Youngheun Jo

The paper identifies social envirotypes in the ABCD study, showing they are associated with distinct brain connectivity patterns and diverging developmental outcomes.

The paper analyzes high-amplitude events in edge time series across the human lifespan, finding age-related changes in their patterns and associations with cognitive phenotypes.

This study identifies age-related changes in brain network organization using edge communities from resting state fMRI data across the human lifespan.

This study identifies bursty dynamics and modular subgraphs in mouse and human brain networks, showing cross-species consistency in co-fluctuation patterns and anatomical connectivity.

The paper investigates cortico-subcortical interactions using edge communities and finds distinct coupling patterns between subcortical regions and cortical systems.

The paper analyzes edge communities in brain networks using the Midnight Scan Club dataset, showing they transcend traditional brain systems and reveal personalized patterns.

The paper develops an edge-centric functional connectivity model to identify subject-specific features across different spatial scales and shows improved identifiability over traditional nodal FC.

The paper introduces an edge-centric network model to analyze brain connectivity, showing that edge functional connectivity is consistent across datasets and modulated by sensory input.

The paper decomposes resting-state functional connectivity to show that high-amplitude activity frames drive most of the variance in connectivity patterns and modular structure.