INTRODUCTION TO NEURAL AND COGNITIVE MODELING, 3RD EDITION

Book Details
• Author: Levine, Daniel S.
• Brand: Taylor & Francis Ltd
• Edition: 3
• Binding: Paperback
• Format: Illustrated
• Number of Pages: 466
• Release Date: 12-10-2018
• EAN: 9781848726482
• Package Dimensions: 9.0 x 6.0 x 1.0 inches
• Languages: English

Description
This textbook provides a general introduction to the field of neural networks. Thoroughly revised and updated from previous editions, the current edition concentrates on networks for modeling brain processes involved in cognitive and behavioral functions.

• Part one: Explores the philosophy of modeling and the field’s history, starting from the mid-1940s, and then discusses past models of associative learning and short-term memory that provide building blocks for more complex models.

• Part two: Reviews recent experimental findings in cognitive neuroscience, discussing models of conditioning, categorization, visual attention, sequence learning, behavioral control, decision making, reasoning, and creativity.

• The book presents these models both as abstract ideas and through examples and concrete data for specific brain regions.

It also includes two appendices: one reviewing the mathematics used in network modeling and another reviewing basic neuroscience. The book is filled with equations, practice exercises, and thought experiments.

Review

• "This new edition provides a remarkable overview of neural and cognitive modeling, from its inception nearly a century ago to the latest advancements. Perfect for advanced undergraduates and graduate students." – Professor Joshua W. Brown, Indiana University, USA

• "Levine's book synthesizes historical trends and current research results, clarifying the power of biological learning models. It’s a solid introduction to key neural models in cognition." – Stephen Grossberg, Boston University, USA

About the Author
Daniel S. Levine is a 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 focuses on computational modeling of brain processes in decision-making and cognitive-emotional interactions.