Self-Supervised Foundation Model for Calcium-imaging Population Dynamics

1. 1Train a self-supervised neural foundation model on neuronal calcium traces
2. 2Use the trained model for multiple downstream tasks such as forecasting and analysis
3. 3Fine-tune the model for specific tasks to improve performance
4. 4Evaluate the model's performance on various neuroscience objectives

Neuroscientists and AI researchers on a team can benefit from this model as it improves neural recording analysis and can be adapted to multiple downstream tasks, making it a valuable tool for understanding brain function

💡 A self-supervised neural foundation model can be trained on neuronal calcium traces and adapted to multiple downstream tasks in neuroscience

💡 Introducing CalM, a self-supervised neural foundation model for calcium-imaging population dynamics!