Confabulation Theory: The Mechanism of Thought [Hardcover]

Robert Hecht-Nielsen (Author)

Book Description

Publication Date: August 24, 2007

This book offers the first detailed, comprehensible scientific presentation of Confabulation Theory, addressing a pressing scientific question: How does brain information processing, or cognition, work? With only elementary mathematics as a prerequisite, this book will prove accessible to technologists, scientists, and the educated public.

Editorial Reviews

From the Back Cover

Confabulation theory offers the first complete detailed explanation of the mechanism of cognition, i.e., thinking, an essential information processing capability of all enbrained Earth animals (bees, octopi, trout, ravens, humans, et al.). Concentrating on the human case, this book offers an hypothesis for the neuronal implementation of cognition, and explores the mathematics and methods of application of its mechanism. Thinking turns out to be starkly alien in comparison with all known technological approaches to information processing. While probably not yet scientifically testable, confabulation theory seems consistent with the facts of neuroscience. Beyond science, any complete detailed explanation of cognition can be investigated by applying it technologically. Multiple experiments of this nature are described in this book in complete detail. The results suggest that confabulation theory can provide the universal platform for building intelligent machines. In short, this book explains how thinking works and establishes the foundation for building machines that think. With two DVDs of courseware, this book is suitable both as a text for professional self-study and for graduate and advanced undergraduate courses in neuroscience, computational intelligence, cognitive science, linguistics and psychology, the prerequisites being elementary mathematics and neuroscience. Because of the theory’s implications for philosophy, education, medicine, anthropology and social science, this book will also be of interest to scientists in those domains.

About the Author

Robert Hecht-Nielsen was made a Fellow of the IEEE in 1997 for leadership in practical applications of neural network technology. He was a pioneer in the development of neural networks and authored the first textbook on the subject, Neurocomputing (1989). He has been a member of the UCSD faculty since 1986.

Product Details

• Hardcover: 255 pages
• Publisher: Springer; 2007 edition (August 24, 2007)
• Language: English
• ISBN-10: 3540496033
• ISBN-13: 978-3540496038
• Product Dimensions: 9.4 x 6.4 x 0.8 inches
• Shipping Weight: 1.3 pounds (View shipping rates and policies)
• Average Customer Review: 3.8 out of 5 stars  See all reviews (4 customer reviews)
• Amazon Best Sellers Rank: #2,114,634 in Books (See Top 100 in Books)

More About the Author

Discover books, learn about writers, read author blogs, and more.

Customer Reviews

Most Helpful Customer Reviews

9 of 9 people found the following review helpful:

4.0 out of 5 stars Outside the box, November 18, 2007

By 

Jim Lewis (NJ USA) - See all my reviews
(REAL NAME)   

Amazon Verified Purchase

This review is from: Confabulation Theory: The Mechanism of Thought (Hardcover)

I heard about confabulation theory from an AGI video and looked forward to this book. The author presents a unique and relatively simple theory about the basic algorithm of the brain. Although the theory is incomplete, the big benefit of the book is presenting a thought provoking new view - and one based (I am not in a position to assess how accurately) on a substantial body of neuroscience. There is substantial redundancy resulting from use of text from the author's scientific papers - I kept asking myself, "didn't I already read this"? And although I'm in the KISS camp I am doubtful that the core algorithm can be quite as simple as confabulation theory supposes. Yet at the core are some fascinating ideas that present fuel for a much needed new direction in thinking about how to approach AGI, and sufficient concreteness from which to develop code experiments for AGI implementations.

6 of 6 people found the following review helpful:

3.0 out of 5 stars Well-written, but repetitive and overstated, April 26, 2008

By 

G. Snider (Palo Alto, CA USA) - See all my reviews
(REAL NAME)   

This review is from: Confabulation Theory: The Mechanism of Thought (Hardcover)

"Confabulation Theory" is not a textbook but a collection of papers by the author plus two talks on DVDs. The writing is very clear and the talks are excellent, taking you through the theory one step at a time. Hecht-Nielsen is a great teacher. But the papers are repetitive, covering the same basics over and over again, while skimming over the key topics of self-organization within modules and implementation of the winner-take-all networks. The book spends too much time on sentence confabulation experiments (which appear to be similar in approach to statistical language translation) and not enough on the applications sketched out in the last two chapters (vision and continuous speech segmentation).

Hecht-Nielsen has an unfortunate habit of overstatement which weakens his presentation. In the text and the videos he repeatedly points out how "starkly alien" confabulation theory is, and how it might revolutionize "psychology, education, philosophy, psychiatry, medicine (both human and veterinary), law, and theology." Really? If you're unfamiliar with neuroscience, the massive parallelism and nonlinear dynamics might seem alien, but this is old hat in the field. His "Fundamental Theorem of Cognition" goes over the edge, though, seemingly suggesting that he has "solved" the problem of cognition once and for all; the "fundamental theorem of confabulation" would have been a more appropriate and less annoying name.

There are a lot of interesting ideas here, and I finished the book wanting to know more. I hope that someday Hecht-Nielsen writes a book with greater depth in implementation issues and more breadth on applications. The papers making up the core of the theory are available on the Web, so the book is worth buying only for the convenience of having everything bound together.

3.0 out of 5 stars Fundamental Theorem of Cognition?, September 27, 2010

By 

Dr. Roy Simpson (Hertfordshire, UK) - See all my reviews

This review is from: Confabulation Theory: The Mechanism of Thought (Hardcover)

I will admit to being new to reading books in the field of neuroscience and this book attracted me with its title, DVDs (definitely a good means for presenting a new idea) and mathematical content. So I note the points of all the other reviewers who are probably more familiar with the area. I am one of those for whom the claim that this cognition method is "alien" to standard approaches is intriguing.

It seems to me indeed that this book is presenting an important idea with its "central theorem of cognition/confabulation". However I could comment on some aspects of the mathematics. Firstly the Fundamental Theorem itself is presented in a mathematically specific way with four assumed facts and one conclusion. This theorem could be generalised to N assumed facts. In fact understanding the Bayes mathematics is possibly easier with N=2 assumed facts. Also many of the examples involve four assumed letters or words. I can understand why many appropriate test examples might use N=4, but is there some reason why N=4 is presented as the Fundamental theorem?

The "duck example" associated with explaining the Fundamental theorem is very good and sets the scene well. It is certainly plausible that empirical mammalian (quasi-) reasoning and also learning is based around this kind of approach. One remaining question, perhaps, is whether all human analytical reasoning can be said to work this way as well?

The discussion around page 200 suggests that earlier work in Vector Quantization and Self Organizing maps has helped to motivate this research. I presume that some of the "alien-ness" of this approach derives from the fact that the brain uses analogue components rather than (just) the discrete digital structures used in modern computation theory. I suspect that there is room for more to be said on this aspect.

I will definitely have to re-read parts of this book to get the most from it, but it does seem to be an important set of ideas!