Anthony C. James

This study identifies white matter microstructural alterations in adult OCD patients and links them to clinical features, while finding no such abnormalities in pediatric patients.

The paper analyzes cortical thickness trajectories in 17,075 individuals to show peak thickness in childhood, steep decline in early adulthood, and slower decline later, with notable exceptions and significant inter-individual variability.

The paper evaluates the ComBat method for multi-site diffusion MRI harmonization, finding that it preserves biological variability in some sites but not others and is sensitive to preprocessing differences.

The paper analyzes sex differences in brain structure variability across the lifespan using a large dataset, finding greater male variability in subcortical volumes, cortical surface area, and thickness in most regions.

This study compares proteomic profiles of olfactory cells from adolescent- and adult-onset schizophrenia patients, finding similar downregulation of ribosomal proteins and mTOR pathway components.

This study analyzes subcortical volume changes across the lifespan using MRI data from 18,605 individuals, finding age-related declines in some structures and increases in others.

This study examines structural brain connectivity differences in pediatric bipolar disorder with psychosis compared to healthy controls, finding widespread network topology changes and correlations with cognitive and psychotic symptoms.

This study compares structural brain differences across ADHD, ASD, and OCD using MRI data from multiple cohorts, finding disorder-specific alterations in brain volume and cortical thickness.

This paper presents a diffusion MRI harmonization method that removes scanner-specific effects across sites while preserving inter-subject variability, validated on two clinical cohorts.

The paper develops deep learning models to assess the quality of subcortical brain shape models from MRI, reducing human rater time by 46-70%.

This work uses machine learning to automate quality control of 3D brain shape models, reducing human workload by 30-70% across multiple datasets and diseases.