Zening Fu

From micro-architecture to networks: canonical neurobiological architecture of functional brain organization across the lifespan and in psychopathology

The paper links functional brain network connectivity across age and psychiatric disorders to neurobiological microprofiles, showing stage-specific associations.

NeuroMark dFNC: Transferable Dynamic-State Templates for Subject-Specific and Frequency-Resolved Chronnectomics

NeuroMark dFNC uses reference-state templates to estimate subject-specific dynamic connectivity states across datasets, enabling cross-cohort comparison while preserving individual patterns.

Directional coordination along the cortical hierarchy is selectively reorganized in schizophrenia

This study identifies a dynamic directional coordination axis in the cortical hierarchy that is selectively reorganized in schizophrenia, linked to symptoms and cognition.

Mapping the Psychosis Spectrum -- Imaging Neurosubtypes from Multi-Scale Functional Network Connectivity

This study identifies three psychosis neurosubtypes using imaging data, showing distinct connectivity patterns and supporting their biological validity through relative alignment.

Comparing Nonlinear Trajectories Across Brain Networks: A Key to Understanding Complex Brain Dynamics

This study analyzes nonlinear developmental trajectories of brain networks in infants using a cubic model, revealing network-specific growth patterns and interactions.

NeuroMark-SZ: A Holistic Resting-State-fMRI-Based Model for Divergent Functional Circuitry in Schizophrenia

This paper develops a model using resting-state fMRI to identify functional connectivity patterns in schizophrenia, finding a robust cerebellothalamic disruption signature.

Robustness of NeuroMark-Derived Functional Networks to fMRI Spatial Normalization Across the Human Lifespan

This study evaluates the robustness of NeuroMark-derived functional networks to fMRI spatial normalization across different age groups, finding high stability regardless of normalization strategy.

DECODING BRAIN DYNAMICS VIA CROSS-NETWORK NON-LINEAR TRAJECTORIES

The paper introduces CNTC to analyze nonlinear developmental trajectories across brain networks using fMRI data from infants, finding linear and selective nonlinear effects across systems.

Dynamic fusion of genomics and functional network connectivity in UK biobank reveals static and time-varying SNP manifolds

Explicitly nonlinear fMRI networks reveal hidden trajectories of infant brain development

This study uses explicitly nonlinear fMRI connectivity to uncover developmental trajectories of brain networks in infants, revealing insights into key functional systems.

Deciphering Multiway Multiscale Brain Network Connectivity:Insights from Birth to 6 Months

This study investigates multiway, multiscale brain network interactions in infants, finding that tri-FNC provide additional insights beyond pairwise interactions during early brain development.

Brain functional network connectivity interpolation characterizes the neuropsychiatric continuum and heterogeneity

This paper introduces a variational autoencoder framework to interpolate functional network connectivity data across neuropsychiatric disorders, revealing continuous gradients and heterogeneity.

SPATIAL DISSIMILARITY TRAJECTORIES REVEAL RAPID FUNCTIONAL NETWORK REFINEMENT DURING EARLY INFANCY

This study shows that spatial brain network organization becomes more coherent with age in infants, using fMRI data and spatial dissimilarity metrics.

Spatial Development of Brain Networks During The First Six Postnatal Months

This study examines spatial changes in infant brain networks using resting-state fMRI data from 74 infants, revealing age-related patterns in network organization and intensity distribution.

PhaseICA: Resolving Individual-Specific Macroscale Brain Propagations

PhaseICA extracts reoccurring spatiotemporal brain patterns by incorporating phase information, improving the analysis of nonstationary brain activity.

Building Multivariate Molecular Imaging Brain Atlases Using the NeuroMark PET Independent Component Analysis Framework

The paper introduces NeuroMark PET, an automated framework using spatially constrained ICA to identify Aβ networks in PET data, showing higher sensitivity for age-related changes compared to traditional ROIs.

Altered Functional Network Energy Across Multiscale Brain Networks in Preterm vs. Full-Term Subjects: Insights from the Adolescent Brain Cognitive Development (ABCD) Study

This study compares functional network energy across multiscale brain networks in preterm and full-term adolescents from the ABCD study, identifying differences in network stability and flexibility.

Mapping the Developmental Trajectory of Functional Brain Networks in Early Infancy: Insights into Typical Maturation

The paper maps functional brain network maturation in early infancy using resting-state fMRI, showing age-related increases in network consistency and engagement.

Analysis of Longitudinal Change Patterns in Developing Brain Using Functional and Structural Magnetic Resonance Imaging via Multimodal Fusion

The paper links functional change patterns to brain structure using multimodal fusion in adolescents, revealing sex-specific differences in neural dynamics.

aNy-way ICA and its application to estimate cortico-thalamo-cerebellar functional links in schizophrenia

This paper uses aNy-way ICA to identify a cortico-thalamo-cerebellar circuit in schizophrenia, showing altered connectivity and cognitive impairments across multiple datasets.

Spontaneous Brain Dynamics Associated With Acceleration Of Longterm Functional Connectome In Postnatal Development

This study links short-term brain dynamics to long-term changes in the functional connectome during postnatal development, finding a strong association between specific brain states and non-linear developmental acceleration.

Evidence for white matter intrinsic connectivity networks at rest and during a task: a large-scale study and templates

The paper presents a WM intrinsic connectivity network template derived from 100,000 fMRI scans, showing distinct WM and GM networks with task-related activity and differences in schizophrenia.

Born Connected: The Early Emergence of Adult-Like Multi-Scale Brain Networks in Infancy

This study identifies adult-like multi-scale brain networks in infants using rsfMRI, showing early emergence of functional connectivity patterns.

A Multimodal Vision Transformer for InterpretableFusion of Functional and Structural NeuroimagingData

This paper introduces a multimodal vision transformer (MultiViT) to classify schizophrenia using structural and functional MRI data, achieving higher accuracy than unimodal and existing multimodal methods.

4D DYNAMIC SPATIAL BRAIN NETWORKS AT REST LINKED TO COGNITION SHOW ATYPICAL VARIABILITY AND COUPLING IN SCHIZOPHRENIA

This study examines dynamic spatial brain networks in resting-state fMRI data, finding atypical variability and coupling in schizophrenia linked to cognitive impairment.

SpaDE: Semantic Locality Preserving Biclusteringfor Neuroimaging Data

SpaDE is a deep learning model for biclustering neuroimaging data that identifies coherent subject and feature subgroups with improved interpretability and performance over existing methods.

Multi-modal Spatial-modality Attentive Fusion for Studying Neuropsychiatric Disorders

This paper introduces a multi-modal AI model for schizophrenia classification using imaging and genetic data, achieving 94.10% accuracy and identifying key brain regions and genes associated with the disorder.

Replication and Refinement of Brain Age Model for adolescent development.

This paper refines a brain age model for adolescents, improving prediction accuracy and showing associations between brain age gap and cognitive abilities.

Gray Matters: An Efficient Vision Transformer GAN Framework for Predicting Functional Network Connectivity Biomarkers from Brain Structure

This paper introduces a generative deep learning framework to predict functional network connectivity biomarkers from brain structure using a modified vision transformer GAN.

Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and its Links to Genetic Risk

The paper develops a method to estimate time-resolved spatial networks and applies it to study sex-specific schizophrenia disruptions and their genetic links.