Mark A. Elliott

The PMADS Project tracks neurobiological and clinical changes in high-risk individuals across the perinatal period to identify biomarkers linking brain plasticity to PMADs risk.

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

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

This study measures NAD+ T1 and T2 relaxation times in human brain using 7 T 1H MRS and quantifies the uncertainty propagation in NAD+ concentration.

This study evaluates head motion correction methods in diffusion MRI, showing both Eddy and SHORELine perform well but are affected by denoising and sampling schemes.

This study shows that brain MRI volumetric biases persist across different scanners in a harmonized MS study, with site explaining over 50% of volume variation.

The paper uses GluCEST MRI to detect glutamate concentration changes in the motor cortex after cTBS, finding decreased ipsilateral signal but no consistent contralateral or sham effects.

FlywheelTools provides software for reproducible data curation and manipulation on the Flywheel platform, addressing challenges in converting neuroimaging data to BIDS format.

The paper examines how different psychopathology dimensions affect various scales of brain functional connectivity using multiple modeling approaches.

The paper shows that reduced value signals in the ventromedial prefrontal cortex are linked to motivational and hedonic deficits across mood and psychotic disorders.

QSIPrep is a software platform for preprocessing diffusion MRI data that supports multiple sampling schemes and ensures reproducibility through standardized workflows and quality measures.

The study replicates and extends the Parieto-Frontal Integration Theory (PFIT) in youths, showing age-related strengthening of brain parameter-cognitive performance associations and suggesting an expanded network incorporating motivation and affect regions.

This study evaluates DTI, NODDI, and MAPL in youth to assess their associations with age and motion, finding that multi-shell models offer advantages for neurodevelopmental studies despite motion sensitivity.

This study uses combined fMRI and TMS to map causal brain networks involving the sgACC and amygdala, showing individualized targeting captures causal circuitry in humans.

This study links accelerated cortical thinning in structural brain networks to irritability in youth, highlighting associations in emotion-related brain regions.

The paper investigates how brain iron levels in youth relate to cognitive performance and socioeconomic status, hypothesizing that higher iron in basal ganglia regions mediates this relationship.

The paper develops an automated method to assess structural brain image quality using Euler number and validates its effectiveness in identifying low-quality images and its relationship with cortical thickness and age-related associations.

The paper constructs a multifactorial model of white matter connectivity during adolescence using Bayesian networks and diffusion imaging data, showing that architectural specifications become more influential with age.

This paper shows that diffusion tensor imaging data are site-specific and demonstrates that ComBat effectively harmonizes them while preserving biological variability.