Xuhong Liao

The paper uses an intrinsic ignition framework to analyze resting-state fMRI data and reveals hierarchical propagation pathways of spontaneous activity in the human brain, linking local events to global patterns and behavioral traits.

The paper analyzes functional and structural MRI data from 33,250 individuals to map lifespan changes in the functional connectome, identifying key developmental stages and differences in neurological disorders.

This study investigates how multiscale structural brain gradients develop from childhood to adolescence and links these changes to cortical morphology and functional specialization.

This study investigates how overlapping functional modules in the developing human brain change with age and their structural correlates using multimodal MRI data.

This study examines neonatal brain connectome dynamics using resting-state fMRI and finds that these dynamics predict cognitive and language outcomes at age 2.

The paper maps cortical thinning patterns during childhood to adolescence, showing they are structurally constrained by white matter networks and linked to gene expression signatures.

The paper models the interdependent structural and functional connectome in the human brain, finding topographic heterogeneity and cognitive significance.

This paper identifies a dual long-axis organization in the human hippocampus during youth, showing its role in cortical hierarchy maturation and functional reorganization.

This paper introduces 3D-MASNet, a 3D mixed-scale asymmetric convolutional network for segmenting infant brain MR images, achieving high Dice coefficients in GM, WM, and CSF.

The paper investigates how structural and functional brain connectome variability are structurally constrained and finds a hierarchical relationship between primary and heteromodal brain regions.

This study tracks the development of a primary-to-transmodal gradient in the brain from childhood to adolescence, linking it to cognitive functions and gene expression.

This study identifies altered brain network dynamics and associated transcriptomic signatures in autism spectrum disorder using resting-state fMRI and postmortem gene expression data from the ABIDE dataset.

The paper identifies consistent and reproducible functional connectome hubs in the human brain using meta-connectomic analysis and links them to specific transcriptomic patterns.

The paper compares word computation mechanisms using fMRI data to determine which models best explain neural activity patterns related to language processing.

The paper examines the longitudinal development of brain network dynamics during childhood and adolescence, linking changes to gene expression profiles and ion transport-related genes.

This study identifies transcriptional signatures associated with the hierarchical organization of dynamic brain networks using fMRI and gene expression data.

The paper creates age-appropriate structural brain atlases for Chinese children using MRI data and shows they improve brain age prediction compared to Western-based atlases.