Functional Brain Connectivity Studies

This study identifies infant brain areas with adult-like functional network organization, showing less age-related variation and higher reliability, and suggests implications for using adult network models in infants.

The paper shows that overlooked brain connectivity features can yield different neurobiological interpretations with similar prediction accuracy in neuroimaging studies.

The paper constructs the first human brain metabolic connectome using MR spectroscopic imaging, revealing distinct topological features and alignment with cytoarchitectonic and genetic patterns.

This study tracks changes in brain functional connectivity networks over 12 months post-stroke using resting-state fMRI in 17 patients and 13 controls, revealing distinct patterns in modularity, hemispheric symmetry, and homotopic connectivity.

This study uses graph learning to analyze resting-state MEG data and identifies frequency-specific functional connectome differences in tinnitus patients compared to controls.

This paper introduces a framework to quantify irreversibility in brain network dynamics across multiple levels and identifies higher-order organizational patterns in human brain interactions.

DySCo introduces a framework for dynamic functional connectivity analysis, providing a unified theoretical approach and efficient algorithms for processing high-dimensional brain data.

The paper assesses neurocognitive maturation in early adolescence by comparing resting-state functional connectivity to adult and infant networks, finding it predicts cognitive performance and development.

The paper shows that visual statistical learning alters low-dimensional cortical architecture by reorganizing neural activity patterns across specific brain regions.

This paper develops a framework for image-based meta-analysis using NeuroVault data, showing that manual selection provides precise results while heuristic methods are effective for heterogeneous domains.

This study uses hyperbolic neural networks to analyze MEG brain networks from the Cam-CAN dataset, revealing age-related hierarchical changes in brain subnetworks.

This study compares changes in linear and nonlinear functional connectivity in MDD patients after psilocybin or escitalopram treatment, finding distinct patterns between responders and non-responders.

The paper identifies three conserved functional connectivity gradients in primate cortical connectomes using fMRI, linking them to predictive coding and adaptive cognition.

This study identifies a structural connectivity pattern shared between physical activity and depressive mood using UK Biobank data, linking it to neurotransmitter receptors and pathways.

This study introduces DEFN, a novel approach using dynamic functional connectivity to identify emotion-specific neural signatures, improving classification accuracy for mood disorders.

This paper introduces M-DyNeMo, a method that reveals uncoupled dynamics between power and functional connectivity in MEG data, showing task-related modulation of these dynamics.

This paper introduces T-TVFC, a method for targeted time-varying functional connectivity analysis, and shows it captures task-related information in thalamocortical networks not found in traditional methods.

This study compares cortical gradients in congenitally blind and sighted adults to assess the role of genetics and experience in shaping functional connectivity.

This study identifies brain network cores with strong bidirectional interactions using fMRI data and links them to conscious perception and sensorimotor functions.

The paper analyzes time-varying synergy and redundancy dominance in fMRI BOLD signals during rest, finding that whole-brain synergy is rare and that optimized subsets show recurrent functional systems.

This study examines the association between parenthood and brain function in mid- to late-life, finding that higher parity is linked to increased functional connectivity and counteracts age-related declines.

The paper uses ultrafast fMRI and a Layer-based Connective Field model to distinguish feedforward and feedback signaling in cortical circuits, revealing distinct layer-specific connectivity patterns.

This study examines topological high-order functional connectivity in schizophrenia, finding disrupted integration-segregation balance and potential diagnostic indicators.

This study uses resting-state fMRI to identify differences in functional connectivity between resilient and susceptible mice after chronic social defeat stress, highlighting brain region interactions linked to stress resilience.

The paper uses white-matter controllability at birth to predict social engagement and language outcomes in toddlers.

The paper identifies multiple stable brain activation patterns for the same perceptual decision-making task using functional MRI and clustering analysis.

This study links functional connectivity profiles to fluid intelligence using dimensionality reduction and graph analysis, showing that functional distance from sensory and high-cognition systems correlates with intelligence.

This paper analyzes dynamic functional connectivity in fMRI data across attentional tasks to identify a spectrum of network relationships tracking external to internal attention.

This study identifies subregional structure-function coupling in the human amygdala using histology and MRI, revealing two axes of microstructural variation linked to functional networks.

This study identifies altered causal functional brain networks in Alzheimer's disease using resting-state fMRI data and the Time-aware PC algorithm, finding reduced connectivity in specific brain regions.