Tyler M. Moore

The paper identifies a founder variant in ADAP1 associated with increased risk of schizophrenia and bipolar disorder in a Colombian genetic isolate.

This study examines how early life adversity and air pollution interact to affect amygdala volumes and psychopathology symptoms in children.

The paper shows that white matter tracts are positioned within the cortical hierarchy to support specific cognitive functions and connect regions with greater cognitive diversity.

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 identifies shared dimensions of variation in diffusion MRI statistics and maps spatial patterns of microstructural similarity across the brain.

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

The paper examines how environmental exposures affect whole-brain functional connectivity and cognition in youth using machine learning and the ABCD Study data.

The paper identifies two neuroanatomical subtypes of callous-unemotional traits using machine learning in a community sample of youth, showing distinct clinical and environmental profiles.

This study examines the relationship between cannabis use, glutamate levels in the anterior cingulate cortex, and symptom severity across the psychosis spectrum using 7T proton magnetic resonance spectroscopy.

This study evaluates transdiagnostic latent factor models for brain-psychopathology associations using neuroimaging data, finding no consistent improvement in predictive utility over summary scores.

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 shows that European GWAS findings for serious mental illness and cognition are portable to an admixed Latin American population, associating genetic risk scores with multiple symptoms and cognitive traits.

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

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 subtypes of functional connectivity development in youth using fMRI data, revealing spatial patterns linked to cognitive performance and gene expression.

The paper introduces conditional-longitudinal models to analyze brain growth trajectories and finds associations between birth weight, psychopathology, and brain volume changes in adolescents.

The paper introduces Reproducible Brain Charts (RBC), an open data resource integrating brain development data from 6,346 youth, showing the benefits of harmonized phenotypes and reproducible processing for studying psychopathology.

This paper evaluates ODF reconstruction methods for single-shell dMRI, finding SS3T provides reliable and predictive WM bundle segmentation with lower angular resolution data.

This paper introduces DELSSOME, a deep learning framework that accelerates biophysical brain circuit model optimization, enabling faster parameter estimation and lifespan trajectory analysis of cortical E/I ratios.

The paper shows thalamocortical connections develop along a sensorimotor-association gradient in youth, linking structural connectivity to cortical plasticity and environmental sensitivity.

This study identifies copy number variants (CNVs) associated with child psychopathology and cognitive function using data from the ABCD study.

The paper investigates how an individual's exposome influences functional brain network organization and cognitive functioning in youth, finding that exposome factors predict cognitive performance better than neuroimaging data.

This study identifies white matter fiber covariance networks in youth, showing their development aligns with executive function and hierarchical cortical maturation patterns.

The paper estimates the whole-cortex excitation-inhibition ratio using fMRI and shows it declines during youth, with lower ratios linked to better cognitive performance in children.

The paper uses network control theory to show that bottom-up signaling across the sensory-fugal axis of the human connectome requires less energy than top-down signaling.

The paper shows that intrinsic brain activity decreases along a sensorimotor-association cortical axis during human development, with reduced activity in disadvantaged youth.

The paper introduces CoCoA, a statistical framework to estimate conditional correlations and association sizes, demonstrating its effectiveness in neurocognitive data analysis.

This study links individual mobility patterns to mood, sleep, and brain connectivity by identifying unique mobility footprints.

This study identifies genetic correlates of phenotypic heterogeneity in autism by analyzing common and de novo variants across core features and co-occurring disabilities.

The paper examines how individual differences in functional brain network topography relate to psychopathology dimensions in youth using machine learning and fMRI data.