Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition

This is a math heavy book, but as long as you know that going in this is a great review (or first time learning) resource for a lot of the concepts in computational neuroscience. Although it is a little pricey it is well worth the cost for the value this book provides.

The full text is freely available on-line at http://neuronaldynamics.epfl.ch/book.htmlThe same site also has video lectures by Gerstner and PowerPoint slides.

So far this book reads in a structural format. Though I must admit that shortcuts taken during explanation really complicate things. Let's take some time to address how formulas are meant to be used. In mathematics, calculus, even apple counting formulas simplify the work taken during figuring up certain values. These things are thus shortcuts to establishing something needed at that time. This book's author must think that concepts or even arguments are better expressed as apples in a bucket. I however would rather read something more vivid, established, even thorough. So if you like books that appear to be stabbed by the formula knives then this book would work. Else, I would not recommend this work.

Good book. Fast delivery.

Clair, complet, et en pleine actualité scientifique : un ouvrage essentiel.

Really well explained and covers a lot of ground, this book feels like it is a must have.

The book accompanies the MOOC Neural Dynamics, which is an excellent course in itself.Even though the book is available online for free on the neuronal dynamics website, I decided to buy it anyway and I didn't regret the purchase. It is not an undergraduate text, as advertised.As far as prerequisites go, you may need to brush up on your differential equations and your signal and systems theory. The accompanying Python code and additional pen and paper exercises make this book suitable for self-study.

This textbook by Wulfram Gerstner and others is a wonderful introduction to neuroscience. The book is divided into four parts: foundations of neuronal dynamics, generalized integrate-and-fire models, networks of neurons and population activity and dynamics of cognition. There are 20 chapters in all. The text is very lucid. There are many diagrams. Examples and advanced mathematics are explained in lightly shaded boxes. Each chapter ends with a summary and exercises.

Es un libro de referencia para aquellos interesados en la neurociencia y en el modelado neuronal. Es muy fácil de seguir y, además, los autores ofrecen videos (accesibles libremente) con explicaciones de conceptos del libro.