Population neuroimaging is an emerging field with the goal to understand brain structure, function, development, and ageing within the general population, including the inherent variety and diversity of health or illness within the population. Unlike studies that recruit patients with specific illnesses, population neuroimaging encompasses epidemiological approaches to better understand genetic and environmental factors that contribute to both brain health and brain disorders in the population at large. This book covers important themes within population neuroimaging and provides the reader with the tools to understand and engage in population-based neuroimaging studies.
Table of Contents
Part I Overview and Design Considerations 1. Overview and introduction 2. Population Neuroimaging Study design, Setup, and Quality 3. Infrastructure for Large Scale Population Neuroimaging Studies 4. Image Processing 5. Incidental Findings
Part II Methodological and Statistical Considerations 6. Statistical challenges in Population Neuroimaging 7. Methodological challenges 8. Replication, Reproducibility, Reliability
Part III Applications 9. Public Health Relevance 10. Population Neuroimaging Domains 11. Data Sharing 12. Future Directions
Authors
Ryan Muetzel Assistant Professor, Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Ryan Muetzel, PhD, is an Assistant Professor in the Department of Child and Adolescent Psychiatry/Psychology at the Erasmus MC University Medical Center in Rotterdam. Ryan completed his undergraduate training in psychology and biology at the University of Minnesota, and his Master of Science degree in Epidemiology at the Netherlands Institute for Health Sciences. His PhD focused on population neuroscience and neuroimaging at the Erasmus University in Rotterdam. He Co-Directs one of the world's largest neuroimaging studies of neurodevelopment, the Generation R Study. His group, the Integrative and Precision Neuroimaging Lab focuses on studying typical and atypical brain development using longitudinal neuroimaging data across four domains: i.) understanding the bidirectional relationship between psychiatric problems and brain over time, ii.) using statistical learning techniques to identify complex patterns in neuroimaging data which are predictive of mental illness, iii.) understanding how various risk and resilience factors shape the brain in the context of mental illness, and iv.) development of open source population neuroimaging tools which enable neuroimaging researchers to incorporate epidemiological concepts into their work.
Tonya White Associate Professor, Department of Child and Adolescent Psychiatry, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Tonya White, MD, PhD is an associate professor in the Department of Child and Adolescent Psychiatry at Erasmus MC University Medical Center in Rotterdam. She received Bachelors (Magna Cum Laude from the University of Utah) and Masters (University of Illinois) degrees in Electrical Engineering prior to completing medical school at the University of Illinois and later a Ph.D. from Erasmus University in Rotterdam, the Netherlands. Her residency involved a combined pediatrics, psychiatry, and child and adolescent psychiatry program (Triple Board Program) at the University of Utah, after which she completed a research fellowship in neuroimaging under the mentorship of Nancy C. Andreasen. Following a junior faculty position at the University of Minnesota, she joined the faculty at Erasmus University Medical Center in 2009 to set up and direct the neuroimaging program in the Generation R study, which has become the largest neuroimaging birth cohort in the world. Her primary focus is in pediatric population neuroimaging. Her primary research goals are to apply neuroimaging techniques to obtaining a better understanding of genetic and environmental factors associated with typical and atypical brain development in hopes that this will translate into either preventing or decreasing the morbidity of severe psychiatric disorders.
