Computational Psychiatry: Mathematical Modeling of Mental Illness, 1st Edition

  • Alan Anticevic
  • John Murray Trinity College
  • Published By:
  • ISBN-10: 0128098260
  • ISBN-13: 9780128098264
  • DDC: 616.890028
  • Grade Level Range: College Freshman - College Senior
  • 332 Pages | eBook
  • Original Copyright 2018 | Published/Released April 2018
  • This publication's content originally published in print form: 2018

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This text 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.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Meeting Emerging Challenges and Opportunities in Psychiatry Through Computational Neuroscience.
Applying Circuit Modeling to Understand Psychiatric Symptoms.
1: Cortical Circuit Models in Psychiatry: Linking Disrupted ExcitationeInhibition Balance to Cognitive Deficits Associated With Schizophrenia.
2: Serotonergic Modulation of Cognition in Prefrontal Cortical Circuits in Major Depression.
3: Dopaminergic Neurons in the Ventral Tegmental Area and Their Dysregulation in Nicotine Addiction.
Modeling Neural System Disruptions in Psychiatric Illness.
4: Computational Models of Dysconnectivity in Large-Scale Resting-State Networks.
5: Dynamic Causal Modeling and Its Application to Psychiatric Disorders.
6: Systems Level Modeling of Cognitive Control in Psychiatric Disorders: A Focus on Schizophrenia.
7: Bayesian Inference, Predictive Coding, and Computational Models of Psychosis.
Characterizing Complex Psychiatric Symptoms via Mathematical Models.
8: A Case Study in Computational Psychiatry: Addiction as Failure Modes of the Decision-Making System.
9: Modeling Negative Symptoms in Schizophrenia.
10: Bayesian Approaches to Learning and Decision-Making.
11: Computational Phenotypes Revealed by Interactive Economic Games.