Helping Humans: Neuroprosthetics

This lecture focuses on the application of computational neuroscience in neuroprosthetics, specifically in predicting intended arm movements based on spike times. It covers the use of mathematical models to decode and encode neural activity, emphasizing the importance of systematic parameter optimization. The lecture also delves into the estimation of receptive fields and the Generalized Linear Model for predicting retinal ganglion cell activity. Additionally, it explores the concept of GLM with lateral coupling and the basic principles of neuroprosthetics, showcasing how mathematical models can assist in enhancing human capabilities.