Functional Brain Connectivity Studies

Testing the Tests: Using Connectome-Based Predictive Models to Reveal the Systems Standardized Tests and Clinical Symptoms Are Reflecting

This paper introduces a feedback approach to connectome-based predictive modeling to identify which brain systems standardized tests and clinical symptoms reflect, enabling better-targeted test development.

A Shared Entropic Axis Spans States of Consciousness Across Pharmacological and Clinical Conditions

The paper quantifies consciousness states using entropy across pharmacological and clinical fMRI data, finding a shared entropic axis spanning from low-entropy anaesthesia to high-entropy psychedelic and schizophrenia states.

Functional Templates in fMRI: Building Accurate and Interpretable Group-Level Decoders

This paper compares functional alignment methods and template construction strategies in fMRI to improve group-level decoding accuracy and interpretability.

Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function

The paper uses fMRI data to estimate hierarchical networks in the human cerebral cortex, revealing a global organization with distinct functional properties across different network orders.

Efficient Deep Learning Models for Predicting Individualized Task Activation from Resting-State Functional Connectivity

This study evaluates deep learning models for predicting task activation from resting-state fMRI, finding that architectural changes improve efficiency without sacrificing accuracy.

Prediction of fMRI activity using vector autoregressive models: a comparison of sparse and low-rank approaches

This paper compares sparse and low-rank approaches for predicting fMRI activity using VAR models, finding that low-rank pre-smoothing reduces prediction error and improves individual-level parameter estimation.

Cortical geometry constrains the unimodal anchors of sensory integration

The paper tests if cortical geometry encodes sensory function by modeling multisensory integration from geometric eigenmodes, finding they align with sensory domains but require additional modes for full hierarchy.

Disentangling Brain-Psychopathology Associations: A Systematic Evaluation of Transdiagnostic Latent Factor Models

This study evaluates transdiagnostic latent factor models for brain-psychopathology associations using neuroimaging data, finding no consistent improvement in predictive utility over summary scores.

Structural co-modulation: An individualized measure of inter-component interactions in source-based morphometry

This paper introduces a structural co-modulation measure to quantify individualized interactions between brain components using source-based morphometry, finding reduced co-modulation in schizophrenia patients.

Lesion-Gradient Mapping in Semantic Aphasia: Comparisons of Observed and Simulated Effects of Stroke on Connectivity Gradients

This study shows that changes in functional connectivity gradients after stroke can explain semantic aphasia deficits, and these changes can be simulated from structural MRI data.

Structure-Function Dynamics in Healthy Cognitive Aging: A Graph Signal Processing Approach

This study uses graph signal processing to analyze structural and functional brain connectivity in healthy aging, revealing distinct age-related patterns in cognitive systems.

Genetic basis of dynamic brain states reveals cellular and disease associations

This study identifies genetic factors influencing dynamic brain states from fMRI data and links them to cellular processes and complex traits.

Arousal modulates functional connectivity through structured and hemispherically asymmetric community architecture during wakefulness

A common connectome-based neural reference space across affective, autonomic, and wakefulness arousal

The paper develops a connectome-based neural reference space for arousal by showing dynamic connectivity captures shared dynamics across affective, autonomic, and wakefulness arousal measures.

Physiologically Informed PCA-Partial Correlation for highly Collinear Brainstem fMRI Networks

This paper introduces a physiologically informed PCA-regularized partial correlation method to estimate direct brainstem functional connectivity in highly collinear fMRI data, improving robustness and interpretability.

Source-space EEG functional connectivity and prediction of cognition in Parkinsons disease: No added benefit of individualized head models over standard templates

The paper evaluates if individualized head models improve source-space EEG functional connectivity predictions of cognition in Parkinson's disease, finding standard templates are sufficient.

Patterns of brain-wide associations reflect socioeconomics

The paper links socioeconomic status (SES) to brain-wide associations, showing SES has stronger associations with brain structure and function than IQ or psychopathology.

Dynamic network reconfigurations during task engagement following resting state in adolescent onset schizophrenia

This study uses energy landscape analysis on fMRI data to show that adolescent-onset schizophrenia exhibits altered brain state dynamics during task engagement compared to healthy controls.

Reorganisation of Functional Connectivity Gradients in Post-Stroke Aphasia

This study examines how stroke-induced changes in functional connectivity gradients relate to language outcomes in aphasia patients.

Longitudinal consensus clustering reveals the functional architecture of the developing rat brain

This study uses longitudinal consensus clustering to map functional brain networks in developing rats, revealing developmental trajectories and functional architecture similar to human brain development.

The blueprint of human functional architecture shifts from cognition to anatomy during perturbations of consciousness

This study shows that cognitive co-activation dominates fMRI synchrony in the awake brain but is replaced by anatomical and molecular constraints during consciousness perturbations.

Generalisable signatures of anaesthesia in the large-scale functional organisation of the marmoset brain

This study shows that anaesthesia in marmosets alters large-scale brain organisation, similar to findings in humans and macaques, by constraining activity with structural connectivity and collapsing functional gradients.

Beyond the Forest and the Trees: Overlooking the Overlooked Terrain of Neural State Dynamics

This paper redefines EEG microstate analysis by shifting from template-based clustering to landmark-based state definitions, improving analytical performance and reproducibility.

A sex-balanced longitudinal developmental task-free fMRI rat dataset.

The paper presents a longitudinal fMRI dataset of Wistar rats across development, including sex-balanced samples and additional phenotypic data for studying brain development and Sex As a Biological Variable.

Spatiotemporal unfolding of prefrontal neural response divergence in adolescent depression during naturalistic experience

This study uses fMRI data to show that neural response divergence in adolescents with depression occurs in specific prefrontal regions during naturalistic experiences, linked to symptom severity and tied to narrative moments.

The ENIGMA MEG Pipeline: Automated cortically localized spectral analysis of multi-site resting state MEG datasets

The ENIGMA MEG pipeline automates spectral analysis of multi-site resting state MEG data, demonstrating compatibility with large-scale processing.

Batch Effect Correction for Neuroimaging Data with Heterogeneous Spatial Correlations

The paper develops and evaluates new batch effect correction methods for neuroimaging data that account for spatial correlations, showing improved performance over existing methods.

Comparative Evaluation of Deep Generative Models for Capturing Topological Features in Brain Structural Connectivity

This study compares deep generative models for generating brain structural connectivity data, finding that WGAN-GP provides the most stable performance while VAE and DDPM have application-specific strengths.

Homophily-informed generative models of brain maps

This paper introduces a generative model of brain maps based on homophily and shows it can accurately reconstruct maps using biological and functional similarity.

Test-retest reliability of resting-state fMRI functional connectivity: impact of scan length and number of participants

This study evaluates the test-retest reliability of resting-state fMRI connectivity metrics based on scan length and participant number, finding that scan length has a stronger impact than participant count.