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.

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. Neurocomputing, Foundations of Research (Cambridge, Mass.: MIT Press, 1988).

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, Güther. 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.

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

Crick, 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.

Koch, Christof. Quest for Consciousness: A Neurobiological Approach (Denver, Colo.: Roberts and Co., 2004).

There are several general-interest brain books published every year. This one by Christof Koch is about consciousness but it covers most of the relevant topics on brains, neuroanatomy, neurophysiology, and consciousness. If you want a basic introduction to neurobiology and brain science in a single readable book, this would be a good place to start.

Mountcastle, Vernon B. Perceptual Neuroscience: The Cerebral Cortex (Cambridge, Mass.: Harvard University Press, 1998).

A great book dedicated to everything and anything about the neocortex. It is well written, has a clean layout, and, although technical, I find it a joy to read. It is one of the best introductions to the neocortex.

Kandel, Eric R., James H. Schwartz, Thomas M. Jessell, eds. Principles of Neural Science, 4th ed. (New York: McGraw-Hill, 2000).

This is a one-volume encyclopedia of all things neural. This big book is not for bedtime reading but it is a good reference book to have. It provides detailed introductions to all parts of the nervous system, including neurons, sensory organs, and neurotransmitters.

Shepherd, Gordon M., ed. The Synaptic Organization of the Brain, 5th ed. (New York: Oxford University Press, 2004).

This book has been helpful to me, although I preferred the earlier editions, which had a single author. It is a technical resource on all parts of the brain, especially synapses. I use it as a reference.

Koch, Christof, and Joel L. Davis, eds. Large-scale Neuronal Theories of the Brain (Cambridge, Mass.: MIT Press, 1994).

There is very little written on overall theories of the brain. This book is a compilation of papers on this very topic, although most of the papers in this volume fall short of the goal suggested by the title. This book gives an overview of the varied approaches people are taking to understanding how the overall brain works. You can find bits and pieces of the memory-prediction framework throughout the book.

Braitenberg, Valentino, and Almut Schüz. Cortex: Statistics and Geometry of Neuronal Connectivity, 2nd ed. (New York: Springer Verlag, 1998).

This book describes the statistical properties of the mouse brain. I know that doesn’t sound very exciting but it is a refreshing and useful book. It tells the story of the cortex in numbers.

The following articles are the original sources for some of the important concepts described in this book. Most of these can only be found in a university library or online.

Mountcastle, Vernon B. “An Organizing Principle for Cerebral Function: The Unit Model and the Distributed System,” in Gerald M. Edelman and Vernon B. Mountcastle, eds., The Mindful Brain (Cambridge, Mass.: MIT Press, 1978).

This paper is where I first read Mountcastle’s proposal for how the entire neocortex works on a common principle. Mountcastle also proposes that a cortical column is the basic unit of computation. These ideas are both the premise and the inspiration for the theory proposed in this book.

Creutzfeldt, Otto D. “Generality of the Functional Structure of the Neocortex,” Naturwissenschaften, vol. 64 (1977): pp. 507–17.

After I finished writing On Intelligence, I became aware of this paper, which, like Mountcastle’s, argues for a common cortical algorithm. It was published slightly before Mountcastle’s and is a nice complement to his.

Felleman, D. J., and D. C. Van Essen. “Distributed Hierarchical Processing in the Primate Cerebral Cortex,” Cerebral Cortex, vol. 1 (January/February 1991): pp. 1–47.

This is the now-classic paper describing the hierarchical organization of the visual cortex. The memory-prediction framework is built on the assumption that not only the visual system but the entire neocortex has a hierarchical structure.

Sherman, S. M., and R. W. Guillery. “The Role of the Thalamus in the Flow of Information to the Cortex,” Philosophical Transactions of the Royal Society of London, vol. 357, no. 1428 (2002): pp. 1695–708.

Provides an overview of thalamic organization and lays out the Sherman-Guillery hypothesis in which the thalamus serves to gate information flow between cortical areas. I elaborate on this idea in chapter 6 in the section titled “An Alternate Path up the Hierarchy.”

Rao, R. P., and D. H. Ballard. “Predictive Coding in the Visual Cortex: A Functional Interpretation of Some Extra-Classical Receptive-field Effects,” Nature Neuroscience, vol. 2, no. 1 (1999): pp. 79–87.

I include this paper as an example of recent research that discusses prediction and hierarchies. Rao and Ballard’s paper presents a model of feedback in cortical hierarchies, in which neurons in higher areas attempt to predict patterns of activity in lower areas.

Guillery, R. W. “Branching Thalamic Afferents Link Action and Perception,” Journal of Neurophysiology, vol. 90 (2003): pp. 539–48.

Young, M. P. “The Organization of Neural Systems in the Primate Cerebral Cortex,” Proceedings of the Royal Society: Biological Sciences, vol 252 (1993): pp. 13–18.

These two well-written papers provide evidence that motor behavior and sensory perception are intimately related and part of the same process. Guillery argues that all sensory cortical areas play a role in motor behavior and Young shows that motor cortex and somatosensory cortex are so tightly linked that they should be considered one system. I briefly discuss these ideas in chapter 6.