Computational Psychiatry: Mathematical Modeling of Mental Illness

by Alan Anticevic (Editor), John D Murray (Editor)

Overview

Computational Psychiatry: Mathematical Modeling of Mental Illness is the first systematic effort to bring together leading scholars in the fields of psychiatry and computational neuroscience who have conducted the most impactful research and scholarship in this area. It includes an introduction outlining the challenges and opportunities facing the field of psychiatry that is followed by a detailed treatment of computational methods used in the service of understanding neuropsychiatric symptoms, improving diagnosis and guiding treatments. This book provides a vital resource for the clinical neuroscience community with an in-depth treatment of various computational neuroscience approaches geared towards understanding psychiatric phenomena. Its most valuable feature is a comprehensive survey of work from leaders in this field. - Offers an in-depth overview of the rapidly evolving field of computational psychiatry - Written for academics, researchers, advanced students and clinicians in the fields of computational neuroscience, clinical neuroscience, psychiatry, clinical psychology, neurology and cognitive neuroscience - Provides a comprehensive survey of work from leaders in this field and a presentation of a range of computational psychiatry methods and approaches geared towards a broad array of psychiatric problems

Product Details

ISBN-13:	9780128098264
Publisher:	Elsevier Science & Technology Books
Publication date:	09/19/2017
Sold by:	Barnes & Noble
Format:	eBook
Pages:	332
File size:	35 MB
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About the Author

Alan Anticevic, Ph.D., is an Assistant Professor of Psychiatry and Psychology at Yale University School of Medicine, where he co-directs a research division and laboratory focused on the integration of cognitive, computational and clinical neuroimaging approaches with the objective of understanding the neurobiology of neuropsychiatric disorders. He received his Ph.D. in Clinical Neuropsychology and Cognitive Neuroscience from Washington University in St. Louis.
John D. Murray, Ph.D., is an Assistant Professor of Psychiatry, Neuroscience, and Physics at Yale University School of Medicine, where he directs a research program in computational neuroscience with a focus on computational models of neuropsychiatric disorders. He received his Ph.D. in Physics from Yale University, and was a postdoctoral researcher at New York University.

Table of Contents

Meeting Emerging Challenges and Opportunities in Psychiatry Through Computational NeuroscienceSection I. Applying Circuit Modeling to Understand Psychiatric Symptoms1. Cortical Circuit Models in Psychiatry: Linking Disrupted Excitation-Inhibition Balance to Cognitive Deficits Associated with Schizophrenia2. Serotonergic Modulation of Cognition in Prefrontal Cortical Circuits in Major Depression3. Dopaminergic Neurons in the Ventral Tegmental Area and their Dysregulation in Nicotine AddictionSection II. Modeling Neural System Disruptions in Psychiatric Illness4. Computational Models of Dysconnectivity in Large-Scale Resting-State Networks5. Dynamic Causal Modelling and its Application to Psychiatric Disorders6. Systems Level Modeling of Cognitive Control in Psychiatric Disorders: A focus on schizophrenia7. Computational Psychiatry: Mathematical Modeling of Mental IllnessSection III: Characterizing Complex Psychiatric Symptoms via Mathematical Models8. A Case Study in Computational Psychiatry: Addiction as Failure Modes of the Decision-Making System9. Modeling Negative Symptoms in Schizophrenia10. Bayesian Approaches to Learning and Decision Making11. Computational Phenotypes Revealed by Interactive Economic Games

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From the Publisher

The first comprehensive book to focus on computational modeling of neuropsychiatric disorders