Entropy in Neuroscience and Ecology

This lecture explores the concept of entropy in neuroscience data, focusing on how sequences of spikes represent sensory information in the fly's visual system. It delves into the maximum possible entropy of sequences of binary digits and the entropy of words in a movie. The lecture also discusses the impact of word duration and time resolution on information in neuroscience data. Furthermore, it examines entropy in ecology and evolution, showcasing the diversity of yeast and bacterial populations over time and the effective number of lineages. The course outline includes topics like quantifying randomness, identifying coevolving sites in proteins, and inferring probability distributions from data.