---
product_id: 3505896
title: "Theoretical Neuroscience: Computational And Mathematical Modeling of Neural Systems (Computational Neuroscience) 1st Edition"
brand: "peter dayanlaurence f abbott"
price: "630 Lei"
currency: RON
in_stock: true
reviews_count: 8
url: https://www.desertcart.ro/products/3505896-theoretical-neuroscience-computational-and-mathematical-modeling-of-neural-systems-computational
store_origin: RO
region: Romania
---

# Theoretical Neuroscience: Computational And Mathematical Modeling of Neural Systems (Computational Neuroscience) 1st Edition

**Brand:** peter dayanlaurence f abbott
**Price:** 630 Lei
**Availability:** ✅ In Stock

## Quick Answers

- **What is this?** Theoretical Neuroscience: Computational And Mathematical Modeling of Neural Systems (Computational Neuroscience) 1st Edition by peter dayanlaurence f abbott
- **How much does it cost?** 630 Lei with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [www.desertcart.ro](https://www.desertcart.ro/products/3505896-theoretical-neuroscience-computational-and-mathematical-modeling-of-neural-systems-computational)

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## Customer Reviews

### ⭐⭐⭐⭐⭐ Majestic overview of the fundamentals; helped me fall in love with the subject
*by S***H on June 11, 2015*

This book was an eye opener for me. Scientists still fully don't understand how neurons "think" and "learn" but I was shocked to learn how much we _do know_. After reading significant chunks for this book I feel inspired and want to recommend this book to others who have an interest in this subject. This book is a great overview of the field of Computational Neuroscience. The authors convincingly explain the most fundamental theoretical concepts in Computation Neuroscience and back them up by describing some of the major experiments in this field. It does not oversimplify nor does it over-complicate, for a first introduction.Coming to the specific merits of the book, what stands out is the quality of the prose and explanations. The book is tightly written, so, it gets to the point fast and explains what it needs to without much ado. Because this book is quite succinct (and does not "over explain") you might need do multiple readings of the chapters to understand the content. Actually, it was only on the repeated readings that I came to appreciate the overall coherence of this book.In this book you will find that complex math and derivations are often either relegated to the chapter appendix or left to the reader to cover independently. This approach actually makes the book less daunting because you don't need to wade through dozens of pages of topics that are not really computational neuroscience but Math!Lest someone get the impression that the book is too mathematical I want to point out that you need to have a standard science/engineering background in Calculus and differential equations and basic knowledge of Physics/Chemistry and you should be fine. I personally only had a few problems in the area of dynamical systems which make their appearance in a few places in the book.On the negative side (though this book definitely deserves its 5 stars), I feel the book lacks a little sparkle and personality and can be a bit dry in places. Luckily there are a lot interesting MOOCs and videos on the Internet on Neuroscience that will provide the necessary background "excitement" and context you need while reading this book.Another (subjective) thing: I love calculus but I think its slightly overdone here. If you're _really_ doing computational neuroscience, you're probably going to use a lot of summation, simulation, discrete math, data analysis and algorithms but this book loves showing things in terms of Calculus. Yeah, its prettier with integrals but you're going to have to translate that into algorithms eventually. So, ironically, this book on Computational Neuroscience needs to be a bit more "computational."Finally, if you have some prior knowledge of Machine Learning you are likely to enjoy this book more. This was an unexpected bonus as I didn't realize that was so much overlap between Machine Learning and (real) Neural Systems before diving into the subject.

### ⭐⭐⭐⭐⭐ Great book from what my daughter says.
*by S***K on January 5, 2021*

Christmas gift for my daughter.Her favorite gift.She was a neuroscience major.

### ⭐⭐⭐⭐⭐ Great Textbook
*by B***S on June 20, 2013*

I bought this book while taking a course on Coursera. The professors there followed the book pretty closely, so it was a must. My understanding is that this is a classical textbook on computational neuroscience, beyond that as someone who just got his toes wet, I cannot offer much of an opinion.

## Frequently Bought Together

- Theoretical Neuroscience: Computational And Mathematical Modeling of Neural Systems (Computational Neuroscience)
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- Principles of Neural Information Theory: Computational Neuroscience and Metabolic Efficiency (Tutorial Introductions)

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*Product available on Desertcart Romania*
*Store origin: RO*
*Last updated: 2026-02-01*