Spiking Neuron Models

Rating:
Summary: Impressive book
Review: This is a very impressive book. It covers in a systematic manner a broad portion of the field of theoretical neuroscience. It covers topics from models of single spiking neurons, through networks of interconnected neurons and up to neuronal plasticity. This book is also written very well. The style of this book reflects the background of the authors as Physicists; it therefore strives for simplicity wherever possible.
I used chapters from this book as a basis for some of my lectures in a course I teach: Introduction to Theoretical/Computational Neuroscience, a graduate level course. I especially liked the systematic approach they have adopted for describing various simplifications of the Hodgkin-Huxley equations.


Rating:
Summary: All you ever wanted to know about spiking neuron models
Review: I have used this book as an introduction and reference book for modeling neurons since I started my thesis work in computational neuroscience two years ago. It covers various types of spiking neuron models (e.g. Hodgkin-Huxley, Morris-Lecar, Integrate&Fire, Spike-Response-Model), noise in neuron models, population models, and plasticity/learning.
It is a very useful book, clearly written and comprehensive, providing sufficient detail and background information. Derivations of the equations are clearly presented and understandable to anyone with a decent knowledge of mathematics. A degree in physics is not required in order to read this book ;-) With this book and some programming skills, one has a solid foundation for modeling neurons on various levels.
I also like the literature recommendations at the end of each chapter, they give a good overview over important original papers and further reviews.
I would strongly recommend this book to undergraduate and PhD-students in computational neuroscience, as well as to anyone interested in modeling neurons.