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Our @NatureNeuro paper is out, first-authored by my student @omidsani. It develops PSID, a novel dynamic method to dissociate & model behaviorally relevant neural dynamics. Thanks to @salixabb, Y Wong & collaborator @pesaranlab. Summary & code below: 1/n
nature.com/articles/s4159…
nature.com/articles/s4159…
Neural dynamics recorded in an experiment relate to various behaviors and internal states simultaneously. How do we dissociate neural dynamics of a specific behavior (green) and ensure they are not masked/missed in modeling due to other dynamics (red)? PSID solves this. 2/n 
Unlike standard neural dynamic models (NDM), PSID uses neural activity & behavior jointly in training set to prioritize learning of behavior-relevant neural dynamics. Model is efficiently learned via projections. States are extracted via a real-time Kalman filter in test set. 3/n
