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Spikes, Decisions, and Actions: The Dynamical Foundations of Neuroscience
 
 
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Spikes, Decisions, and Actions: The Dynamical Foundations of Neuroscience [Paperback]

Hugh R. Wilson (Author)
5.0 out of 5 stars  See all reviews (4 customer reviews)


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Book Description

0198524307 978-0198524304 August 5, 1999 Pap/Dis/CD
The nervous system of higher animals is both very complex and very nonlinear. Nervous systems are constantly making decisions between alternative actions, and switching gears among dynamical modes. This book is an exploration of the mathematical principles by which brains generate neural spikes, make decisions, store memories, and control actions. Assuming only a basic knowledge of mathematics, and including problem sets and simulations on disk, Spikes, Decisions, and Actions is an ideal text for courses in neuronal modelling in particular, and mathematical modelling in biology generally.


Editorial Reviews

Review

The book is a valuable source of information at the level accessible to well-trained undergraduate students and can be successfully used by specialists interested in mathematical modelling in neuroscience. Zentralblatt MATH

About the Author

Hugh Wilson is at Visual Sciences Center, University of Chicago.

Product Details

  • Paperback: 320 pages
  • Publisher: Oxford University Press, USA; Pap/Dis/CD edition (August 5, 1999)
  • Language: English
  • ISBN-10: 0198524307
  • ISBN-13: 978-0198524304
  • Product Dimensions: 9.6 x 4.4 x 1.1 inches
  • Shipping Weight: 1.2 pounds
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Best Sellers Rank: #2,091,358 in Books (See Top 100 in Books)

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16 of 19 people found the following review helpful:
5.0 out of 5 stars Excellent overview of the theory, November 1, 2000
By 
Yuri Kuzyk (Toronto, Ontario Canada) - See all my reviews
This review is from: Spikes, Decisions, and Actions: The Dynamical Foundations of Neuroscience (Paperback)
For anyone with a good background in math, particularly from an engineering background, this book presents a broad overview of the neurosciences in a very understandable format. In fact, the math overview is probably better than that found in many calculus textbooks and the Matlab disk would certainly save a lot of time for many common problems. Again, any readers with an engineering background (particularly mechanical or electrical) will find the math and results to be rather familiar.

I suspect someone looking for another "popular science" book like Gleick's "Chaos" will be highly disappointed. This book is definitely structured for someone interested in pursuing study in the field.

I hope that Wilson now moves on to expanding on the hints of philosophical thought he has listed here. Anyone familiar with nonlinear chaotic systems MUST have some understanding of the implications of their non-deterministic nature; certainly a quick reading of Jantsch or Prigogine would help too. As Wilson points out on page 184, chaos and free will may easily be tied to each other.

Further study of Perlovsky's work (hopefully his book will be out soon too) will clarify many of the issues regarding neural net modeling and its philosophical implications. Certainly one can only wonder at Churchland's child-like beliefs that neural nets will resolve "folk psychology" and the fundamental questions of consciousness when confronted with nonlinear chaotic systems on the order of 10 the 10th order!

Highly recommended.

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2 of 2 people found the following review helpful:
5.0 out of 5 stars A great introduction and teaser to the world of neuroscience, January 29, 2009
By 
J. Ball (Columbia, Mo USA) - See all my reviews
(REAL NAME)   
This review is from: Spikes, Decisions, and Actions: The Dynamical Foundations of Neuroscience (Paperback)
I got this book in late 2006 as my very first introduction to the world of neuroscience. I am an electrical engineering PhD student, and coming from that background at the time, this book was very easy to pick up and read. The author seldom gets lost in the more complicated details, and when you have read a section and run the accompanying matlab scripts, you really get a sense that you've just peeked into a fundamental property of a neural system.

I'd recommend this for any engineering student that wants to study neural systems. The biology is not daunting, but once you get a taste, I feel you are more prepared to venture into the biology that the systems in this book are based upon.
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11 of 19 people found the following review helpful:
5.0 out of 5 stars Foundation, December 5, 1999
This review is from: Spikes, Decisions, and Actions: The Dynamical Foundations of Neuroscience (Paperback)
This book is beyond a doubt the foundation to a new approach. While too many of todays science books say me too, or action figure sold seperately this book is the action figure. Including Matlab linked library. As a student of chaos theory with a strong backround in the biological sciences imagine the warm and fuzzy feeling of seeing things involving chaos theory I had suspected in cognitive neuroscience but, not having the access to prove. Although the stronger the math backround the richer the text, Wilson's command of his subject guides the reader through 2 years of differential equations and feedback and control theory in 3 of the best written chapters I have come accross in major texts. Then just to make sure everyone is reading from the same sheet of music, he heads to, what is for me at least, the Grand Unification Theory. The difficulty is presenting this type of material in cohesive body should make this the basic text for future research in biomeimetic materials,nonlinear neurodynamics, biopharmaceuticals, and neural nets. As an example on page 126 Wilson has already anticipated my question of toroidial limit cycles saving long hours of computer simulations proving and disproving compatiblilies. Virtually all of the material is translatable to other computer math systems (Mathcad) since the book includes the formulas.
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Inside This Book (learn more)
First Sentence:
The nervous system of all higher animals is inherently both highly complex and highly nonlinear. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
phase oscillator model, neural bursting, asymptotically stable spiral point, retinal light adaptation, isocline equations, divisive gain control, swimming network, neural chaos, mutually inhibitory neurons, human neocortical neurons, asymptotically stable limit cycle, lamprey swimming, segmental oscillator, unstable spiral point, coupled phase oscillators, asymptotically stable steady state, parabolic bursting, asymptotically stable node, parent dendrite, recurrent excitation, cable equation, lamprey spinal cord, postinhibitory rebound, spike rate, first return map
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Van Vreeswijk, Hodgkin Huxley
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