Theodore Daniel Satterthwaite

The paper compares five algorithms for deriving structural covariance networks in the thalamocortical system and finds they emphasize different neurobiological aspects based on their mathematical properties.

This study examines insula functional connectivity development across 562 individuals, showing spatially heterogeneous changes aligned with an antero-posterior axis.

The paper introduces a multimodal MRI dataset to evaluate myelin-sensitive imaging methods across test-retest acquisitions and metrics.

The paper shows aging and Alzheimer's disease alter distinct functional connectivity axes in the brain, with AD affecting the sensory-association axis and aging affecting the representation-executive axis.

Resting-state fMRI intrinsic timescale lengthens with age in association, not sensorimotor, cortex during ages 8-22, following the sensorimotor-association axis in two cohorts; it is largely age-stable in young adults.

This paper introduces the R-ratio to quantify the balance between local and distributed excitation in the brain, showing it increases with aging and Alzheimer's disease.

The paper introduces a statistical test to detect confounding effects in multimodal neuroimaging data by assessing covariate influences on intermodal correspondence.

This paper introduces brain age intervals (BAIs) as a method to quantify uncertainty in brain age predictions using conformal prediction, showing stable coverage and highlighting the need for larger samples.

The paper shows that white matter tracts are positioned within the cortical hierarchy to support specific cognitive functions and connect regions with greater cognitive diversity.

The paper identifies shared dimensions of variation in diffusion MRI statistics and maps spatial patterns of microstructural similarity across the brain.

The paper introduces a longitudinal data resource combining multimodal imaging and cognitive phenotyping to study brain development and EF variation in adolescents.

This study examines how childhood adversity affects structure-function coupling in corticolimbic circuits and its role in buffering internalizing symptoms during development.

The paper identifies two neuroanatomical subtypes of callous-unemotional traits using machine learning in a community sample of youth, showing distinct clinical and environmental profiles.

The paper uses neuroimaging data to study how plasticity in language-related brain regions changes across early childhood, finding distinct patterns of development in different brain areas.

This study evaluates transdiagnostic latent factor models for brain-psychopathology associations using neuroimaging data, finding no consistent improvement in predictive utility over summary scores.

This study links childhood environmental exposures to white matter structure in children, showing that advantaged environments correlate with larger white matter tracts and reduced orientation dispersion.

The paper presents a curated dataset of processed diffusion MRI data from the ABCD Study, showing that specific diffusion metrics are sensitive to adolescent white matter development and robust to image quality variation.

The paper introduces an open data resource combining neuroimaging and behavioral measures to study mood and sleep in adolescents and young adults.

This study identifies two axes of white matter development in human cortico-cortical tracts using diffusion MRI across three datasets, revealing non-uniform maturation patterns.

This study identifies subtypes of functional connectivity development in youth using fMRI data, revealing spatial patterns linked to cognitive performance and gene expression.

This study examines how spatiotemporal brain activity propagations change from childhood to early adulthood, finding that certain propagation patterns become more prevalent with age and correlate with cognitive performance.

This paper introduces ReForm, a method to calibrate MRI-based reference intervals for new samples without sharing reference data, showing comparable or better false positive rate control than alternative methods.

The paper introduces conditional-longitudinal models to analyze brain growth trajectories and finds associations between birth weight, psychopathology, and brain volume changes in adolescents.

The paper describes improvements in diffusion MRI processing for the HBCD study, introducing new software and observing developmental patterns in brain data.

This study introduces an interpretable predictive model to identify functional connectivity patterns predictive of cognitive traits in youth, showing improved accuracy and fine-grained characterization.

The paper uses deep learning to identify brain-behavior dimensions and biotypes in youth with ADHD and anxiety disorders, revealing distinct symptom profiles and brain development patterns.

The paper introduces a scalable toolkit for 3D surface-based brain analysis, demonstrating its utility in mapping subcortical shape variations across 21 international samples.

This study identifies small but consistent anatomical correlates of negative symptom dimensions in schizophrenia, linking them to prefrontal cortical thickness and limbic subcortical volumes.

The paper introduces Reproducible Brain Charts (RBC), an open data resource integrating brain development data from 6,346 youth, showing the benefits of harmonized phenotypes and reproducible processing for studying psychopathology.

This paper evaluates ODF reconstruction methods for single-shell dMRI, finding SS3T provides reliable and predictive WM bundle segmentation with lower angular resolution data.