DESCRIPTION:
- The book goes beyond current understanding of how the cerebral cortex operates, by combining evidence from different disciplines.
- Presents theories of operation of the hippocampus in memory, and of visual object recognition, to illustrate how the principles combine to produce theories of operation of brain systems.
- Includes comprehensive appendices that allow the reader to develop an understanding of how networks in the cerebral cortex operate, and how information theory can be used to quantify neuronal encoding.
- Describes neuronal network simulation software written in Matlab which allows readers to gain insight into how biologically plausible neuronal networks operate.

CONTENTS:
1. Introduction
2. Hierarchical Organization
3. Localization of Function
4. Recurrent Collateral Connections and Attractor Networks
5. The Noisy Cortex: Stochastic dynamics, decisions, and memory
6. Attention, Short-term Memory, and Biased Competition
7. Diluted Connectivity
8. Coding Principles
9. Synaptic Modification for Learning
10. Synaptic and Neuronal Adaptation and Facilitation
11. Backprojections in the Neocortex
12. Memory and the Hippocampus
13. Limited Neurogenesis in the Adult Cortex
14. Invariance Learning and Vision
15. Emotion, Motivation, Reward Value, Pleasure, and their Mechanisms
16. Noise in the Cortex, Stability, Psychiatric Disease, and Aging
17. Syntax and Language
18. Evolutionary Trends in Cortical Design and Principles of Operation
19. Genetics and Self-Organization Build the Cortex
20. Cortex versus Basal Ganglia Design for Selection
21. Sleep and Dreaming
22. Which Cortical Computations Underlie Consciousness?
23. Cerebellar Cortex
24. The Hippocampus and Memory
25. Invariant Visual Object Recognition Learning
26. Synthesis
Introduction to Linear Algebra for Neural Networks
Neural Network Models
Information Theory and Neuronal Encoding
Simulation Software for Neuronal Network Models
References
Index
Colour Plates