Table of Contents

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

Reviews

"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
"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." -- IEEE Spectrum
"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