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Neural Control Engineering: The Emerging Intersection between Control Theory and Neuroscience (Computational Neuroscience) Hardcover – January 1, 2012

ISBN-13: 978-0262015370 ISBN-10: 0262015374 Edition: 1st

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Editorial Reviews

Review

For many years, Steve Schiff's pioneering work has led the way toward a deeper understanding of the brain as a dynamical system. In this beautifully written and groundbreaking book, he presents a new synthesis of neuroscience, computation, and engineering. Neural Control Engineering will be a welcome resource for all working in this emerging field, and it will guide and inspire the next generation of students.

(Olaf Sporns, Provost Professor, Department of Psychological and Brain Sciences, Indiana University, author of Networks of the Brain)

About the Author

Steven J. Schiff, a neurosurgeon, is Brush Chair Professor of Engineering and Director of the Center for Neural Engineering at Pennsylvania State University.
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Product Details

  • Series: Computational Neuroscience
  • Hardcover: 384 pages
  • Publisher: The MIT Press; 1 edition (January 1, 2012)
  • Language: English
  • ISBN-10: 0262015374
  • ISBN-13: 978-0262015370
  • Product Dimensions: 7 x 0.6 x 9 inches
  • Shipping Weight: 1.8 pounds (View shipping rates and policies)
  • Average Customer Review: 4.6 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Best Sellers Rank: #365,393 in Books (See Top 100 in Books)

More About the Author

I am a pediatric neurosurgeon, and I direct efforts at fusing medicine with engineering at the Penn State Center for Neural Engineering. I have always been fascinated with how we might better understand the brain through the physics of the brain. My hopes are that such knowledge will better enable us to engineer treatments for controlling conditions such as epilepsy, migraines or Parkinson's disease more effectively. I had no shortage of motivation to write the book Neural Control Engineering.

I set up a website where I have archived errata that corrects mistakes that my students and I have found in the text. I also archived working computer code that lay behind many of the calculations in the book for those who wish to replicate or extend these results. Lastly, this book grew out of my teaching this material, and I have made available my lecture slides for those who may wish to teach these subjects. The website is also a good place to find some of the links to the original research papers that lay behind many of the chapters in the book.

http://www.esm.psu.edu/schiff

I do hope that you enjoy the book.

Customer Reviews

4.6 out of 5 stars
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This is a very nice interdisciplinary book.
Luigi Fatori
Apart from these, this book is a gold mine for anyone interested in how to model brain activity, and how to control it.
Jack Cowan
It is about how they function -- or will function in the future to make an impact on modern medicine.
Markus A. Dahlem

Most Helpful Customer Reviews

8 of 10 people found the following review helpful By Jack Cowan on May 8, 2013
Format: Hardcover
Niels Bohr has been quoted as saying "the hardest thing to do in science is to predict, especially the future!" This book is concerned, in large part, with this problem, in its application to controlling the dynamics of the brain. The problem involves collecting observations of brain activity, filtering out the effects of noise and measurement errors, and controlling brain dynamics. In many ways this set of problems originated in Gauss's least squares method of minimizing the effects of measurement errors, which is over 200 years old. But it was during the period between World Wars 1 and 2, that the current methods for dealing with noisy data in the exercise of predictive control were really started by Norbert Wiener, and by Andrey Kolmogorov in 1941. Wiener's theory considered data in the form of continuously changing data represented by stationary random processes with Gaussian statistics, and Kolmogorov studied very similar processes generated by data sampled at discrete times. Essentially Wiener and Kolmogorov developed filters to remove the effects of noise and measurement errors from the data, so the theory is often called the Wiener-Kolmogorov filtering theory.

The problem with both theories was that they dealt only with linear, stationary and Gaussian processes. It took another 20 years before Rudy Kálmán (1960) introduced a filter theory to deal with noisy dynamical systems, and another 40 years or so before the Kalman filter techniques were used to estimate the parameters of dynamics generated by various equations describing neural activity. Schiff's book is the first comprehensive account of this development. Schiff is perhaps uniquely qualified to write this account.
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3 of 4 people found the following review helpful By Thomas Schreiber on August 7, 2012
Format: Hardcover
In terms of what this book is about, I have not much to say beyond what a previous reviewer said. What I want to emphasize is the extraordinary fact that all these chapters are offered by the same author. He has obviously spent many years of his life to learn and practise enough engineering, mathematics, statistics, physics, philosophy - beyond his primary profession as a neurosurgeon trained in physiology - to meaningfully bring together what is needed to advance his field beyond this point.

Why should you read this book - beyond admiring the last polymath?

Case 1: You plan to attend Prof. Schiff's Course - well then it's obvious

Case 2: You plan to teach a course in a related field - then you can take this text as a blueprint for your preparation

Case 3: You plan to do work in neural control engineering - then you will find your learning agenda set in this book. You will probably master one or two of the branches covered, but you need to develop some intuition on the others as well

Case 4: You are just curious what is going on in this area - that's how I came to read it. Then you will understand what it is like to go beyond trial-and-error in a field where full understanding of the inner workings of the system is way out of reach.

The book is a very entertaining demonstration that intuition is of utmost importance in interdisciplinary work - and that intuition comes as the result of hard work.

What I personally enjoyed is that where other authors offer bold statements and hyperbole, Steven Schiff shows courage and hope. That is a major difference.

Hope and courage is needed in particular for the last chapter "Assimilating Minds".
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1 of 1 people found the following review helpful By Luigi Fatori on December 28, 2013
Format: Hardcover Verified Purchase
This is a very nice interdisciplinary book. It deals with neuronal models and a number of issues related to filtering and model uncertainty. This book will prove helpful for those who need to grasp knowledge about neurons, models and data from both. There is much information on historical development of the field which is an extra benefit. The author succeeds in making a strong point for Kalman filtering (in one of its nonlinear versions, the UKF) as a tool for handling, model, data and uncertainty. The book, which is very well written, reads more like a research monograph than a textbook and the bias is clearly towards neural issues albeit the author's efforts to relate the material to control engineering. Given the "plant" considered by the author, it is fair to say that his efforts have been quite successful.
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1 of 2 people found the following review helpful By Markus A. Dahlem on July 12, 2012
Format: Hardcover
You should simple read the first page of the book and not this review. It's a page turner ... But here you go.

There is "control" between "neural" and "engineering". The field of neural control engineering partly involves the development of devices but mostly the techniques that actually alter brain activity and treat nervous system disorders in a well defined way. Various human brain stimulation devices use electrical and magnetic stimulation.

Let me briefly give two clinical conditions as examples and name several of such devices to explain what the book is about, how broad is its scope. Be warned, the book is not about these devices. It is about how they function -- or will function in the future to make an impact on modern medicine.

First, treating headaches -- which may not generally be considered appropriate for invasive neurosurgical therapy that implants electrodes to alter brain activity, but I happen to know a bit about it -- various methods are approved: occipital nerve stimulation (ONS), vagus nerve stimulation (VNS), cervical spinal cord stimulation (cSCS), and even hypothalamic deep brain stimulation (DBS). Furthermore, there are non-invasive methods, such as transcutaneous electrical nerve stimulation (TENS), transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS).

Consider the various methods mentioned above. Seven only for headaches. Question is: Which device uses what kind of stimulation protocol? Given the hardware works well with the wetware, what is the software? This, the stimulation sequence, can be determined empirically or quantitatively with model-based methods.

Second example.
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