Introduction to Modeling Cognitive Processes

Tom Verguts

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English

MIT Press
22 February 2022

Cognition & cognitive psychology

An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments.

An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments.

Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field's proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills.

After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and Bayesian models; and models of social interaction. All mathematical concepts are introduced gradually, with no background in advanced topics required. Hints and solutions for exercises and a glossary follow the main text. All code in the book is Python, with the Spyder editor in the Anaconda environment. A GitHub repository with Python files enables readers to access the computer code used and start programming themselves. The book is suitable as an introduction to modeling cognitive processes for students across a range of disciplines and as a reference for researchers interested in a broad overview.

By: Tom Verguts
Imprint: MIT Press
Country of Publication: United States
Dimensions: Height: 254mm, Width: 178mm,
Weight: 567g
ISBN: 9780262045360
ISBN 10: 0262045362
Pages: 256
Publication Date: 22 February 2022
Audience: General/trade , ELT Advanced
Format: Hardback
Publisher's Status: Active

Preface and Acknowledgments ix 1 What Is Cognitive Modeling? 1 2 Decision Making 17 3 Hebbian Learning 37 4 The Delta Rule 53 5 Multilayer Networks 69 6 Estimating Parameters in Computational Models 89 7 Testing and Comparing Computational Models 107 8 Reinforcement Learning: The Gradient Ascent Approach 123 9 Reinforcement Learning: The Markov Decision Process Approach 133 10 Unsupervised Learning 153 11 Bayesian Models 173 12 Interacting Organisms 191 Convention and Notation 203 Glossary 205 Hints and Solutions to Select Exercises 207 Notes 217 References 219 Index 243

Tom Verguts is Professor in the Department of Experimental Psychology at Ghent University.