Two recent innovations, the emergence of formal cognitive models and the addition of cognitive neuroscience data to the traditional behavioral data, have resulted in the birth of a new, interdisciplinary field of study: model-based cognitive neuroscience. Despite the increasing scientific interest in model-based cognitive neuroscience, few active researchers and even fewer students have a good knowledge of the two constituent disciplines. The main goal of this edited collection is to promote the integration of cognitive modeling and cognitive neuroscience. Experts in the field will provide tutorial-style chapters that explain particular techniques and highlight their usefulness through concrete examples and numerous case studies. The book will also include a thorough list of references pointing the reader towards additional literature and online resources.
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1 An Introduction to Cognitive Modeling |
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3 | (22) |
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2 An Introduction to Good Practices in Cognitive Modeling |
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25 | (24) |
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3 An Introduction to the Diffusion Model of Decision Making |
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49 | (22) |
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4 An Introduction to Human Brain Anatomy |
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71 | (20) |
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5 An Introduction to fMRI |
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91 | (22) |
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6 An Introduction to Neuroscientific Methods: Single-cell Recordings |
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113 | (26) |
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7 Model-Based Cognitive Neuroscience: A Conceptual Introduction |
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139 | (20) |
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Part II How Cognitive Models Inform the Cognitive Neurosciences |
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8 Linking Across Levels of Computation in Model-Based Cognitive Neuroscience |
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159 | (20) |
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9 Bayesian Models in Cognitive Neuroscience: A Tutorial |
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179 | (20) |
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10 Constraining Cognitive Abstractions Through Bayesian Modeling |
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199 | (22) |
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11 Predictive Coding in Sensory Cortex |
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221 | (24) |
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12 Using Human Neuroimaging to Examine Top-down Modulation of Visual Perception |
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245 | (32) |
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Part III How the Cognitive Neurosciences Inform Cognitive Models |
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13 Distinguishing Between Models of Perceptual Decision Making |
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277 | (14) |
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14 Optimal Decision Making in the Cortico-Basal-Ganglia Circuit |
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291 | (12) |
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15 Inhibitory Control in Mind and Brain: The Mathematics and Neurophysiology of the Underlying Computation |
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303 | (18) |
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16 Reciprocal Interactions of Computational Modeling and Empirical Investigation |
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321 | (18) |
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17 Using the ACT-R Cognitive Architecture in Combination With fMRI Data |
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339 | (14) |
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| Index |
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353 | |
Birte Forstmann is a Professor for Cognitive Neurosciences at the University of Amsterdam as well as honorary professor at the University of Leiden. She earned her PhD in 2006 at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. After completing her postdoc in 2008 at the University of Amsterdam, she became tenured Research Fellow at the Cognitive Science Center Amsterdam with the focus of model-based cognitive neurosciences. Since then she has contributed to a range of topics in cognitive neuroscience, experimental psychology, mathematical psychology, and lately also in quantitative neuroanatomy.
Eric-Jan (EJ) Wagenmakers is a professor at the Psychological Methods Unit of the University of Amsterdam. His current work concerns Bayesian inference, philosophy of science, mathematical models of cognition, and model-based cognitive neuroscience. His studies in cognitive neuroscience are guided by the conviction that mathematical process models can provide useful structure and constraint for the analysis and interpretation of brain data.
