Functional Brain Connectivity Studies

A conserved node degree-based backbone and flexible hub organization of brain connectome underlying naturalistic movie watching

The paper reveals a conserved network backbone and flexible hubs in the brain during movie watching, linking network organization to stimulus features.

CREB: Consistent Reference External Batch Harmonization

CREB improves fMRI data harmonization by learning site effects from training data, enabling safe application to new unseen data while preserving biological variance.

Arousal state alters brain network switching and moderates cognitive task performance

This study examines how arousal states affect brain network switching rates and their relationship with cognitive task performance using fMRI, EEG, and eye tracking.

Unified Multi-Cohort Harmonisation and Normative Modelling of Neuroimaging Data via Hierarchical GAMLSS

This paper introduces a hierarchical GAMLSS framework for harmonizing and modeling neuroimaging data across multiple cohorts, showing improved removal of cohort effects and preservation of biological signals.

Exploring Links between Brain Image-Derived Phenotypes and Accelerometer-Measured Physical Activity in the UK Biobank

The paper investigates the association between brain image-derived phenotypes and physical activity using UK Biobank data, finding a strong link between PA and functional connectivity with moderate predictive value for cardiometabolic diseases.

PaSTA: Fast parametric inference of significance for spatial associations between brain maps

PaSTA provides a fast and reliable method to assess the statistical significance of spatial associations between brain maps, improving false positive control and power in heterogeneous data.

Hormone-Dependent Microstates and the Reconfiguration of Resting-State Dynamics across the Menstrual Cycle

This study shows that hormone levels across the menstrual cycle affect brain activity patterns and predict psychological well-being.

Multi-task fMRI outperforms resting-state fMRI for revealing task-invariant organization of the human brain

This study shows that multi-task fMRI better predicts brain functional organization than resting-state fMRI across diverse tasks and datasets.

Modeling Multi-Modal Brain Connectomes for Brain Disorder Diagnosis via Graph Diffusion Optimal Transport Network

This paper introduces GDOT-Net, a graph diffusion optimal transport network that aligns structural and functional brain connectivity for improved diagnosis of neuropsychiatric disorders.

A normative reference for large-scale human brain dynamics across the lifespan

The paper establishes a normative reference for large-scale human brain dynamics using resting-state fMRI data from over 10,000 individuals, revealing systematic reorganization across development and ageing and disorder-specific deviations in mental health conditions.

Transformation and recombination of neural information in a brain network

The paper investigates how neural information is transformed and recombined across brain regions in rats using fMRI, finding dynamic changes in activity patterns and excitation/inhibition balance.

Individual-level metabolic connectivity captures cortical morphology and their coupling strengthens with age

Evolutionary Divergence of Structure-Function Coupling between Human and Macaque: Spatial Patterns and Transcriptomic Basis

This study compares structural-functional coupling patterns between human and macaque brains, finding species-specific differences linked to evolutionary adaptations in gene expression and cognitive function.

Functional connectome harmonics and dynamic connectivity maps of the preadolescent brain

The paper applies Functional Connectome Harmonics and Leading Eigenvector Dynamics Analysis to resting-state fMRI data from children to characterize preadolescent brain network organization.

From local motifs to global dynamical stability in the mouse brain connectome

The paper analyzes the mouse brain connectome to show that specific neuron connection patterns and modules contribute to global dynamical stability rather than optimal processing capacity.

Untamed: Unconstrained Tensor Decomposition and Graph Node Embedding for Cortical Parcellation

Untamed improves cortical parcellation by combining tensor decomposition and graph node embedding, producing spatially coherent regions aligned with functional networks.

Regional brain age deviations reveal divergent developmental pathways in youth

The paper uses brain age gaps to identify developmental trajectories in youth, finding distinct patterns in ADHD and cognitive profiles.

Controlling the human connectome with spatially diffuse input signals

This paper adapts network control theory to model spatially diffuse input signals in the human brain, showing reduced energy for state transitions and matching existing neurobiological maps.

Frequency-resolved cortical functional connectivityacross the adult lifespan

This study examines age-related changes in frequency-specific resting-state functional connectivity across the adult lifespan using MEG data and finds associations with sensorimotor function.

Directed Brain Connectomics Revealed by Bicommunity Structure

This paper introduces directed connectomics using bicommunities to reveal asymmetric pathways in brain networks and validates them with electrophysiological data.

Exploring the role of the rich club in network control of neurocognitive states

This study challenges the idea that the rich club controls brain dynamics, showing low-degree regions are more effective in controlling the human connectome across various brain states and parameters.

The methodological foundations of lesion network mapping remain sound

The paper defends lesion network mapping by showing that it provides meaningful differences through specificity testing, refuting criticisms that it reflects normative connectome properties.

Modular functional brain network organization contributes to training-related changes in task switching in children

This study finds that higher baseline network modularity in children predicts better task-switching training outcomes, including faster improvements in accuracy and speed.

The genetic landscape of heterogeneity in human functional brain connectivity

The paper identifies genetic variants associated with functional brain connectivity in a large cohort, linking them to neurodevelopment and health-related traits.

Normative Deviations Reveal Task-Evoked and Clinical Network Reorganization

OSCAR detects condition-related deviations in brain connectivity using a normative modeling framework, identifying task-evoked and clinical network reorganization with high accuracy.

Exploring the Interaction of APOE-ϵ4 and PICALM rs3851179 With Dynamic Functional Connectivity in Healthy Middle-Aged Adults at Risk for Alzheimer's Disease

This study uses resting-state fMRI to analyze dynamic functional connectivity dwell-time patterns in middle-aged adults to differentiate Alzheimer's disease genetic risk profiles.

The Intrinsic Manifold of Spontaneous Activity Constrains Cortical Responses to Naturalistic Stimuli

This paper shows that the low-dimensional manifold of spontaneous brain activity can represent responses to naturalistic stimuli, using a deep variational autoencoder trained on resting-state fMRI data.

Synergistic and Redundant Information Dynamics Exhibit Dissociable Alterations Across Major Psychiatric Disorders

The paper analyzes information dynamics in brain networks of psychiatric disorders, finding distinct patterns of synergy and redundancy reduction or increase in schizophrenia, autism, and ADHD.

Conditioned Graph Reconstruction of Brain Functional Network Connectivity Reveals Interpretable Latent Axes of Sex and Fluid Intelligence

The paper introduces a conditional graph variational autoencoder to model brain functional connectivity, reconstructing network patterns conditioned on sex and fluid intelligence while preserving interpretable latent features.

Attractor dynamics of a whole-cortex network model predicts emergence and structure of fMRI co-activation patterns in the mouse brain

The paper develops a whole-cortex model of resting-state fMRI activity in mice, showing that attractor dynamics explain the emergence and structure of co-activation patterns (CAPs) through anatomical connectivity.