Functional Brain Connectivity Studies

This study integrates Florbetapir PET and functional network connectivity to identify disease progression markers and genetic risk associations in Alzheimer's disease.

This paper develops a multiclass classification framework to identify shared and substance-specific neural circuits in cannabis and alcohol use disorder using functional connectivity features from cue-induced craving tasks.

This study introduces a novel method to analyze whole brain activity from fMRI data, revealing dynamic spatiotemporal relationships across task trials and individuals.

The paper constructs individualized functional brain networks in autism using normative models and identifies language network expansion as a key deviation.

IBMMA improves neuroimaging analysis by handling missing data and large datasets, revealing new brain region findings overlooked by traditional methods.

This study identifies increased intrinsic neural timescales in specific brain networks in cocaine use disorder patients compared to healthy controls, suggesting potential diagnostic biomarkers.

The paper shows that a small portion of posterior callosal fibers can sustain full inter-hemispheric integration, challenging the traditional topographic model of callosal organization.

BACE learns phase-specific directed connectivity from LFP data to reveal behavioral-aligned network reconfiguration during tasks.

This study shows sleep deprivation reduces brain network flexibility by altering thalamic regulation and coupling with cortical networks, leading to cognitive impairments.

The paper examines dynamic fMRI correlates of adolescent rumination and finds that adult models do not generalize, suggesting developmental differences in neural correlates of rumination.

The paper analyzes brain entropy (BEN) during movie watching in children aged 3-12 using fMRI data to identify developmental changes in the action-mode network.

The paper uses track-weighted dynamic functional connectivity to analyze hippocampal structure-function relationships in the human brain, revealing distinct functional connectivity patterns across hippocampal subfields.

This study examines intersubject correlations during naturalistic movie watching and finds they align with functional gradients across different brain networks and spatial scales.

The paper examines how cognitive states like resting and movie watching affect large-scale brain functional connectivity using fMRI data from the HCP and PNI datasets.

This study introduces an interpretable predictive model to identify functional connectivity patterns predictive of cognitive traits in youth, showing improved accuracy and fine-grained characterization.

The paper shows that increased attentive use of a brain region leads to more idiosyncratic functional connections, with implications for personalized rehabilitation and brain plasticity.

The paper provides resting-state functional MRI derivatives from the COMPASS-ND study to aid in neurodegenerative disease research.

This study shows high-frequency fMRI signals are linked to brain states and can predict spontaneous neural activity using machine learning.

This study introduces a heterochronous generative network model to better capture the spatial and temporal aspects of brain network development, improving model fit and identification of individual differences.

This paper validates data-driven factor models over RDoC-based models using fMRI and behavioral data, showing better reproducibility and clinical relevance across neural and behavioral domains.

This paper introduces a spatiotemporal connectome framework to map the human brain's action network using spatial connectivity, revealing its functional architecture and energy-saving dynamics.

This paper uses fMRI data to show that engaging in immoral behavior during a task alters post-task brain states, with lasting effects on neural dynamics.

The paper maps individual functional brain network trajectories in neonates, showing age-related changes and differences between preterm and term-born infants.

This paper introduces a new meta-analytic method to improve cerebellar mapping specificity and shows 54 behavioral terms converge to specific cerebellar subregions.

The paper examines the relationship between brain activity and connectivity across cognitive domains using resting-state data and activation maps, finding a robust association that supports connectivity as a general organizational principle.

The paper quantifies the contribution of aperiodic activity to oscillatory functional networks in EEG data and finds that aperiodic activity dominates most networks.

This study investigates the reconfiguration of brain hierarchy in schizophrenia using resting-state fMRI and finds increased hierarchical organization linked to clinical symptoms and diagnostic separation.

This study shows that resting-state functional connectivity better predicts sex than cortical thickness in preadolescents and relates to sex/gender alignment.