Editorial: Reproducibility in neuroscience

Scientific progress depends on the ability to independently repeat and validate key scientific findings. To verify the rigor, robustness, and validity of a research study, scientists test if they can reach the same conclusions when they use the same methods, data, and code (reproducible result) or when they use a different, independent model, technology, or tool (replicable result). Several large-scale efforts have revealed significant challenges related to reproducing and replicating research studies, including lack of access to research reagents, detailed methodology, or source code developed for the study (Manninen et al., 2018; Errington et al., 2021; Botvinik-Nezer and Wager, 2022). In addition, studies that “merely” repeat a published work are seen as lacking novelty and, therefore, difficult to fund and publish, further lowering the incentive for researchers to embark on replication or reproducibility studies, but this is starting to change.