Functional Brain Connectivity Studies

Mapping individualized multi-scale hierarchical brain functional networks from fMRI by self-supervised deep learning

This paper introduces a self-supervised deep learning framework to compute individualized multi-scale hierarchical functional networks from fMRI data and shows their association with biological phenotypes.

An engine for systematic discovery of cause-effect relationships between brain structure and function

The paper introduces a computational engine to systematically discover cause-effect relationships between brain structure and function using in-silico brain models.

Stimulus-Driven Leakage in Naturalistic Neuroimaging

This paper identifies stimulus-driven leakage as a methodological issue in cross-validation for naturalistic neuroimaging, showing how it leads to spurious predictive performance due to overfitting to repeated stimuli.

Unraveling the Neural Landscape of Mental Disorders using Double Functional Independent Primitives (dFIPs)

This study identifies distinct functional connectivity patterns in mental disorders using dFIPs derived from rs-fMRI data, revealing disorder-specific and shared neural signatures.

Disuse-driven plasticity in the human thalamus and putamen

This study investigates disuse-driven plasticity in the human thalamus and putamen using fMRI, finding strengthened functional connectivity and signal pulses in these regions during limb immobilization.

Identification of cortical targets for modulating function supported by the human hippocampal network

The paper identifies individualized TMS targets in the hippocampal network using resting-state fMRI data from a large cohort.

Age differences in brain functional connectivity underlying proactive interference in working memory.

This study examines age-related differences in resting-state functional connectivity linked to proactive interference in working memory using cross-sectional and longitudinal data.

Adolescents with major depression featured by sensory-association subtyping show divergent information dynamics and streams

This study identifies two subtypes of adolescent major depression based on sensory-association gradients, showing divergent information dynamics and clinical correlates.

Optimizing Artificial Neural Network Models to Predict Brain-Age from Functional MRI

This study optimizes deep learning models to predict brain-age from resting state fMRI data, achieving accurate predictions but showing mixed results for clinical populations.

brain network dynamics during multi-task demands predict children math achievement

The paper investigates how dynamic brain network configurations during multi-tasking predict children's math achievement by analyzing neural patterns and states.

Integrative Analysis of Neuroimaging and Microbiome Data Predicts Cognitive Decline in Parkinson's Disease

This study integrates neuroimaging and microbiome data to predict cognitive decline in Parkinson's disease, achieving high accuracy with a joint machine learning model.

Brain network connectivity underlying remission in early psychosis: a whole brain model approach

This study uses whole-brain models to analyze brain connectivity differences between remitting and non-remitting early psychosis patients, finding altered functional connectivity and potential compensatory mechanisms.

Age-related alterations in functional and structural networks in the brain in macaque monkeys

This study examines age-related changes in functional and structural networks in macaque monkeys, finding decreased structural connectivity and increased functional connectivity and amplitude of low-frequency fluctuations with age.

A General Framework for Characterizing Optimal Communication in Brain Networks

This study introduces a framework using game theory to characterize optimal communication in brain networks, finding that broadcasting models best describe communication efficiency, with rich-club regions playing a key role.

A network correspondence toolbox for quantitative evaluation of novel neuroimaging results

The paper introduces the Network Correspondence Toolbox (NCT) to evaluate spatial correspondence between novel neuroimaging results and existing brain atlases, enabling standardized reporting and comparison across studies.

Differences in fMRI-based functional connectivity during abstinence or interventions between heroin-dependent individuals and healthy controls

This paper reviews studies on how heroin dependence affects functional connectivity and how abstinence or interventions like TMS can improve it in comparison to healthy controls.

Brain structural modules associated to functional high-order interactions in the human brain

This study investigates the coupling between structural connectivity and high-order functional interactions in the human brain, finding that structural networks are associated with both redundant and synergistic functional interactions.

Resting State connectivity patterns associated with trait anxiety in adolescence

The paper investigates resting-state connectivity patterns in adolescents with trait anxiety, finding reduced connectivity in networks related to self-referential processing and rumination.

Beyond Pairwise Connections in Complex Systems: Insights into the Human Multiscale Psychotic Brain

This paper introduces a matrix-based entropy functional to analyze multiscale brain networks beyond pairwise interactions, offering new insights into complex brain dynamics and psychiatric conditions.

Connectional axis of individual functional variability: Patterns, structural correlates, and relevance for development and cognition

The paper identifies a connectional axis of functional connectivity variability across the human connectome, showing its structural correlates, developmental changes, and link to cognitive performance.

Spontaneous fluctuations in global connectivity reflect transitions between states of high and low prediction error

The paper investigates how brain connectivity fluctuates between high and low prediction error states using fMRI and EEG data, showing these fluctuations correlate with cognitive operations.

Resting state brain network segregation is associated with walking speed and working memory in older adults

This study examines network segregation in older adults and finds it correlates with walking speed and working memory, with higher segregation linked to better physical function.

Influence of insulin sensitivity on food cue evoked functional brain connectivity in children

This study examines how insulin sensitivity in children affects brain connectivity in response to food cues, finding differences in insula functional connectivity associated with lower insulin sensitivity.

Apparent Diffusion Coefficient fMRI shines light on white matter resting-state connectivity as compared to BOLD

This study compares BOLD and ADC-fMRI in functional connectivity, finding ADC-fMRI provides more robust white matter connectivity and higher inter-subject similarity.

Co-Activation Patterns Characterize Early Resting-State Networks in Newborn Infants: A High-Density Diffuse Optical Tomography Study

This study applies co-activation pattern analysis to neonatal HD-DOT data to identify dynamic functional connectivity features in newborns.

Network geometry shapes the transformation of task representations across human cortex

The paper shows that network geometry influences how task representations change across different cortical regions, with low-dimensional connectivity compressing and high-dimensional connectivity expanding representations.

Lifetime physical activity and network attack tolerance contribute to the preservation of motor function in Parkinson's disease

State-dependent relationship between lower and higher order networks in fMRI brain dynamics

This study investigates how functional connectivity in resting-state networks depends on structural connectivity, showing state-dependent interactions between lower and higher order networks.

Using normative models pre-trained on cross-sectional data to evaluate intra-individual longitudinal changes in neuroimaging data

This paper introduces a framework using normative models to assess intra-individual longitudinal changes in neuroimaging data, revealing significant grey matter normalization in schizophrenia patients over time.

A Subset of Cortical Areas Exhibit Adult-like Functional Network Patterns in Early Childhood

This study identifies infant brain areas with adult-like functional network organization, showing less age-related variation and higher reliability, and suggests implications for using adult network models in infants.