Date Deposited: 18 Apr 2023 14:59
Last Modified: 05 Apr 2024 14:20
Cite in APA 7: Niso, G., Botvinik-Nezer, R., Appelhoff, S., De la Vega, A., Esteban, O., Etzel, J. A., Finc, K., Ganz, M., Gau, R., Halchenko, Y. O., Herholz, P., Karakuzu, A., Keator, D. B., Markiewicz, C. J., Maumet, C., Pernet, C. R., Pestilli, F., Queder, N., Schmitt, T., ... Rieger, J. W. (2022). Open and reproducible neuroimaging: From study inception to publication. NeuroImage, 263, 119623 (19 pages). https://doi.org/10.1016/j.neuroimage.2022.119623

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