Using Neuroscience Insights to Inform Personally Tailored, Measurement-Based Care
Psychiatry is dedicated to understanding mental disorders and helping people struggling with them live fulfilling lives. Although current treatment modalities can be remarkably effective at improving patients' quality of life and mitigating the burden of symptoms for disorders like depression, bipolar disorder, or posttraumatic stress disorder, finding the right treatment for an individual can be a long and fraught process during which symptoms can worsen the risks associated with other health conditions.
Precision psychiatry, as outlined in this groundbreaking book, presents a new path forward. By integrating findings from basic and clinical neuroscience, clinical practice, and population-level data, the field seeks to develop therapeutic approaches tailored for specific individuals with a specific constellation of health issues, characteristics, strengths, and symptoms.
This guide harnesses the expertise of more than three dozen contributors in diverse areas of interest, including neuroimaging, electrophysiology, neurocognition, behavioral science, machine learning, and pharmacotherapy, to examine the current state of precision medicine in psychiatry and explore future areas of advancement.
Numerous case examples illustrate and apply the principles of precision psychiatry to mood and anxiety disorders, as well as schizophrenia, in adult patients, emphasizing the push to develop biomarkers and algorithms that will identify subtypes of patients that may be underserved by conventional therapies.
In these pages, educators, trainees, and clinicians will find the latest research in precise classification, treatment planning, and early identification across a spectrum of psychiatric disorders—and the foundation for a future where one-size-fits-all treatments are replaced by modalities optimized for individual patients across all stages of a disorder.
- Part 1: Neuroimaging of Circuits
- Chapter 1. A Neural Circuit-Informed Taxonomy for Precision Psychiatry
- Chapter 2. The Future of Precision TMS in Psychiatry
- Chapter 3. Neural Mechanisms of Bipolar Disorder
- Part 2: Neurocognition, Neurophysiology, and Behavior
- Chapter 4. Information Processing Impairments as Transdiagnostic Treatment Targets
- Chapter 5. State-Sensitive Vision Science-Based Markers in People with Schizophrenia
- Part 3: Blood Markers
- Chapter 6. Using Inflammatory Biomarkers to Identify Transdiagnostic Subtypes
- Chapter 7. Pharmacogenetic Testing
- Part 4: Translational Neurobiological Approaches
- Chapter 8. Treatment Prediction Biomarkers for Major Depression
- Chapter 9. Translational Neurobiological Approaches to Precision Medicine
- Part 5: New Approaches and Computational Models That Bridge Neuroscience Insights and Clinical Application
- Chapter 10. Latent Variable-Based Predictive and Explanatory Disease Models
- Chapter 11. Computational Cognitive Methods for Precision Psychiatry
- Chapter 12. Toward Precision CBT via Reinforcement Learning Theory
- Part 6: Developing the Academic Discipline of Precision Psychiatry
- Chapter 13. Moving from Precision to Personalized Psychiatry: Clinical Perspectives
- Chapter 14. Preparing for the Future of Precision Psychiatry
About the Authors
Leanne M. Williams, Ph.D., is Professor and Associate Chair of Translational Neuroscience and Director of the Precision Psychiatry and Translational Neuroscience Lab (PanLab) in the Stanford Department of Psychiatry and Behavioral Sciences; Director of the Stanford Center for Precision Mental Health and Wellness at Stanford University School of Medicine; and Director of Precision Medicine at the Department of Veterans Affairs, Sierra-Pacific MIRECC, California.
Laura M. Hack, M.D., Ph.D., is a Postdoctoral Fellow, Advanced Fellowship in Mental Illness Research and Treatment, in the Palo Alto Veterans Affairs Health Care System, Sierra-Pacific MIRECC; and Clinical Instructor and Director of the Translational Precision Mental Health Clinic in the Department of Psychiatry and Behavioral Sciences at Stanford University School of Medicine in Stanford, California.
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