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 et Jochem W. Rieger
Article de revue (2022)
Document en libre accès dans PolyPublie et chez l'éditeur officiel |
|
Libre accès au plein texte de ce document Version officielle de l'éditeur Conditions d'utilisation: Creative Commons: Attribution-Pas d'utilisation commerciale-Pas de modification (CC BY-NC-ND) Télécharger (2MB) |
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.
Mots clés
open science; reproducibility; MRI; PET; MEG; EEG
Sujet(s): |
1900 Génie biomédical > 1900 Génie biomédical 1900 Génie biomédical > 1901 Technologie biomédicale 2500 Génie électrique et électronique > 2500 Génie électrique et électronique |
---|---|
Département: | Institut de génie biomédical |
Organismes subventionnaires: | 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 |
Numéro de subvention: | 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 |
URL de PolyPublie: | https://publications.polymtl.ca/52127/ |
Titre de la revue: | NeuroImage (vol. 263) |
Maison d'édition: | Elsevier |
DOI: | 10.1016/j.neuroimage.2022.119623 |
URL officielle: | https://doi.org/10.1016/j.neuroimage.2022.119623 |
Date du dépôt: | 18 avr. 2023 14:59 |
Dernière modification: | 05 avr. 2024 14:20 |
Citer en 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 |
---|---|
Statistiques
Total des téléchargements à partir de PolyPublie
Téléchargements par année
Provenance des téléchargements
Dimensions