Neuromatch Academy aims to introduce traditional and emerging tools of computational neuroscience to trainees. It is appropriate for student population ranging from undergraduates to faculty in academic settings and also includes industry professionals. In addition to teaching the technical details of computational methods, Neuromatch Academy also provide a curriculum centered on modern neuroscience concepts taught by leading professors along with explicit instruction on how and why to apply models.
This course introduces the "hidden states" that neurons and networks have that affect their function and how to use graphical models with hidden states to learn about the dynamics in the world that only has access to from noisy measurements. In addition, the course introduces multiple topics on dynamical neural modeling and inference and their application to basic neuroscience and neurotechnology design:
- How to develop multiscale dynamical models and filters?
- How to study neural dynamics across spatiotemporal scales?
- How to dissociate and model behaviorally relevant neural dynamics?
- How to model neural dynamics in response to electrical stimulation input?
- How to apply these techniques in developing brain-machine interfaces (BMIs) to restore lost motor or emotional function?