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Population neuroimaging is an emerging field with the goal to understand brain structure, function, development, and ageing within the general population, including the inherent… Read more
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Part I Overview and Design Considerations
1. Overview and introduction
1.1. Overview of population neuroscience
1.2. Introduction to epidemiologic principles
1.3. Neuroimaging primer
1.4. Introduction to population neuroimaging
2. Population Neuroimaging Study design, Setup, and Quality
2.1. Study designs
2.2. Protocol Considerations
Imaging sequences
Multisite Considerations
2.3. Protocol Stability and Quality Control (perhaps split into 2 chapters)
Phantom, Human, Scanner Stability, Protocol Stability
3. Infrastructure for Large Scale Population Neuroimaging Studies
3.1. Data storage and management
3.2. Image analysis
3.3. high performance computing
4. Image Processing
4.1. Structural
4.2. Diffusion Tensor Imaging
4.3. Resting State Functional MRI
4.4. Task-based Functional MRI
4.5. Other sequences
4.6. Quality Control
5. Incidental Findings
5.1. General (protocol options, sequence selection)
5.2. Ethical considerations
Part II Methodological and Statistical Considerations
6. Statistical challenges in Population Neuroimaging
6.1. Statistical inference and multiple testing correction
6.2. effect sizes, confidence intervals
6.3. multivariate methods
6.4. novel population methods
7. Methodological challenges
7.1. Confounding
7.2. Other bias
7.3. Epidemiological Methods
7.4. Causal Inference
8. Replication, Reproducibility, Reliability
8.1. General
8.2. State of the Art
Part III Applications
9. Public Health Relevance
9.1. World Health Organization / OHBM initiative
9.2. Under-represented countries in brain mapping
9.3. Opportunities for population neuroimaging in public health
10. Population Neuroimaging Domains
10.1. Prenatal Exposures
10.2. Neurology
10.3. Radiology
10.4. Psychiatry
10.5. Family/Early Environment
10.6. Stress and brain development
10.7. Air pollution
10.8. Public Health
10.9. Imaging Genetics
11. Data Sharing
11.1. General
11.2. Open Cohort Profiles
12. Future Directions
12.1. Discovering transdiagnostic stratifications
12.2. Normative Modelling
12.3. Multimodal integration
12.4. Multi-organ systems interactions
12.5. Role in Precision Medicine
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Henning Tiemeier is a Professor of Social and Behavioral Science and the Sumner and Esther Feldberg Chair in Maternal and Child Health at the Harvard T.H. Chan School of Public Health, Boston, where he directs the Harvard Center of Excellence in Maternal and Child Health. He received both his medical and sociological degrees from the University of Bonn, Germany, and his PhD from the Erasmus University in Rotterdam, Netherlands.
Tiemeier is a psychiatric epidemiologist who studies child development in population-based cohort studies. His work has a focus on prenatal exposures such as maternal depression and substance use. Much of his work takes a neurodevelopmental approach and his group conducted large scale brain imaging studies in children and adolescents. Recent work shows how parenting and environmental risk factors relate to brain development in childhood and pre-adolescence. Other studies highlight methodological problems in child and adolescent psychiatric research using multi-informant assessments. His multidisciplinary work combining epidemiology, genetics, brain imaging, and child development bridges historically separate disciplines and forms Population Neuroscience. He has conducted large scale population-based birth cohorts from fetal life onwards as well as follow-up studies of international adoptees with exposure to early life trauma and abuse.
At the Harvard TH Chan School of Public Health, he mainly focusses on Population Neuroscience, he has received NIH funding to establish the Mississippi Delta Center of Excellence in Maternal Health to conduct observational studies and trials to improve maternal morbidity, and also works on a longitudinal study of children of incarcerated mothers. Tiemeier has received several honors among which the 2017 Dutch VICI prize, the 2019 Leon Eisenberg Award, and the 2023 Alzheimer Award.