Functional Brain Connectivity Studies

This study examines hyper- and hypoconnectivity in early schizophrenia using fMRI data, finding localized dysconnections and highlighting the impact of denoising strategies on results.

This study examines functional connectivity changes in the Default Mode Network of Australian Rules Football players using resting-state fMRI to assess potential as an early biomarker for non-concussive impacts.

This study uses off-equilibrium fluctuation-dissipation theorem to analyze brain dynamics in Alzheimer's disease, finding increased deviations in MCI and decreased deviations in AD, suggesting potential biomarkers for early detection.

This study investigates how cerebellar stimulation affects cortical network dynamics using dynamic community detection, finding increased network flexibility and individualized modular changes.

This study examines the development and co-evolution of microstructural and functional brain connectomes in preterm and full-term infants, finding age-related changes and disruptions due to prematurity.

This paper creates a whole-brain functional atlas from resting-state fMRI data to standardize terminology and improve consistency across neuroimaging studies.

This study introduces BEN-Based Predictive Modeling (BPM) to predict phenotypes using brain entropy (BEN) and gray matter volume (GMV), showing it outperforms GMV-based models and matches connectome-based predictive modeling (CPM) accuracy.

The paper introduces graph diffusion wavelets to estimate functional connectivity from structural connectivity, achieving high correlation and revealing power-law diffusion scales and frontal pole dominance.

This study investigates how neurotransmitters contribute to structural-functional coupling in the brain using gray matter volume and brain entropy metrics from fMRI data.

This study examines how variability in brain state engagement changes with age and its relationship to executive function in youth.

This study uses movie-driven fMRI to identify homologous functional brain networks in marmosets and humans, revealing shared neurofunctional architecture across species.

The paper examines how time spent in mealtime conversations affects default network function using mobile sensing and fMRI data.

This study examines sex-specific brain activity dynamics in youth with and without a family history of substance use disorder, finding differences in transition energy across brain networks.

This study uses multimodal brain imaging data from UK Biobank participants to identify shared and distinct brain properties associated with insomnia, depression, and anxiety symptoms.

The paper identifies a functional open loop circuit (OLC) in humans connecting ventral putamen to motor cortical areas via subcortical limbic nodes using high-resolution fMRI.

This study examines how connectivity hyperalignment (CHA) affects brain network properties across spatial scales, showing improved inter-subject similarity while preserving individual-specific features.

The paper examines how functional connectivity between thalamic nuclei and cortical/subcortical networks changes during learning in humans, identifying shifts associated with transitioning from controlled to habitual behavior.

Indiv-Brain uses deep learning to partition brain networks from individual fMRI data without prior parcellation, achieving higher accuracy than existing methods.

The paper responds to criticisms of a previous study showing that geometric eigenmodes of the human cortex better reconstruct fMRI activity maps than connectome-derived eigenmodes.

This paper introduces a method to identify linear and explicitly nonlinear dependencies in resting fMRI data and applies it to detect differences in schizophrenia.

This study examines intrinsic brain network function in chronic pain using EEG data from 537 individuals, finding some replicable associations but highlighting the need for collaborative research.

This study examines how geometric eigenmodes of the brain change over adolescence and their links to mental health and wellbeing.

The paper introduces an information-theoretic method to detect community structure in dense cortical networks, revealing a nested hierarchy of link and node communities in macaques.

This study examines opioid-induced changes in brain activation and functional connectivity in awake mice, finding that dysconnectivity correlates with analgesia.

The paper investigates whether redundancy in brain networks protects cognitive function in individuals with accelerated brain aging, finding that redundancy in the dorsal attention network is positively associated with processing speed in those with a positive brain-age gap.

The paper uses connectome predictive modeling to identify neural correlates of trait mindfulness subscales in resting-state fMRI data from three samples.

This study evaluates seven dynamic functional connectivity methods using simulation data, finding that enhanced versions outperform originals based on spatiotemporal association.

This study examines sex differences in cerebellar structure and functional connectivity across adulthood, linking these differences to sex-steroid hormone levels.

The paper develops MEG functional connectome sub-network fingerprints to classify Parkinson's patients from healthy subjects with high F1 score.

This study uses connectome harmonic decomposition to show that ketamine-induced unresponsiveness increases localised harmonics, similar to psychedelic states, unlike traditional sedation which increases global harmonics.