Ruben C. Gur

Generalizable sex differences in functional brain organization follow the cortical hierarchy in youth

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.

Insula functional connectivity development follows a canonical antero-posterior axis of organization

This study examines insula functional connectivity development across 562 individuals, showing spatially heterogeneous changes aligned with an antero-posterior axis.

A founder population reveals genetic variation with major effect on serious mental illness

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

Analysis of Rare Coding Variation Identifies New Genetic Contributors to Schizophrenia

Ultra-rare damaging coding variants in 87,959 schizophrenia cases and 150,587 controls implicate 40 genes (16 exome-wide, 24 at 5% FDR), half overlapping autism, developmental delay or bipolar genes.

Effect of ancestry and shared genetic architecture of serious mental illness on symptoms and cognition in an admixed Latin American population

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.

An open, fully-processed data resource for studying mood and sleep variability in the developing brain

The paper introduces an open data resource combining neuroimaging and behavioral measures to study mood and sleep in adolescents and young adults.

Spatial Heterogeneity and Subtypes of Functional Connectivity Development in Youth

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

Neuroanatomical Correlates of Negative Symptoms in Schizophrenia

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

Reproducible Brain Charts: An open data resource for mapping brain development and its associations with mental health

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.

Benchmarking Orientation Distribution Function Estimation Methods for Tractometry in Single-Shell Diffusion Magnetic Resonance Imaging - An Evaluation of Test-Retest Reliability and Predictive Capability

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

A cross-disorder analysis of CNVs finds novel loci and dose-dependent relationships of genes to psychiatric traits

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

Mapping individualized multi-scale hierarchical brain functional networks from fMRI by self-supervised deep learning

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.

Optimizing Biophysical Large-Scale Brain Circuit Models With Deep Neural Networks

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.

Mapping individual differences in intermodal coupling in neurodevelopment

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

Sex differences in deep brain shape and asymmetry persist across schizophrenia and healthy individuals: A meta-analysis from the ENIGMA-Schizophrenia Working Group

Regression and Alignment for Functional Data and Network Topology

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.

Brain-Age Prediction: Systematic Evaluation of Site Effects, and Sample Age Range and Size

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.

A sensorimotor-association axis of thalamocortical connection development

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

Network Enrichment Significance Testing in Brain-Phenotype Association Studies

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

Development of White Matter Fiber Covariance Networks Supports Executive Function in Youth

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

Similarity-Based Multimodal Regression

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.

Using network control theory to study the dynamics of the structural connectome

This paper introduces a framework for applying network control theory to the human structural connectome to study neural dynamics and control energy, controllability, and their correlations with behavior and mental health.

In-vivo whole-cortex estimation of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth

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.

Computing personalized brain functional networks from fMRI using self-supervised deep learning

This paper develops a self-supervised deep learning method to compute personalized brain functional networks from fMRI data, showing it can identify canonical networks and predict individual differences in behavior and schizophrenia status.

Normative Modeling of Brain Morphometry Across the Lifespan using CentileBrain: Algorithm Benchmarking and Model Optimization

The paper benchmarks and optimizes a normative modeling framework for brain morphometry across the lifespan using MFPR, showing excellent accuracy and stability.

Individual Differences in Delay Discounting are Associated with Dorsal Prefrontal Cortex Connectivity in Youth

This study links individual differences in delay discounting to specific patterns of dorsal prefrontal cortex connectivity in youth using resting-state fMRI.

Asymmetric Signaling Across the Hierarchy of Cytoarchitecture within the Human Connectome

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.

Compression supports low-dimensional representations of behavior across neural circuits

The paper uses network theory to predict compression levels in neural circuits and finds differences in dimensionality and representational capacity across brain regions and behaviors.

Spatially-enhanced clusterwise inference for testing and localizing intermodal correspondence

The paper introduces CLEAN-R, a method to test and localize intermodal correspondence in neuroimaging data, demonstrating high statistical power and nominal type I error levels.

Curation of BIDS (CuBIDS): a workflow and software package for streamlining reproducible curation of large BIDS datasets

CuBIDS streamlines reproducible curation of large BIDS datasets by validating metadata, managing variability, and preparing data for preprocessing pipelines.