Read Spiking Neuron Models: Single Neurons, Populations, Plasticity by Wulfram Gerstner, Werner M. Kistler Online
# Read * Spiking Neuron Models: Single Neurons, Populations, Plasticity by Wulfram Gerstner, Werner M. Kistler ó eBook or Kindle ePUB. Spiking Neuron Models: Single Neurons, Populations, Plasticity "All you ever wanted to know about spiking neuron models" according to Orlando Furioso. 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, pro
| Title | : | Spiking Neuron Models: Single Neurons, Populations, Plasticity |
| Author | : | |
| Rating | : | 4.61 (511 Votes) |
| Asin | : | 0521890799 |
| Format Type | : | paperback |
| Number of Pages | : | 496 Pages |
| Publish Date | : | 2013-04-24 |
| Language | : | English |
It focuses on phenomenological approaches rather than detailed models in order to provide the reader with a conceptual framework. No prior knowledge beyond undergraduate mathematics is required.. This introduction to spiking neurons can be used in advanced-level courses in computational neuroscience, theoretical biology, neural modeling, biophysics, or neural networks. The authors formulate the theoretical concepts clearly without many mathematical details. While the book contains standard material for courses in computational neuroscience, neural modeling, or neural networks, it also provides an entry to current research
"All you ever wanted to know about spiking neuron models" according to Orlando Furioso. 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 . "Impressive book" according to Harel Z. Shouval. 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 systemat
He studied physics in Tubingen and Munich and holds a PhD from the Technical University of Munich. Wulfram Gerstner is Director of the Laboratory of Computational Neuroscience and a Professor of Life Sciences and Computer Science at the Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland. He teaches computational neuroscience to physicists, computer scientists, mathematicians, and life scientists. His research in computational ne
'The treatment undoubtedly holds pointers to future developments that will allow robots to come closer to their biological prototypes.' Journal of Robotica
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