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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 neuroscience
- Covers the mathematical and computational aspects of linear algebra, Ordinary and Partial Differential Equations, Fourier Series and Transforms, Probabilities, and Stochastic Processes
- Introduces the numerical methods used to implement algorithms related to each mathematical concept
- Illustrates numerical methods by applying them to specific topics in the neurosciences
- Provides implementation examples in MATLAB code
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