Hanspeter A. Mallot – författare

This book provides an essential introduction to modeling the nervous system at various levels. Readers will learn about the intricate mechanisms of neural activity, receptive fields, neural networks, and information coding.

The chapters cover topics such as membrane potentials, the Hodgkin-Huxley theory, receptive fields and their specificity for important stimulus dimensions, Fourier analysis for neuroscientists, pattern recognition and self-organization in neural networks, and the structure of neural representations. The second edition includes revised text and figures for improved readability and completeness. Key points are highlighted throughout to help readers keep track of central ideas.

Researchers in the field of neuroscience with backgrounds in biology, psychology, or medicine will find this book particularly beneficial. It is also an invaluable reference for all neuroscientists who use computational methods in their daily work. Whether you are a theoretical scientist approaching the field or an experienced practitioner seeking to deepen your understanding, "Computational Neuroscience - An Essential Guide to Membrane Potentials, Receptive Fields, and Neural Networks" offers a comprehensive guide to mastering the fundamentals of this dynamic discipline. 

Computational Neuroscience - A First Course provides an essential introduction to computational neuroscience and  equips readers with a fundamental understanding of modeling the nervous system at the membrane, cellular, and network level. The book, which grew out of a lecture series held regularly for more than ten years to graduate students in neuroscience with backgrounds in biology, psychology and medicine, takes its readers on a journey through three fundamental domains of computational neuroscience: membrane biophysics, systems theory and artificial neural networks. The required mathematical concepts are kept as intuitive and simple as possible throughout the book, making it fully accessible to readers who are less familiar with mathematics. Overall, Computational Neuroscience - A First Course represents an essential reference guide for all neuroscientists who use computational methods in their daily work, as well as for any theoretical scientist approaching the field of computational neuroscience.