Joseph Biederman

This study analyzes structural brain asymmetries in ADHD using 39 datasets, finding small effects that do not meet study-wide significance thresholds.

The paper develops a functional brain network model to predict stimulus-independent, task-unrelated thought across different populations and contexts.

This study uses machine learning to show that structural brain anomalies in ADHD are similar in children and adults, supporting continuity of the disorder's pathophysiology.

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 study investigates genetic mechanisms underlying sex bias in ADHD prevalence using genome-wide data and finds no mean polygenic burden difference across sexes but increased risk in female siblings and comorbid conditions.