TY - JOUR
T1 - Cycling on the Freeway
T2 - The perilous state of open-source neuroscience software
AU - Westner, Britta U.
AU - McCloy, Daniel R.
AU - Larson, Eric
AU - Gramfort, Alexandre
AU - Katz, Daniel S.
AU - Smith, Arfon M.
AU - Delorme, Arnaud
AU - Litvak, Vladimir
AU - Makeig, Scott
AU - Oostenveld, Robert
AU - Schoffelen, Jan Matthijs
AU - Tierney, Tim M.
N1 - e.g., US National Science Foundation’s POSE program and CSSI “Transition to Sustainability” programs, stand-alone software- and developer/maintainer-focused grants as well as open science supplements to research grants from the US National Institutes of Health, the UK Research and Innovation office, the national plan for open science (“plan national pour la science ouverte”) of the French government, and software-focused grants from organizations like CZI, the Sloan Foundation, and the Simons Foundation
The authors thank Sylvain Baillet for valuable discussion and comments on a previous version of this manuscript. This project has been made possible in part by grant number 2021-237679 from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation. V.L. and T.M.T. were supported by the Wellcome Centre for Human Neuroimaging, funded by Wellcome [203147/Z/16/Z]. T.M.T. is funded by a fellowship from Epilepsy Research UK and Young Epilepsy (FY2101).
PY - 2025/5/2
Y1 - 2025/5/2
N2 - Most scientists need software to perform their research (Barker et al., 2020; Carver et al., 2022; Hettrick, 2014; Hettrick et al., 2014; Switters & Osimo, 2019), and neuroscientists are no exception. Whether we work with reaction times, electrophysiological signals, or magnetic resonance imaging data, we rely on software to acquire, analyze, and statistically evaluate the raw data we obtain—or to generate such data if we work with simulations. In recent years, there has been a shift toward relying on free, open-source scientific software (FOSSS) for neuroscience data analysis (Poldrack et al., 2019), in line with the broader open science movement in academia (McKiernan et al., 2016) and wider industry trends (Eghbal, 2016). Importantly, FOSSS is typically developed by working scientists (not professional software developers), which sets up a precarious situation given the nature of the typical academic workplace wherein academics, especially in their early careers, are on short- and fixed-term contracts. In this paper, we argue that the existing ecosystem of neuroscientific open-source software is brittle, and discuss why and how the neuroscience community needs to come together to ensure a healthy software ecosystem to the benefit of all.
AB - Most scientists need software to perform their research (Barker et al., 2020; Carver et al., 2022; Hettrick, 2014; Hettrick et al., 2014; Switters & Osimo, 2019), and neuroscientists are no exception. Whether we work with reaction times, electrophysiological signals, or magnetic resonance imaging data, we rely on software to acquire, analyze, and statistically evaluate the raw data we obtain—or to generate such data if we work with simulations. In recent years, there has been a shift toward relying on free, open-source scientific software (FOSSS) for neuroscience data analysis (Poldrack et al., 2019), in line with the broader open science movement in academia (McKiernan et al., 2016) and wider industry trends (Eghbal, 2016). Importantly, FOSSS is typically developed by working scientists (not professional software developers), which sets up a precarious situation given the nature of the typical academic workplace wherein academics, especially in their early careers, are on short- and fixed-term contracts. In this paper, we argue that the existing ecosystem of neuroscientific open-source software is brittle, and discuss why and how the neuroscience community needs to come together to ensure a healthy software ecosystem to the benefit of all.
KW - electrophysiology
KW - neuroscience
KW - open science
KW - open source
UR - https://www.scopus.com/pages/publications/105010258743
UR - https://www.scopus.com/pages/publications/105010258743#tab=citedBy
U2 - 10.1162/imag_a_00554
DO - 10.1162/imag_a_00554
M3 - Article
C2 - 40800958
AN - SCOPUS:105010258743
SN - 2837-6056
VL - 3
JO - Imaging Neuroscience
JF - Imaging Neuroscience
M1 - imag_a_00554
ER -