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An Introduction to Model-Based Cognitive Neuroscience

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Cover of 'An Introduction to Model-Based Cognitive Neuroscience'

Table of Contents

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    Book Overview
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    Chapter 1 General Introduction to Model-Based Cognitive Neuroscience
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    Chapter 2 Linking Models with Brain Measures
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    Chapter 3 Reinforcement Learning
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    Chapter 4 An Introduction to the Diffusion Model of Decision-Making
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    Chapter 5 Discovering Cognitive Stages in M/EEG Data to Inform Cognitive Models
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    Chapter 6 Spiking, Salience, and Saccades: Using Cognitive Models to Bridge the Gap Between “How” and “Why”
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    Chapter 7 Ultrahigh Field Magnetic Resonance Imaging for Model-Based Neuroscience
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    Chapter 8 An Introduction to EEG/MEG for Model-Based Cognitive Neuroscience
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    Chapter 9 Advancements in Joint Modeling of Neural and Behavioral Data
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    Chapter 10 Cognitive Models as a Tool to Link Decision Behavior with EEG Signals
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    Chapter 11 Toward a Model-Based Cognitive Neuroscience of Working Memory Subprocesses
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    Chapter 12 Assessing Neurocognitive Hypotheses in a Likelihood-Based Model of the Free-Recall Task
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    Chapter 13 Cognitive Modeling in Neuroeconomics
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    Chapter 14 Cognitive Control of Choices and Actions
Attention for Chapter 3: Reinforcement Learning
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Summary
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Chapter title
Reinforcement Learning
Chapter number 3
Book title
An Introduction to Model-Based Cognitive Neuroscience
Published by
Springer, Cham, January 2024
DOI 10.1007/978-3-031-45271-0_3
Book ISBNs
978-3-03-145270-3, 978-3-03-145271-0
Authors

Man, Vincent, O’Doherty, John P.

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