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Why We See What We Do: An Empirical Theory of Vision

Why We See What We Do: An Empirical Theory of VisionAuthors: Dale Purves, R. Beau Lotto
Publisher: Sinauer Associates
Category: Book

List Price: $53.95
Buy New: $43.16
as of 11/21/2009 03:12 PST details
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New (9) Used (9) from $36.26

Seller: Amazon.com

Media: Paperback
Edition: 1
Pages: 260
Number Of Items: 1
Shipping Weight (lbs): 1.2
Dimensions (in): 9.2 x 7 x 0.7

ISBN: 0878937528
Dewey Decimal Number: 152.14
EAN: 9780878937523
ASIN: 0878937528

Publication Date: January 2003
Availability: Usually ships in 24 hours

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Editorial Reviews:

Product Description
This provocative book reviews a broad range of evidence leading to the conclusion that the visual system is not organized to generate a veridical representation of the physical world, but rather a statistical reflection of the visual history of the species and the individual observer. Thus, what humans actually see is a reflexive manifestation of past rather than a logical analysis of the present. The idea that the images we consciously entertain represent the historical significance of visual stimuli follows from the inability to decipher ambiguous retinal information analytically, and has far-reaching consequences not only for vision but brain function generally. The immediate benefit of this approach is that it provides a framework by which to understand a variety of fundamental visual illusions that are otherwise difficult, if not impossible, to explain.

With its straightforward style, Why We See What We Do can be understood by individuals with little or no background in neuroscience or vision. It includes chapter introductions and summaries that make the overall argument easy to follow, over 400 bibliographic citations, and a complete glossary.


Customer Reviews:
5 out of 5 stars A Paradigm Shift!!   August 15, 2007
Mark Dubin (Boulder, CO USA)
1 out of 1 found this review helpful

This book describes a fundamental shift in understanding how the visual system makes sense of what is seen. It is a must read for those interested in perception and in information processing by the brain. There has been much recent research supporting its hypotheses. The book signals a shift away from a mechanistic machine-like image reconstruction by the brain to a more intuitive and empirical model based on what we actually see.


5 out of 5 stars Well worth a look   June 6, 2006
David H. Peterzell (San Diego, CA United States)
8 out of 8 found this review helpful

The book's thesis is as follows: "The problem [of vision] is solved by having retinal stimuli trigger reflex responses... that have been determined purely by behavioral consequences of interactions with the environment over time. As a result, what observers actually experience in response to any visual stimulus is its accumulated statistical meaning... In short, the observer sees the probability distribution of the possible sources of the visual stimulus." There are two reviews of this book that are highly critical of its thesis. They are well worth reading. One is by Alan Gilchrist (Nature Neuroscience, 2003), and the other is by David Burr (J. Cognitive Neuroscience, 2005). I find myself agreeing with many of their criticisms of the central thesis, but...

I gave the book 5 stars anyway. (1) Each chapter's discussion of the basic problems of vision is clear and concise. (2) The artwork, and what it demonstrates, is well worth the price of admission. For instance, the illustrations of color perception and reflective surfaces are beautiful and powerful. The illustrations are simply phenomenal. (3) Perhaps the authors are re-inventing the wheel or kicking dead horses, but I'm just not so sure... The authors have forced me to re-think some ideas about vision that I've held for a long time. And I think they do a nice job of taking some truly old and cartoonish ideas about vision and relegating them to the dust heap. Even if their "empirical" theory of vision seems flawed or incomplete, there's much about it that I find myself wanting to re-visit and mull over. And if I'm not mistaken, various recent findings regarding the statistics of natural images are, independently, providing considerable evidence for the authors' thesis.


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