This tutorial will start with an introduction to the new statistical mechanical theory of neural manifolds, and the example scenarios where the theory is particularly relevant and useful. The second part of the tutorial will focus on the theory-inspired analysis method for characterizing geometric properties of neural manifolds, and predicting the neural manifold classification capacity, and how to incorporate this geometric analysis tool into the data. There will be hands-on exercises, so please bring a laptop. The analysis code (in Matlab) and example data will be provided; if you have your own data you want to analyze, even better and please bring it.

Suggested Reading: https://journals.aps.org/prx/abstract/10.1103/PhysRevX.8.031003