Do we have the tools and resources to develop FAIR large-scale brain circuit models?
As models in neuroscience have become increasingly complex, it has become more difficult to share all aspects of models and model analysis, hindering model accessibility and reproducibility. In this session, we will discuss existing resources for promoting FAIR data and models in computational neuroscience, their impact on the field, and the remaining barriers. This lecture covers how to make modeling workflows FAIR by working through a practical example, dissecting the steps within the workflow, and detailing the tools and resources used at each step.
- Modeling workflow example: Large-scale model of motor cortex
- FAIR tools/resources for each step of the workflow
- Gather and preprocess data
- Implement model
- Tune and validate model
- Experiments and predictions
- Share and disseminate