Functional Brain Connectivity Studies

This study maps resting-state cerebello-hippocampal connectivity in young adults, revealing sex differences but no significant cognitive associations after correction.

This paper introduces FINE, a frequency-aware deep learning model for Alzheimer's disease classification using resting-state fMRI, achieving ROC-AUC 0.769 on OASIS-3.

This study examines functional dedifferentiation in the frontoparietal network during naturalistic movie watching in older adults, linking it to depressive symptoms and emotion regulation difficulties.

The paper analyzes dynamic functional connectivity in the human brain, identifying two recurring states of cortical-subcortical interactions in healthy subjects.

This paper examines limitations in interpreting resting-state fMRI correlations, distinguishing measurement distortion from causal non-identifiability and their implications for biological interpretation.

This study uses connectome-based predictive modeling to predict individual differences in three executive function components using fMRI data from the Human Connectome Project.

This study uses dynamic functional connectivity to compare brain state dynamics during mindfulness and control conditions after stress in moderate to heavy drinkers, finding differences in salience and default mode network activity.

This study examines longitudinal changes in brain network functional connectivity during smoking cessation, finding that successful quitters show normalization of pre-quit connectivity in salience-executive and salience-default mode networks.

This paper compares sliding window Pearson correlation and phase synchronization for time-resolved functional connectivity in fMRI data, finding they capture different aspects of brain dynamics and are complementary in their strengths and limitations.

The paper investigates how task instructions affect cortical network modularity using fMRI data, finding that allocentric tasks reduce module count and recruit additional hubs for integration.

The paper links brain structure to function by showing that commute time, derived from diffusion MRI, correlates better with functional MRI data than other measures.

The paper investigates altered basal forebrain connectivity in depressive and anxiety disorders using resting-state fMRI and finds increased inhibitory connectivity from nucleus basalis of Meynert to the default mode network in clinical participants.

The paper characterizes claustral effective connectivity in humans using fMRI, showing bidirectional connections and psilocybin-induced changes in inhibition and disinhibition.

The paper examines how socioeconomic status and adversity affect the maturation rates of functional brain networks in children and adolescents, finding distinct associations with the default mode and hippocampal networks.

This study examines brain network segregation in individuals with opioid use disorder, finding that drug use severity is linked to reduced segregation in association networks, with age and positive affect also playing roles.

The paper examines how head motion-related exclusions and differential retention affect the representativeness of longitudinal neuroimaging samples in the ABCD Study, highlighting disparities among racial groups.

The paper uses network control theory to show fetal brain controllability follows a U-shaped trajectory during pregnancy, co-developing with synaptic functions and synchronizing with maternal controllability changes.

This paper examines age-related changes in cognitive integration and segregation using chimera states in brain networks, showing differential aging effects across cognitive systems.

This study develops a personalized fMRI analysis pipeline for disorders of consciousness, identifying connectivity and local parameters as biomarkers for diagnosis and prognosis.

This study maps how cortical organization matures across childhood and adolescence by analyzing frequency-specific brain activity, revealing distinct developmental stages and individual differences linked to cognitive and social traits.

This study examines changes in brain network dynamics after 60 minutes of aerobic cycling, finding reduced striato-frontoparietal connectivity.

This study uses DCC-GARCH modeling on rs-fMRI data to analyze dynamic functional connectivity in Alzheimer's disease, showing improved sensitivity to CSF Aβ status compared to current methods.

This study identifies anti-correlated neural states across multiple spatial scales in naturalistic brain activity, showing their relationship to stimulus changes and functional organization.

This study examines age-related changes in fMRI signatures of autonomic physiology, finding slower respiratory responses and faster cardiac responses with aging, with a notable turning point after age 60.

This study uses connectome-based predictive modeling to show that task-based brain functional connectivity can predict grip strength, a marker of frailty, with subcortical regions like the caudate nucleus playing a key role.

CalciumNetExploreR provides an R package for analyzing calcium imaging data through a unified pipeline of network analysis tools.

This study identifies developmental differences between dorsomedial and dorsolateral prefrontal cortex using multimodal data and transcriptomics, revealing a medial-lateral topographic division.

This paper develops a statistical framework to measure individual differences in conceptual brain representations using fMRI and finds that these differences are systematic and highest in social information processing regions.

The paper presents a large-scale multimodal fMRI dataset combining naturalistic stimuli with diverse cognitive tasks to enable comprehensive cognitive neuroscience research.

This paper uses Dynamic Causal Modeling on fMRI data to compare three basal ganglia connectivity models across cognitive tasks and resting state, finding the Mixed model performs best.