Mathematics for Neuroscientists

Mathematics for Neuroscientists, Second Editionintroduces and develops the topic through a sequence of concrete computational models that guide the reader from elementary to advanced stages. It is intended as a tutorial, for self- learning, a text, for course adoption, and as a reference for undergraduate and graduate students in the neurosciences and related disciplines. As neuroscience research is multidisciplinary in nature, this often recommended tutorial is a valuable tool for neuroscience researchers and colleagues across disciplines. The new edition includes coverage of models of motion detection that link motion-energy models to the Reichardt correlation model, a new chapter on Extracellular Potentials that focuses on the current interest in electrocorticography and electroencephalography, and a new chapter on Energy, Metabolism, and Neuro-Vascular coupling. The new edition also retains the MATLAB simulations that have been updated from the latest release of MATLAB. Presents an integrated introduction to mathematics, computation and neuroscienceCovers the mathematical and computational aspects of linear algebra, Ordinary and Partial Differential Equations, Fourier Series and Transforms, Probabilities, and Stochastic ProcessesIntroduces the numerical methods used to implement algorithms related to each mathematical conceptIllustrates numerical methods by applying them to specific topics in the neurosciences Provides implementation examples in MATLAB code