Raquel E. Gur

The paper examines sex differences in functional brain connectivity across youth, finding that males show greater network integration while females show greater network segregation along the sensorimotor-association axis.

This study investigates olfactory deficits and structural anomalies in the olfactory system among individuals with 22q11.2 deletion syndrome compared to psychosis spectrum and typically developing controls.

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

The paper maps phenotypic and genetic links between plasma proteins and organ imaging traits using UK Biobank data, identifying associations and causal links across multiple organs.

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.

The paper examines how gene dosage, polygenic background, and environment influence complex traits like height and BMI using large-scale data from multiple cohorts.

This study identifies two axes of white matter development in human cortico-cortical tracts using diffusion MRI across three datasets, revealing non-uniform maturation patterns.

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

This study identifies small but consistent anatomical correlates of negative symptom dimensions in schizophrenia, linking them to prefrontal cortical thickness and limbic subcortical volumes.

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 study identifies shared genetic loci between psychiatric disorders and cortical brain structure using genome-wide association data from over 700,000 individuals.

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 identifies novel CNV loci and dose-dependent gene effects across six psychiatric disorders using genome-wide analysis.

The paper investigates organ-specific and modality-specific aging clocks using proteomic and imaging data, revealing distinct biological processes and their roles in age-related diseases.

This paper introduces a self-supervised deep learning framework to compute individualized multi-scale hierarchical functional networks from fMRI data and shows their association with biological phenotypes.

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 introduces CEIDR, a method to test individual differences in intermodal brain coupling, and demonstrates its application in neurodevelopmental studies.

This paper introduces a method to analyze functional brain networks by treating network diagnostics as functions of parameters, enabling regression and alignment with cognitive performance measures.

The paper evaluates factors affecting brain-age prediction models using structural neuroimaging data from 35,683 individuals, finding optimal model performance with no site harmonization, age-binning, and a sample size of over 1,600.

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

The paper introduces NEST, a framework for testing brain-phenotype associations within functional networks, applied to neurodevelopmental imaging data.

The paper examines how functional connectivity develops along the sensorimotor-association axis during childhood to adolescence, finding that sensorimotor connectivity increases while association connectivity decreases, reinforcing cortical hierarchy.

This study investigates how structural brain alterations in schizophrenia relate to network architecture, finding hub susceptibility and shared epicenters across disease stages and disorders.

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

This paper introduces a distance-based regression method for multimodal data that can handle different data types and dimensionalities, showing its effectiveness through simulations and real-world studies.

This study identifies 928 genes associated with brain weight variation across three datasets and links them to neurodevelopmental processes and brain function.