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Fundamentals of Computational Neuroscience Paperback – June 20, 2002

ISBN-13: 978-0198515838 ISBN-10: 0198515839

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Product Details

  • Paperback: 360 pages
  • Publisher: Oxford University Press (June 20, 2002)
  • Language: English
  • ISBN-10: 0198515839
  • ISBN-13: 978-0198515838
  • Product Dimensions: 9.4 x 0.7 x 6.7 inches
  • Shipping Weight: 1.4 pounds
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #4,095,462 in Books (See Top 100 in Books)

Editorial Reviews


"The book is small enough to be manageable in a semester-long course, but it is large enough to contain a wonderful amount of material. ... [A] very useful book for its clarity of presentation ... and ... success in teaching modeling."--The Quarterly Review of Biology

About the Author

Thomas Trappenberg is in the Department of Psychology, University of Oxford and Department of Computing Science, Dalhousie University, Canada.

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Most Helpful Customer Reviews

2 of 2 people found the following review helpful By Vishnu Sreekumar on August 2, 2013
Format: Paperback Verified Purchase
The headline of this review is how my committee member described this book when assigning it to me as part of my candidacy readings. I'm pursuing a PhD in Cognitive Psychology. As of today, I've read 4 chapters (all about neurons, spiking neurons, rate and population nodes, important issues like the effect of noise in the channels, synaptic plasticity, etc). I've thoroughly enjoyed all of it. I must say however that this isn't a book for beginning Cog Sci students. You also need to be comfortable with basic calculus before you can read the book uninterrupted by confusions about math. The book does a very good job of giving you enough information to give you a sense of satisfaction but also doesn't give you everything (because it is impossible to do so in such a small volume). So I now understand why the professor called it "the best concise overview of computational neuroscience". For those of you who have access to MATLAB, there are very useful codes provided that you can run to see how the different models behave under different conditions. Each chapter contains little sections about simulations where the author also provides basic MATLAB guidance which can be great for beginners. All in all, a 5 star book that every student of computational neuroscience must read. I look forward to reading the rest of it!
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3 of 5 people found the following review helpful By zfhindbrain on November 23, 2012
Format: Paperback Verified Purchase
To be fair, I think it impossible to write a CompuNeuro text that is EASY to read, since it requires advanced math AND neuroscience. As a professional neurobiologist needing to understand computational approaches for my research, I struggled mightily with such texts as "Spikes" and "Theoretical Neuroscience". Some older books on the subject helped including The Computational Brain (plus one by Hertz, which had crucial details), but none address the current range of important topics that I need to digest. Discovering Trappenberg's text was like finding gold -- I needed an approachable treatment to bootstrap my learning AND to convey these ideas to students in my new Computational Neuroscience course (if you want to learn something, teach a class in it). One reviewer found it difficult to read, but the problem is not (to my mind) the writing but the subject matter. Certainly, there are things that could be explained better, but this is the "best of the mess" methinks.

So, WHY did I give this 5 stars? The organization and content are superb. It has exactly what I needed to bring undergraduates into the computational neuro arena, with enough math to help the biologists (including the appendices) and good problems to interest the engineers/physicists/programmers. It starts with the Hodgkin-Huxley models and builds to current frontiers in this chaotic, dynamic field including integrate and fire networks, self-organizing maps, memory systems, attractors, sparse coding and more. I don't think there are very many who can fully comprehend all the neurobiology and math inherent in these topics (my physicist helpers who do cutting edge Perceptron research could not understand the notation used here and this is not Trappenberg's fault but rather a sign of the field-- this is rough stuff).
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6 of 12 people found the following review helpful By drydeniv on February 20, 2012
Format: Paperback
I rarely write reviews for textbooks, but this gem is a great exception.

The content is not bad, and I assume it is par for the course, but as I recently switched fields I can't make concrete recommendations on alternative sources.

The diction used by this author is truly horrible, that is to say painful to read or comprehend. I guess I would be marginally more forgiving if I knew he was a non-native English speaker, but as it is being sold as an authoritative textbook, I can't. I often read textbooks for fun, but with this particular one - I find myself reading the same sentence or paragraph several times just to realize that I got absolutely nothing out of it. Perhaps I am being too critical, my classmates don't seem to have the same severe issue I have with this book.

I do appreciate that the author has provided a website with the MATLAB scripts and various other information (animations, figure images, et c.) free of charge.

My professor says that the first edition is worse, so I will heed his warning an not attempt to read any single word of the first edition.
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