Time Series Analysis for Neuroscience Data Using State Space Models

1 credits · Graduate

This course will present the basics of state space modeling to analyze time series data that are frequently encountered in neuroscience problems. The course lectures will cover linear state space models, Markov chains, switching state space models, and algorithms for learning and inference. Students and instructors will work through practical data analysis exercises in Python in weekly labs and recitation sections.