Bibliography

Most science books and journal articles have lengthy bibliographies, which serve
as much to catalog the contributions of others as to assist the reader. Given that
this book is intended for a variety of readers, including those with no previous
neuroscience knowledge, I have avoided writing the book in an academic style.
Similarly, this bibliography is designed primarily to assist the nonexpert reader who
wants to learn more. I don't list all relevant published research, nor do I attempt to
credit all the individuals who have made the fundamental discoveries in this field.
Instead I list selected items that I believe would be good materials for an
interested reader to learn more about brains. I also include several items that I
found useful but are mostly for the specialist. You can find in-depth discussions on
many of these topics on the World Wide Web. More bibliographic material can be
found on this book's Web site, www. OnIntelligence.org.

Unfortunately, you will find only a few references to overall theories of the brain
because, as I wrote in the prologue, not a lot has been written on this topic, and
even less on the specific proposals outlined in this book.

History of AI and Neural Networks

Baumgartner,

Peter, and Sabine Payr, eds. Speaking Minds: Interviews with Twenty
Eminent Cognitive Scientists (Princeton, N. J.: Princeton University Press,
1995).

This book contains interesting interviews with many of the leading thinkers in AI,
neural networks, and cognitive science. It is an easy and enjoyable synopsis of the
recent history and spirit of thinking on intelligence.

Dreyfus,

Hubert L. What Computers Still Can't Do: A Critique of Artificial Reason
(Cambridge, Mass.: MIT Press, 1992).

A harsh critique of AI originally published under the title What Computers Can't Do
and reissued years later with the revised title. It is an in-depth history of AI written
by one of its strongest critics.

Anderson,

James A., and Edward Rosenfeld, eds. N eurocomputing, Foundations of
Research (Cambridge, Mass.: MIT Press, 1988).
166
This large book is an annotated collection of important papers in neutral network
and brain theory spanning the years 1890 to 1987, presented in chronological
order. It contains papers by W. S. McCulloch and W. Pitts, Donald Hebb, Steve
Grossberg, and many others, with an introduction to each paper by the editors. It
is an easy way to read many of the important historical papers in this field.

Searle,

J. R. "Minds, Brains, and Programs," The Behavioral and Brain Sciences, vol.
3 (1980): pp. 417-24.

Presents the famous "Chinese Room" argument against computation as a model
for the mind. You can find many descriptions and discussions of Searle's thought
experiment on the World Wide Web.

Turing,

A. M. "Computing Machinery and Intelligence," Mind, vol. 59 (1950): pp.
433-60.

Presents the famous "Turing Test" for detecting the presence of intelligence.
Again, many references and discussions on the Turing Test can be found on the
World Wide Web.

Palm,

Günther. Neural Assemblies: An Alternative Approach to Artificial
Intelligence (New York: Springer Verlag, 1982).

To understand how the cortex works and how it stores sequences of patterns, it
helps to be familiar with auto-associative memories. And although much has been
written on auto-associative memories, I have not found any printed sources that
present an easily digested summary of what I consider important. Palm is one of
the pioneers in this field. This book of his is hard to obtain and not that easy to
read, but it covers the basics of auto-associative memories including sequence
memory.

Neocortex and General Neuroscience

The following books are recommended for those who want to learn more about
neurobiology and the neocortex.

Crick,
167
Francis H. C. "Thinking about the Brain," Scientific American, vol. 241
(September 1979): pp. 181-88. Also available in The Brain: A Scientific
American Book (San Francisco: W. H. Freeman, 1979).

This is the paper that got me interested in brains. Although it is twenty-five years
old, I still find this paper by Francis Crick inspiring.