3rd Edition
Introduction to Neural and Cognitive Modeling 3rd Edition
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
Biography
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.
‘Newly updated with advances in cognitive neuroscience and modeling, this introductory textbook provides a remarkable overview of the whole field of neural and cognitive modeling, from its inception nearly a century ago to the most recent advances. The beginner can easily gain an overview of the principles of modeling, while the advanced student will find ample mathematical detail and practical simulation exercises. This new edition will be my go-to text for advanced undergraduates and graduate students looking for an introduction to the subject.’ Professor Joshua W. Brown, Indiana University, USA
‘Levine's book achieves an impressive synthesis of historical trends and current research results in both biological and artificial neural network research. This synthesis clarifies that the currently popular Deep Learning is just one contribution to this burgeoning field, and one that does not incorporate many of the most powerful properties of biological learning. Levine's book provides an accessible introduction to many of these properties, while also reviewing important properties of neural models of vision and visual attention, sequence learning and performance, executive function, and decision-making, among its other expository accomplishments.’ Stephen Grossberg, Boston University, USA
