Introduction to Neural and Cognitive Modeling

This textbook provides a general introduction to the field of neural networks, concentrating on networks for modeling brain processes involved in cognitive and behavioral functions.

Autorentext

Daniel S. Levine is Professor of Psychology at the University of Texas at Arlington. He is a Fellow and former President of the International Neural Network Society. His research involves computational modeling of brain processes in decision making and cognitive-emotional interactions.

Inhalt

Contents

Part I: Foundations of Neural Network Theory

* Chapter 1: Neural Networks for Modeling Behavior

• * Chapter 2: Historical Outline

• * Chapter 3: Associative Learning and Synaptic Plasticity

• * Chapter 4: Competition, Lateral Inhibition, and Short-Term Memory

• Part II: Computational Cognitive Neuroscience

* Chapter 5: Progress in Cognitive Neuroscience

• * Chapter 6: Models of Conditioning and Reinforcement Learning

• * Chapter 7: Models of Coding, Categorization, and Unsupervised Learning

• * Chapter 8: Models of Supervised Pattern and Category Learning

• * Chapter 9: Models of Complex Mental Functions

• Appendices *

Appendix 1: Mathematical Techniques for Neural Networks

• * Appendix 2: Basic Facts of Neurobiology

• References