Information Theory Tools for Neuroscience Applications - Class 1 of 3

Explore the first class of a three-part series on information theory tools for neuroscience applications, delivered by Osvaldo A. Rosso at the School on Nonlinear Dynamics, Complex Networks, Information Theory and Machine Learning in Neuroscience. Delve into topics such as dynamical systems, time series, chaotic and stochastic dynamics, chaos and information, information theory quantifiers, complexity measures, and the concept of disequilibrium. Learn about the selection of information measures, distances between probability distribution functions, and the application of these concepts to the logistic map. Gain insights into the Bandt & Pompe probability distribution function and its relevance in neuroscience research.