Functional Brain Connectivity Studies

This paper examines the dynamic functional architecture of the somato-cognitive-action network (SCAN) and identifies coupling patterns that contribute to its static structure.

The paper shows longer scans improve prediction accuracy in brain-wide association studies while reducing costs, with 30-minute scans being the most cost-effective.

This study examines how functional homotopy changes with age and its relationship with intelligence in children and adolescents, finding that higher IQ individuals show faster hemispheric specialization.

This paper identifies five large-scale signal propagation modes in resting-state fMRI data that predict BOLD dynamics and unify brain network transitions, with implications for cognitive abilities and neurological disorders.

The paper reduces a large set of time-series features to a smaller, efficient subset for analyzing fMRI data from mouse cortical circuits, showing improved performance and generalization.

This study compares functional network energy across multiscale brain networks in preterm and full-term adolescents from the ABCD study, identifying differences in network stability and flexibility.

The paper maps functional brain network maturation in early infancy using resting-state fMRI, showing age-related increases in network consistency and engagement.

This paper identifies amplitude-dependent co-fluctuation transitions along the sensorimotor-association axis using resting-state fMRI data across developmental stages and external stimuli.

This study introduces normalized dynamic time warping to improve sensitivity in detecting functional network connectivity differences in schizophrenia compared to standard DTW and correlation methods.

The paper investigates how heart rate influences large-scale brain network dynamics using EEG, fMRI, and HR data during emotional stimuli, finding both direct and obscured neural-cardiac links.

The paper analyzes edge controllability in a macaque structural connectome to identify critical edges for state transitions in brain networks.

The paper identifies a neural archetype associated with chronic pain susceptibility by analyzing resting-state networks in population and clinical samples.

DeepDisco predicts brain connectivity maps from binary regions or lesions using deep learning, providing a scalable and accessible tool for large datasets.

This study uses probabilistic Boolean networks to model brain connectivity in Alzheimer's disease, identifying five declining connections and a disruption from the Default Mode Network to the Medial Temporal Lobe.

This study examines how isoflurane affects functional brain networks in marmosets, finding reduced network dynamics and increased similarity to anatomical structure under anaesthesia.

This paper introduces a biologically grounded model that explains both cooperative and competitive interactions in the brain using laminar-specific cross-frequency coupling, validated on fMRI data from 60 subjects.

The paper integrates spatial transcriptomics and cortical networks in macaques to identify cellular correlates of aging, finding age-related declines in transmodal networks linked to inhibitory and glial cells.

The paper examines age-related changes in within- and between-module interactions in rsfMRI data, finding stronger within-module inhibitory effects in older adults.

This study compares intra- and inter-individual brain connectivity patterns using longitudinal neuroimaging data, finding that intra-individual correlations better reflect resting-state functional connectivity and are influenced by aging and state-like variability.

The paper investigates individual uniqueness in brain connectivity gradients using resting-state fMRI data, finding that network complexity and dispersion influence identification rates.

The paper applies a VARX model to intracranial recordings to separate intrinsic brain dynamics from external stimuli, finding that intrinsic dynamics enhance and prolong neural responses to sensory inputs.

This study identifies neuroimaging correlates of depression across six large-scale datasets, finding gray matter reductions in specific brain regions and unexpected results in subcortical and functional connectivity analyses.

This study examines how structural and functional brain network architecture, age, and attention skills develop in early childhood using graph theory and longitudinal neuroimaging data.

The paper links functional change patterns to brain structure using multimodal fusion in adolescents, revealing sex-specific differences in neural dynamics.

This paper introduces dFNG, a method to estimate dynamic functional network connectivity gradients from ICA, and applies it to schizophrenia data to reveal distinct connectivity patterns between patient and healthy groups.

This study uses multilayer network analysis of MEG data to show that musicians have distinct modular brain organization in specific frequency bands compared to non-musicians.

The paper applies fMRI analysis techniques to whole-brain calcium imaging data in Drosophila to study structural and functional connectivity relationships.

This study shows that reduced thalamic network controllability in MS patients predicts cognitive impairment better than thalamic volume.

This study identifies altered neural timescales in adolescents with major depressive disorder, linking them to clinical symptoms and neurobiological mechanisms.

The paper examines how different tasks affect inter-individual functional brain connectivity estimates using regional homogeneity from fMRI data across seven tasks and a resting state.