F. Xavier Castellanos

The paper identifies a topographic organization of mental imagery in the human parietal cortex, showing modality-specific regions and a central hub for multisensory imagery.

This study uses naturalistic fMRI to explore social brain differences in ASD, finding unique amygdala signatures and shared prefrontal deficits linked to symptom severity.

The paper identifies sgACC functional connectivity abnormalities in depression using large-scale brain imaging data and develops an individualized TMS targeting algorithm to improve treatment outcomes.

The paper introduces a longitudinal dataset of school-age children and adolescents in China, detailing its design, sampling, and neuroimaging measurements.

This paper develops a deep learning classifier for Alzheimer's disease using brain MRI data from 85,721 scans, achieving high accuracy across multiple independent datasets.

The paper examines factors predicting successful MRI data acquisition in children with neurodevelopmental conditions after simulator training, finding age and sensorimotor atypicalities as key predictors.

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

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.

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.

DREAM is a toolbox for decoding brain rhythms that analyzes neural and neurobehavioral oscillations, revealing age and sex differences in head motion and frequency-specific reliability of neural oscillations.

This study examines the stability and similarity of the pediatric connectome across different states and tasks, finding correlations with social skills but not age.

This paper evaluates test-retest reliability of multilayer network measures in neuroimaging, identifying methodological factors affecting reliability and task-specific requirements.

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.

The paper develops a pipeline to generate age-specific MRI brain templates and growth charts for children and adolescents, revealing neurodevelopmental differences between Chinese and US populations.

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 paper quantifies covariation patterns in cortical and subcortical brain shape measures and shows they can predict age, sex, and cognitive ability with high accuracy.

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 shows that Nf1 loss-of-function disrupts corticocortical and corticostriatal functional connectivity in both human NF1 patients and Nf1+/- mice.

The paper analyzes resting-state fMRI data from 1,300 MDD patients and 1,128 controls to find reduced default mode network functional connectivity in recurrent MDD, not first-episode MDD.

The paper introduces a method to estimate relative brain iron concentrations using functional MRI, showing good correspondence with formal iron imaging and providing insights into brain iron and cognition across the lifespan.

The paper assesses the impact of shared data on scientific literature using a brain imaging case study, showing increased publication rates and broader scientific collaboration.

The paper introduces the Healthy Brain Network (HBN) biobank, a large-scale multimodal dataset for pediatric mental health and learning disorders research, with initial data release.

This paper compares functional connectivity variability during movies and rest, finding movies enhance individual differences detection.

The paper describes a repository of fMRI data assessing inter-individual differences in default mode network activity and reports technical validation of the dataset.