Seok‐Jun Hong

This study identifies distinct subcortical-cortical circuit disruptions in autism and ADHD using functional connectivity and dynamic causal modeling in a multi-site cohort.

This study introduces a neuroimaging framework to discover state-dependent signal flow hierarchy in the human cerebral cortex using integrated effective connectivity and signal flow mapping.

This study examines thalamo-cortical and thalamo-hippocampal functional connectivity in temporal lobe epilepsy, finding reduced connectivity in TLE patients and its association with seizure generalization and surgical outcomes.

This study examines how spatiotemporal brain activity propagations change from childhood to early adulthood, finding that certain propagation patterns become more prevalent with age and correlate with cognitive performance.

This study introduces Relative Phase Analysis to reveal sub-second switches between top-down and bottom-up brain modes, showing distinct dynamics in consciousness and ADHD.

The paper identifies brain mediators involved in integrating predictive cues with noxious inputs to modulate pain over time using temporal mediation analysis.

This study finds reduced cortex-wide connectivity distance in ASD, indicating shorter average connection length and increased short-range connectivity, particularly in transmodal brain systems.

The paper identifies three ASD subtypes using morphometric similarity networks and finds distinct transcriptomic and functional connectome patterns associated with each subtype.

This study shows that pharmaco-resistant temporal lobe epilepsy causes a progressive shift in cortical excitation-inhibition balance, linked to cognitive impairments and seizure frequency.

This study examines how thalamocortical connectivity changes with age and contributes to the development of large-scale functional brain networks from infancy to young adulthood.

The paper investigates structural connectome asymmetry in autism, finding atypical asymmetry in specific brain networks and associations with communication symptoms and intelligence.

This study uses multimodal imaging and connectivity modeling to show that polysynaptic mechanisms are implicated in autism spectrum disorder, with reduced structure-function coupling in transmodal networks.

This study examines functional asymmetry in autism, finding reduced leftward asymmetry in language networks and altered developmental trajectories of functional lateralization.

This study shows that social and interoceptive mental training leads to changes in brain function and microstructure, which predict behavioral improvements in attention and empathy.

The paper presents a whole-brain 3D myeloarchitectonic atlas based on historical histological data, validated with MRI markers and integrated into neuroimaging software.

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

The paper identifies three subgroups of eating behavior traits independent of obesity using functional connectivity and autoencoder-based feature representation in healthy adults.

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.

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

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 identifies subtypes of school-aged children based on brain structure and environmental factors using Similarity Network Fusion, revealing distinct associations between environments and neurodevelopment.

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

This paper introduces a function-based method to align cortical organization across species, revealing evolutionary changes in brain regions associated with human cognition.

This paper evaluates the reliability, reproducibility, and predictive validity of functional connectivity gradients in fMRI data across different analytical settings.

This study shows that schizophrenia is associated with a compressed cortical hierarchy organization, reducing the separation between sensory and cognitive systems.

BrainSpace provides a toolbox for analyzing macroscale gradients in neuroimaging and connectomics data, enabling gradient identification, alignment, visualization, and association studies.

The paper identifies a dissociation between microstructural and functional gradients in transmodal brain networks using histological and MRI data.