In this groundbreaking work, computer scientist Leslie G. Valiant details a promising new computational approach to studying the intricate workings of the human brain. Focusing on the brain's enigmatic ability to access quickly a massive store of accumulated information during reasoning processes, the author asks how such feats are possible given the extreme constraints imposed by the brain's finite number of neurons, their limited speed of communication, and their restricted interconnectivity. Valiant proposes a "neuroidal model" that serves as a vehicle to explore these fascinating questions. While embracing the now classical theories of McCulloch and Pitts, the neuroidal model also accommodates state information in the neurons, more flexible timing mechanisms, a variety of assumptions about interconnectivity, and the possibility that different areas perform different functions. Programmable so that a wide range of algorithmic theories can be described and evaluated, the model provides a concrete computational language and a unified framework in which diverse cognitive phenomena-such as memory, learning, and reasoning-can be systematically and concurrently analyzed. Requiring no specialized knowledge, Circuits of the Mind masterfully offers an exciting new approach to brain science for students and researchers in computer science, neurobiology, neuroscience, artificial intelligence, and cognitive science.
1. The Approach ; 2. Biological Constraints ; 3. Computational Laws ; 4. Cognitive Functions ; 5. The Neuroidal Model ; 6. Knowledge Representation ; 7. Unsupervised Memorization ; 8. Supervised Memorization ; 9. Supervised Inductive Learning ; 10. Correlational Learning ; 11. Objects and Relational Expressions ; 12. Systems Questions ; 13. Reasoning ; 14. More Detailed Neural Models ; 15. Afterword
Delivers what its title promises, and more: an engaging, broad, thorough, and often deep, development of undergraduate complex analysis and related areas (non-Euclidean geometry, harmonic functions, etc.) from a geometric point of view. The style is lucid, informal, reader-friendly, and rich with helpful images (e.g., the complex derivative as an "amplitwist"). A truly unusual and notably creative look at a classical subject. * American Mathematical Monthly * Although there are many books today dealing with a simple neuronal model based on the weighted sum principle, this one rises above these others in providing an explanation of cognitive functions. * Choice * The author shows that the proposed neuroidal model supports the cognitive activities he identifies. It provides a good structure to explore the functions of the mind still further. * IIEEE Spectrum * The book is written in a clear style, with a sufficient number of figures illustrating the algorithms. . .This new insight into complex problems of the brain, as well as the proposed methodology, makes the book highly readable and interesting. * Computing Reviews *