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|a An introduction to model-based cognitive neuroscience /
|c Birte U. Forstmann, Brandon M. Turner, editors.
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|a Second edition.
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|a Cham :
|b Springer,
|c 2024.
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|a 1 online resource (vi, 388 pages) :
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|a The main goal of this edited collection is to promote the integration of cognitive modeling and cognitive neuroscience. Experts in the field provide tutorial-style chapters that explain particular techniques and highlight their usefulness through concrete examples and numerous case studies. The book also includes a thorough list of references pointing the reader toward additional literature and online resources. The second edition of Introduction to Model-Based Cognitive Neuroscience explores important new advances in the field including joint modeling and applications in areas such as computational psychiatry, neurodegenerative diseases, and social decision-making.
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|a Includes index.
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|a Online resource; title from PDF title page (SpringerLink, viewed April 5, 2024).
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|a Intro -- Contents -- General Introduction to Model-Based Cognitive Neuroscience -- 1 Introduction -- 1.1 What Is Model-Based Cognitive Neuroscience? -- 1.2 Neural Data Constrain the Behavioral Model -- 1.3 Behavioral Model Predicts Neural Data -- 1.4 Simultaneous Modeling -- 2 Prominent Models and Measures in the Field of Model-Based Cognitive Neuroscience -- 2.1 Types of Behavioral Measures -- 2.2 Types of Neural Measures -- 2.3 Types of Cognitive Models -- 3 Applications in the Field of Model-Based Cognitive Neuroscience -- 4 Future Directions -- 5 Open Challenges -- References.
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|a Linking Models with Brain Measures -- 1 Introduction -- 2 Some Functions of Models in Science -- 3 Levels of Analysis -- 4 Other Types of Models Useful in Analysing Brain Data -- 5 General Comparison of Model and Brain Data -- 6 Cognitive Model as Integral Part of the Data Analysis -- 7 Individual Differences -- 8 Models Can Uncover Useful Latent States -- 9 Comparing Model and Brain Representations -- 10 Multiple Levels of Representation -- 11 Conclusions -- Questions for Consideration -- Further Reading -- References -- Reinforcement Learning -- 1 Introduction -- 2 Reinforcement Learning.
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|a 2.1 Pavlovian Conditioning -- 2.1.1 Temporal-Difference Learning -- 2.2 Instrumental Conditioning -- 2.2.1 Actor-Critic Model -- 3 Model-Based fMRI -- 3.1 Univariate Approach -- 3.2 Multivariate Analyses -- 4 Considerations When Linking RL and fMRI Models -- 4.1 Evaluating Model Quality -- 4.2 Addressing Model Considerations -- 5 Bridging Levels of Analyses -- 5.1 Neural Correlates of Computational Processes -- 5.2 Leveraging fMRI to Adjudicate Between Models -- 5.3 Future Directions -- 6 Exercises -- 7 Further Reading -- References -- An Introduction to the Diffusion Model of Decision-Making.
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|a 1 Historical Origins -- 2 Diffusion Processes and Random Walks -- 3 The Standard Diffusion Model -- 4 Components of Processing -- 5 Bias and Speed-Accuracy Tradeoff Effects -- 6 Mathematical Methods for Diffusion Models -- 7 The Representation of Empirical Data -- 8 Fitting the Model to Experimental Data -- 9 Diffusion Models of Continuous Outcome Decisions -- 10 Conclusion -- 11 Suggestions for Further Reading -- 12 Exercises -- References -- Discovering Cognitive Stages in M/EEG Data to Inform CognitiveModels -- 1 Introduction -- 2 Part 1: The Discovery of Processing Stages in M/EEG Data.
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|a 2.1 The HsMM-MVPA Method -- 2.2 Discovering Cognitive Processing Stages in Associative Recognition -- 3 Part 2: A Symbolic Process Model -- 3.1 The Cognitive Architecture ACT-R -- 3.2 A Model of Associative Recognition -- 4 General Discussion -- Exercises -- Answers -- Further Reading -- References -- Spiking, Salience, and Saccades: Using Cognitive Models to Bridge the Gap Between H̀̀ow'' and Ẁ̀hy'' -- 1 Introduction -- 1.1 Dimensions of Constraint -- 2 A Case Study: SCRI -- 2.1 Phenomena to Be Explained -- 2.2 The Model -- 2.2.1 Motivating Principles -- 2.2.2 Conceptual Outline.
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| 650 |
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|a Cognitive neuroscience
|x Mathematical models.
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|a Human behavior models.
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| 650 |
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|a Neuropsychology.
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| 650 |
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|a Neurosciences cognitives
|x Modèles mathématiques.
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|a Modélisation du comportement humain.
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| 700 |
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|a Forstmann, Birte U.,
|e editor.
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| 700 |
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|a Turner, Brandon M.,
|d 1985-
|e editor.
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