  Most scientists need software to perform their research (Barker et al., 2020;
Carver et al., 2022; Hettrick, 2014; Hettrick et al., 2014; Switters and 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 will 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
growth of our software landscape to the benefit of all.
