Functional Brain Connectivity Studies

The paper examines how thalamic nuclei's structural and functional properties relate to cognitive performance, finding that functional controllability contributes uniquely to specific cognitive domains beyond structural metrics.

The paper compares individual variability in fMRI and MEG neural fingerprints, finding low correspondence at the subject level despite population-level similarity.

This paper identifies lifespan transitions in cortical morphometry using a data-driven framework and shows that morphometric features exhibit distinct network organisation patterns across age.

This study shows that flexible brain state engagement predicts cognitive control across multiple psychiatric disorders using machine learning and three transdiagnostic datasets.

The paper examines how chemoarchitecture influences frequency-resolved functional connectivity and how aging affects this relationship, finding that neurochemical-functional alignment varies by frequency and impacts cognitive performance.

This study examines how different musical genres modulate functional brain networks using EEG data, revealing genre-specific patterns of neural integration and information flow.

The paper uses DyNeMo to analyze MEG data from children and adults during emotional face processing, revealing distinct developmental trajectories in brain network activation and connectivity.

This paper introduces an information-theoretic framework to decode cognitive states from fMRI data, showing it can identify active brain regions and distinguish between cognitive task phases and expertise levels.

This paper introduces a Shannon information source model for fMRI-based network analysis to diagnose early Alzheimer's disease, finding that entropy increases and inter-regional interactions decrease with disease progression.

The paper examines how food preference relates to distinct cortical functional connectivity patterns during food image observation using EEG data from healthy adults.

This paper develops a computational framework to model how task-induced changes in brain dynamics relate to cognitive individual differences using rsfMRI and tfMRI data.

The paper identifies parallel processing chains in association cortex using multiple functional mapping modalities, showing they are experience-driven and organized across different cytoarchitectures.

The paper shows that brain representations converge across individuals despite diverse topographic layouts, with topographic differences linked to architectural constraints and developmental factors.

The paper uses a convolutional neural network on longitudinal MRI data to derive latent brain representations linked to adolescent phenotypic variation.

The paper introduces IC-TFCE, an algorithm that improves the computational efficiency of threshold-free cluster enhancement for functional connectivity analysis, achieving significant speedups for large-scale analyses.

This paper introduces a method to analyze directional brain network organization using fMRI data, identifying strength and duration signatures of neural influence across species and conditions.

This study examines how brain network organization changes with age during negative movie watching, finding reduced integration and altered hub dynamics in older adults.

This paper evaluates rsfMRI foundation models for identifying robust neural patterns predicting cognitive intervention outcomes in aging, showing improved performance over conventional methods.

This study uses multivariate information theory to show how structural features of the human connectome influence higher-order information sharing, revealing distinct structural profiles for redundant and synergistic brain region subsets.

This paper reframes Global Signal Removal (GSR) as graph spatial filtering, introducing variants with different effects on network connectivity.

This study examines structural and functional connectivity of the central auditory system in HIV-exposed uninfected children at age 11, finding subtle alterations in the inferior colliculus and its connections without significant neurocognitive correlates.

This paper introduces a voxel-wise O-information framework to analyze high-order functional interactions in neuroimaging data, revealing age-related changes in default mode network redundancy.

This study uses nonlinear functional brain networks to show that resting-state brain dynamics predict transcendent thinking in adolescents, unlike linear measures or IQ.

The paper uses EEG and machine learning to show that thermodynamic rigidity in brain states correlates with general mental ability in juvenile myoclonic epilepsy.

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

This paper develops a fusion hidden Markov model for simultaneous EEG-fMRI data, identifying a dominant backbone state and transient alternatives in resting-state brain dynamics.

This paper introduces bi-cross-validation to evaluate and compare dynamic functional connectivity models in fMRI, showing it balances model fit and complexity effectively.

This paper develops a normative modeling framework to analyze static and dynamic functional connectivity across lifespan, revealing distinct age-related trajectories for each.

The paper identifies a transdiagnostic brain functional connectivity signature of craving across substance use disorders using connectome-based predictive modeling.

This study uses longitudinal MRI and complementary techniques in rats to show that female-specific brain connectivity and white matter preservation support cognitive resilience with age, mediated by sex hormones.