Theodore Daniel Satterthwaite

· MD, MA

University of Pennsylvania · Rehabilitation Medicine

Active 2007–2024

h-index94

Citations40.6k

Papers830581 last 5y

Funding$32.2M5 active

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About

Theodore Daniel Satterthwaite, MD, MA, is a Professor of Psychiatry at the University of Pennsylvania Perelman School of Medicine. He is a member of multiple research centers including the Center for Neuroimaging in Psychiatry, the Center for Biomedical Computing and Image Analysis, the Center for Functional Neuroimaging, and the Institute for Translational Medicine and Therapeutics. Dr. Satterthwaite also holds affiliations with the Warren Center for Network and Data Science, the Center for the Neuroscience of Depression and Stress, the Penn/CHOP Lifespan Brain Institute, and the Center for Autism Research at Children's Hospital of Philadelphia, among others. He serves as the Director of the Penn Lifespan Informatics and Neuroimaging Center (PennLINC) and is a Senior Fellow at the Institute of Biomedical Informatics. His research focuses on using advanced analytics to integrate complex brain images and behavioral data to map normal brain development and understand how alterations in brain maturation increase the risk of psychiatric illness. Dr. Satterthwaite's clinical expertise includes mood disorders. He is actively involved in academic and clinical activities at the University of Pennsylvania, contributing to the understanding of neuroimaging and neuroinformatics in psychiatry.

Research topics

Computer Science
Psychology
Neuroscience
Medicine
Artificial Intelligence
Psychiatry
Data Mining
Cognitive psychology
Biology
Computer vision
Physics
Audiology
Database
Developmental psychology
Gerontology
Data science
Cognitive science
Internal medicine
Radiology
Social psychology
Cardiology
Computational biology
Clinical psychology

Selected publications

Intrinsic activity development unfolds along a sensorimotor–association cortical axis in youth
Nature Neuroscience · 2023 · 185 citations
Senior authorCorresponding
- Neuroscience
- Psychology
- Biology
DOI
Brain charts for the human lifespan
Nature · 2022 · 1720 citations
- Computer Science
- Biology
- Neuroscience
, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
DOI
Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group
Translational Psychiatry · 2021 · 68 citations
- Psychology
- Clinical psychology
- Psychiatry
The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.
DOI
Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3–90 years
Human Brain Mapping · 2021 · 161 citations
- Psychology
- Neuroscience
- Gerontology
Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
DOI
Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology
Neuron · 2021 · 733 citations
Senior authorCorresponding
- Neuroscience
- Psychology
- Biology
DOI
QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data
Nature Methods · 2021 · 315 citations
Senior authorCorresponding
- Computer Science
- Computer Science
- Data Mining
DOI
Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3–90 years
Human Brain Mapping · 2021 · 289 citations
- Psychology
- Neuroscience
- Developmental psychology
Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
DOI
<scp>Mega‐analysis</scp> methods in <scp>ENIGMA</scp> : The experience of the generalized anxiety disorder working group
Human Brain Mapping · 2020 · 77 citations
- Computer Science
- Psychology
- Computer Science
The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.
DOI
Structural and Functional Brain Parameters Related to Cognitive Performance Across Development: Replication and Extension of the Parieto-Frontal Integration Theory in a Single Sample
Cerebral Cortex · 2020 · 34 citations
- Psychology
- Audiology
- Neuroscience
The parieto-frontal integration theory (PFIT) identified a fronto-parietal network of regions where individual differences in brain parameters most strongly relate to cognitive performance. PFIT was supported and extended in adult samples, but not in youths or within single-scanner well-powered multimodal studies. We performed multimodal neuroimaging in 1601 youths age 8-22 on the same 3-Tesla scanner with contemporaneous neurocognitive assessment, measuring volume, gray matter density (GMD), mean diffusivity (MD), cerebral blood flow (CBF), resting-state functional magnetic resonance imaging measures of the amplitude of low frequency fluctuations (ALFFs) and regional homogeneity (ReHo), and activation to a working memory and a social cognition task. Across age and sex groups, better performance was associated with higher volumes, greater GMD, lower MD, lower CBF, higher ALFF and ReHo, and greater activation for the working memory task in PFIT regions. However, additional cortical, striatal, limbic, and cerebellar regions showed comparable effects, hence PFIT needs expansion into an extended PFIT (ExtPFIT) network incorporating nodes that support motivation and affect. Associations of brain parameters became stronger with advancing age group from childhood to adolescence to young adulthood, effects occurring earlier in females. This ExtPFIT network is developmentally fine-tuned, optimizing abundance and integrity of neural tissue while maintaining a low resting energy state.
Publisher OA PDF DOI
Leveraging multi-shell diffusion for studies of brain development in youth and young adulthood
Developmental Cognitive Neuroscience · 2020 · 93 citations
Senior authorCorresponding
- Artificial Intelligence
- Computer Science
- Psychology
Diffusion weighted imaging (DWI) has advanced our understanding of brain microstructure evolution over development. Recently, the use of multi-shell diffusion imaging sequences has coincided with advances in modeling the diffusion signal, such as Neurite Orientation Dispersion and Density Imaging (NODDI) and Laplacian-regularized Mean Apparent Propagator MRI (MAPL). However, the relative utility of recently-developed diffusion models for understanding brain maturation remains sparsely investigated. Additionally, despite evidence that motion artifact is a major confound for studies of development, the vulnerability of metrics derived from contemporary models to in-scanner motion has not been described. Accordingly, in a sample of 120 youth and young adults (ages 12-30) we evaluated metrics derived from diffusion tensor imaging (DTI), NODDI, and MAPL for associations with age and in-scanner head motion at multiple scales. Specifically, we examined mean white matter values, white matter tracts, white matter voxels, and connections in structural brain networks. Our results revealed that multi-shell diffusion imaging data can be leveraged to robustly characterize neurodevelopment, and demonstrate stronger age effects than equivalent single-shell data. Additionally, MAPL-derived metrics were less sensitive to the confounding effects of head motion. Our findings suggest that multi-shell imaging data and contemporary modeling techniques confer important advantages for studies of neurodevelopment.
Publisher DOI