From Computer to Brain: Foundations of Computational Neuroscience

by William W. Lytton

Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.

Genres: Textbooks, Neuroscience

384 pages, Paperback

First published January 1, 2002

Reviews

[Per-Yngve Ingensson · Rating 4 out of 5]

Overall this book was both surprisingly easy to read and immensely informative, not to mention humorous. The author comes across as someone you'd want to meet.

However, there breakdowns, especially towards the end, for instance in describing analog electric models of neurons. I'll admit that the author needs to make trade-offs in the level of exposition, and that I like and have an easier time with discrete/digital modeling than analog things, but omitting calculus from the description probably only muddied the waters. The author uses an unfamiliar numerical approximation of the differential equations involved and then doesn't explain them enough, in my opinion. So I ended up skipping that section, and then the Hodgkin-Huxley model too, because I assume it builds on the same material. I ended up heading to the final two chapters and even then the way he described neural circuits seemed sort of hazy and rushed. The same could have been said of some of the other passages: for instance, some of the explanations about the factors involved in limulus modeling were perplexing.

But don't get the impression that I'm just finding fault. I'm writing the review like this because saying all the good things about this book would take longer than saying all the bad things about it. A lot of the exposition is both clear and enthralling. It is shown that without compensation, lateral inhibition in the retina might lead to a bright halo around the whole field of vision; that the digestive tract will function in lieu of a brain, as if we have a simple worm living inside all of us; that a number of the brain's messaging systems are derived from our own cellular shit: "Are you thinking about your food, or is your food thinking about you?" On top of that I finally have a (somewhat) better understanding of the Hopfield neural network model and how it may have a kernel of biological plausibility. It just seems like the author, though brilliant, was pressured by a deadline. If a second edition comes out I'll look forward to it.

Last word: I really do like the Computer Modern Roman typeface used in this book. It's an acquired taste; not anywhere near as refined as, say, Palatino; and is usually associated with much more painful reading but I have fond memories of it nonetheless.

[Ryan · Rating 5 out of 5]

Super great intro to computational neuroscience, though aimed at undergrads so there is little depth!

[Will Wei · Rating 3 out of 5]

A total but simple and interesting guide to readers who want to entry this area.