Boris C. Bernhardt

This paper predicts brain function from the structural connectome using a Riemannian approach based on diffusion maps and random walks, showing performance plateaus around the third walk.

The paper examines how genetic and phylogenetic factors influence structure-function coupling in the human transmodal cortex and finds reduced genetic control in regions linked to social cognition and memory.

This study identifies a structure-function substrate of cognitive imbalances in autism using multi-site neuroimaging data and dimensional analysis.

This study shows that LSD and psilocybin reduce hierarchical cortical organization by flattening connectivity gradients, supporting a mechanistic model of the psychedelic state.

The paper investigates how mind-wandering during reading affects neural coupling between the default mode network and visual regions, showing that decoupling impairs comprehension.

The paper examines hemispheric asymmetry in structural covariance networks in ASD across 43 datasets, finding altered topological features in specific brain regions.

This study examines age-related changes in brain functional architecture using multi-scale fMRI analyses in younger and older adults, finding both global and network-specific dedifferentiation patterns.

BrainStat provides a toolbox for statistical analysis and feature association in neuroimaging data, integrating multiple modalities and templates to enhance cross-modal research.

This study identifies shared and distinct structural brain differences in children with autism and anxiety, using neuroimaging data from 82 participants.

This study characterizes the anatomy of the human default mode network using histology and neuroimaging, revealing its cytoarchitectural diversity and unique signal flow properties.

This study identifies divergent patterns of atypical cortical asymmetry and regional atrophy in temporal lobe epilepsy using MRI data from a large multi-site cohort.

The paper investigates how long-range brain connections relate to microarchitectural and cognitive hierarchies in the human brain, finding that transmodal association cortices have distributed long-range connections linked to similar microarchitecture.

This study links structural network changes in epilepsy syndromes to risk gene expression patterns using ENIGMA data.

This study identifies hemispheric differences in a principal gradient of brain connectivity and links these differences to semantic cognition and visual reasoning.

The paper examines how cortico-cortical networks mediate localized and global communication by analyzing the functional connectivity of unimodal and multimodal brain regions across multiple scales.

BigBrainWarp simplifies integration of BigBrain histology with neuroimaging by providing tools for registration and cytoarchitectural feature access.

This study examines structural and functional brain network development in adolescents, finding that structural wiring changes correlate with functional differentiation.

The paper identifies microglial activation as a factor contributing to cortical thinning in epilepsy by integrating neuroimaging and gene expression data.

The paper introduces the ENIGMA Toolbox, a Python/Matlab ecosystem for integrating multisite neuroimaging datasets across disorders and contextualizing findings at multiple scales.

The paper investigates how social, personality, and demographic factors influence brain structure in midlife using UK Biobank data.

This study quantifies how population diversity affects brain-imaging prediction accuracy and pattern stability using two clinical cohorts.

The paper examines how BMI variations relate to functional brain organization by analyzing connectome structure in healthy young adults, finding increased segregation and disrupted hierarchy in higher BMI individuals.

The paper combines connectome analysis and computational models to show autism has altered subcortico-cortical interactions linked to microcircuit and macroscale network anomalies.

The paper uses manifold learning to analyze longitudinal structural connectome data, showing expansion in transmodal regions during adolescence and linking it to cognitive outcomes.

The paper introduces a new spatial memory task and shows its correlation with structural and functional brain differences in temporal cortices.

This study shows that fast oscillations >40Hz detected with high-density EEG can accurately localize the epileptogenic zone, outperforming conventional EEG methods.

This study identifies higher functional network idiosyncrasy in ASD compared to TD, linked to ASD risk genes and symptom severity.

This paper provides a voxel-level description of the directed mouse connectome, revealing hierarchical structure and functional organization.

The paper identifies two topographic gradients of intrinsic brain dynamics across the neocortex, linked to cognitive and functional processing patterns.

This study identifies two distinct neural states during wakeful rest using machine learning and links them to specific psychological features like problem-solving and negative rumination.