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Neuronal Dynamics: From Single Neurons To Networks And Models Of Cognition
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Book Description
Exploring neuron models, the neural code, decision making and learning, this textbook provides a thorough and up-to-date introduction to computational neuroscience for advanced undergraduate and beginning graduate students. With step-by-step explanations, end-of-chapter summaries and classroom-tested exercises, it is ideal for courses or for self-study.
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About the Author
Wulfram Gerstner is Director of the Laboratory of Computational Neuroscience and a Professor of Life Sciences and Computer Science at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. He studied physics in Tubingen and Munich and holds a PhD from the Technical University of Munich. His research in computational neuroscience concentrates on models of spiking neurons and synaptic plasticity. He teaches computational neuroscience to physicists, computer scientists, mathematicians, and life scientists. He is a co-author of Spiking Neuron Models (Cambridge, 2002).
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Product details
Paperback: 590 pages
Publisher: Cambridge University Press; UK ed. edition (September 22, 2014)
Language: English
ISBN-10: 1107635195
ISBN-13: 978-1107635197
Product Dimensions:
6.8 x 1.3 x 9.7 inches
Shipping Weight: 2.6 pounds (View shipping rates and policies)
Average Customer Review:
3.3 out of 5 stars
2 customer reviews
Amazon Best Sellers Rank:
#612,533 in Books (See Top 100 in Books)
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.
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