Functional Brain Connectivity Studies

This paper identifies two neurophysiology-informed symptom dimensions in MDD using contrastive functional connectivity analysis of fMRI data.

The paper examines genetic and environmental influences on local brain function measures (ReHo and fALFF) in adolescents, finding region-specific effects and temporal stability across two time points.

This paper introduces instantaneous frequency as a biomarker for dynamic brain networks, showing it can distinguish clinical and demographic groups in neurodegenerative conditions.

The paper investigates functional connectivity among sulci in lateral prefrontal and parietal cortex using individual sulcal morphology to link anatomy to cognition in children and adolescents.

The paper examines the relationship between dynamic functional connectivity measured by magnetoencephalography and plasma p-tau231 levels in cognitively intact participants, finding a positive association between frontotemporal connectivity and p-tau231.

This study identifies distinct resting state functional networks associated with striosome and matrix compartments in the human striatum using diffusion and functional MRI data.

The paper predicts [18F]FDG PET parameters using rs-fMRI and 15O PET data, showing rs-fMRI and CMRO2 explain 45% of Ki variance.

The paper identifies cross-scale neural alterations linked to affective symptoms in psychiatric disorders by comparing normative brain function with clinical data and linking these to specific cell types.

This study examines functional connectivity of thalamic nuclei during sensorimotor tasks using fMRI at 9.4 Tesla, finding that thalamic nuclei exhibit task-specific connectivity patterns rather than fixed roles.

This study uses fMRI to analyze cognitive task representations across 25 tasks, finding subject-specific and subject-invariant structures in cortical regions.

This study examines how levodopa affects brain connectivity in Parkinson's patients using resting-state functional connectivity analysis across cross-sectional and longitudinal datasets.

This study uses PHATE to reduce the dimensionality of resting-state MEG data, revealing dynamic brain states and their transitions in a low-dimensional space.

This study parcellates the cerebral cortex in toddlers using functional connectivity and shows high reproducibility across ages, with area boundaries more similar to adults than neonates.

The paper links shorter sleep duration in adolescents to somatomotor network disconnection, socioeconomic factors, screen time, cognition, and psychopathology using network neuroscience methods.

This study compares EEG resting state and task-based functional connectivity for predicting working memory performance using connectome-based predictive modeling, finding task data slightly better overall but resting state better under high load.

The paper uses simultaneous calcium imaging and fMRI in mice to identify cell-type specific signals in the brain with high spatiotemporal resolution.

This paper maps global cortical organization by integrating microstructural, connectivity, and functional data with cytoarchitectural maps, revealing a sensory-fugal gradient and functional diversity across brain areas.

The paper uses functional connectivity to parcellate the mouse prefrontal cortex and shows that perturbing specific clusters affects only their associated functional networks.

The paper examines how aging, Alzheimer's pathology, and APOE4 genotype affect longitudinal functional connectivity and episodic memory in older adults.

This study investigates the relationship between resting-state brain entropy (BEN), ovarian hormones, and behavioral inhibition and activation systems (BIS/BAS) using fMRI data.

This paper introduces Virtual Brain Twins (VBTs) as personalized digital brain models that integrate structural and functional data to improve understanding of brain function and support personalized treatment.

The paper uses fALFF to compare brain activity patterns in ASD, SSD, and TDC groups, finding shared neurobiological features and variability differences.

The paper introduces a framework using SHAP to identify FNC biomarkers distinguishing between schizophrenia patients and controls, and young vs. old adults with high accuracy.

The paper uses functional connectivity networks to analyze calcium dynamics in non-neural tissues, revealing non-random structural and informational patterns post-injury.

This study links short-term brain dynamics to long-term changes in the functional connectome during postnatal development, finding a strong association between specific brain states and non-linear developmental acceleration.

This study links multi-scale brain connectivity networks to cognitive and behavioral functions in adolescents, finding significant associations with attention, working memory, and behavioral regulation.

This study evaluates the accuracy of reconstructing cortical functional maps using subject-specific geometric and connectome eigenmodes, finding that spatially smooth eigenmodes best explain functional data.

FREQ-NESS estimates frequency-resolved brain networks using MEG data, revealing simultaneous networks and their interactions during resting state and auditory stimulation.

NaDyNet provides a toolbox for dynamic network analysis of naturalistic stimuli, offering methods to isolate and analyze brain responses in real-time.

The paper identifies robust sex differences in personalized functional brain network topography in youth, linked to X-linked genes and brain regions involved in psychiatric disorders.