Reproducibility is key for scientific progress. If research results cannot be reproduced and trusted, other researchers cannot build on them.
Reproducibility is a challenge also in computational neuroscience, and today's guest has worked on how this can be remedied, for example, through standardized model description and model sharing.
He also recently organised a workshop celebrating a decade with the (reproducible) Potjans-Diesmann neural network model, which has become an important community tool.