Damien A. Fair

This study compares functional brain network estimation using resting state crosshair fixation and movie watching in adolescents, finding similar network topography with minor border shifts.

The paper analyzes age-related changes in neurometabolite concentrations in infants using 1H-MRS data from the HBCD study, finding significant increases in some metabolites and decreases in others.

This paper introduces PCM, a method to assess network assignment confidence in rs-fMRI data, improving precision with limited scan durations.

The paper develops an age-appropriate functional reference to estimate individualized brain networks in young children, revealing early network organization and stability.

This study evaluates deep learning models for predicting task activation from resting-state fMRI, finding that architectural changes improve efficiency without sacrificing accuracy.

The paper links socioeconomic status (SES) to brain-wide associations, showing SES has stronger associations with brain structure and function than IQ or psychopathology.

This study examines hippocampal subregion development in early life and links growth patterns to school-aged episodic memory performance.

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 identifies parallel processing chains in association cortex using multiple functional mapping modalities, showing they are experience-driven and organized across different cytoarchitectures.

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 identifies menarche as an inflection point for mental health and brain development in adolescent females using longitudinal data.

This study compares brain network organization during resting state and executive function tasks, finding task-evoked networks show new and strengthened relationships with executive function ability in children.

BIBSNet is a deep learning model for infant brain segmentation in MRI scans that outperforms JLF in accuracy and speed, with compatible outputs for further analysis.

This study predicts adolescent substance use facets using resting-state connectivity, finding improved prediction accuracy over time with different facets being predicted at baseline and follow-up.

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 distinct cortical thickness and curvature patterns in autism and ADHD using harmonized, large-scale brain imaging data.

The paper estimates heritability of subcortical brain volumes in adolescents using a multi-site cohort, finding high heritability in cerebellum cortex and hippocampus.

The paper introduces dGAMLSS, a distributed algorithm for fitting GAMLSS models to construct population reference charts without sharing patient data.

The paper uses functional MRI to map cortical areas in neonates, finding that their arrangement is individually specific and reliably identifiable.

This study shows stimulant medications affect brain connectivity in action/motor and reward-related regions, not attention networks, and mimic the effects of sleep.

The paper demonstrates the feasibility of precision functional imaging in infants to identify individual-specific auditory responses and their relation to brain functional networks.

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

This paper demonstrates that 7T MRI improves spatial resolution and data quality for functional brain mapping in infants compared to 3T MRI, enabling more reliable developmental studies.

This paper validates data-driven factor models over RDoC-based models using fMRI and behavioral data, showing better reproducibility and clinical relevance across neural and behavioral domains.

The paper introduces SHAMAN, a method to assess motion impact on brain-behavior associations in fMRI studies, finding significant motion overestimation and underestimation in various traits.

This study estimates the heritability of functional brain networks in adolescents using SNP and twin data from the ABCD study, finding low genetic contributions.

This study identifies two ASD subgroups with distinct brain morphology using cross-cultural datasets, highlighting key brain regions associated with subgroup characteristics and autistic traits.

The paper extends fMRIPrep to handle MRI data from infancy to old age, demonstrating high-quality preprocessing across a wide age range.

This study parcellates the cerebral cortex in toddlers using functional connectivity and shows high reproducibility across ages, with area boundaries more similar to adults than neonates.

This study identifies infant brain areas with adult-like functional network organization, showing less age-related variation and higher reliability, and suggests implications for using adult network models in infants.