Functional Brain Connectivity Studies

The human claustrum initiates networks for externally and internally driven task demands.

This study identifies the claustrum as a key initiator of task-dependent network states in cognitive control using fMRI and structural connectivity analyses.

Functional Inputs to the Subgenual Cingulate Cortex Distinguish Neurotypical Individuals with Severe and Mild Depressive Problems: Granger Causality and Clustering Analyses

The paper uses Granger causality and clustering to identify brain regions with significant input to the subgenual cingulate cortex (sgACC) and distinguishes individuals with severe and mild depressive symptoms.

Cognition is associated with task - related brain network reconfiguration in late childhood

The paper examines brain network reconfiguration in late childhood and finds more reconfiguration correlates with better task performance and cognition.

The Topological Architecture of Brain Identity

This paper introduces a topological fingerprinting method using homological scaffolds from resting-state fMRI data, achieving near-perfect individual identification accuracy.

Disrupted Energy Landscape in Individuals with Mild Cognitive Impairment: Insights from Network Control Theory

This study uses Network Control Theory to analyze differences in brain energy landscapes between MCI patients and healthy controls, finding lower transition energy in the limbic network and reduced global entropy in MCI.

The synergistic interactions of low-dimensional brain modes

The paper examines how dimensionality reduction techniques preserve synergistic interactions in brain dynamics using resting-state fMRI data from 100 healthy participants.

Spectral imprint of structural embedding in effective connectivity

This paper introduces a chromatic dynamic causal model that links structural valency to spectral properties of neural fluctuations, showing it outperforms standard models and reveals conserved valency-exponent mappings across species.

Independence-based causal discovery analysis reveals statistically non-significant regions to be functionally significant

The paper uses causal discovery analysis to show that statistically non-significant fMRI regions causally influence psychopathology severity and working memory performance.

Structural connectivity-informed dynamic estimation (STRiDE): Multimodal connectivity constrained ICA

STRiDE improves dynamic brain state estimation by integrating structural and functional connectivity, revealing disruptions in schizophrenia.

Population-specific brain charts reveal Chinese-Western differences in neurodevelopmental trajectories

The paper develops population-specific brain charts for Chinese individuals, revealing distinct neurodevelopmental patterns compared to Western populations and showing better performance in predicting brain phenotypes.

NiCLIP: Neuroimaging contrastive language-image pretraining model for predicting text from brain activation images

NiCLIP predicts cognitive tasks and domains from brain activation maps using a contrastive language-image model trained on neuroscientific articles.

A multiplex of connectome trajectories enables several connectivity patterns in parallel

The paper examines multi-timescale functional connectivity dynamics in the brain using EEG and fMRI data, finding spatial convergence but temporal divergence across different FC timescales.

Resting-state fMRI coherence is selectively diminished around 0.1 Hz, particularly inside watershed areas, in patients with unilateral carotid artery stenosis

This study shows that unilateral carotid artery stenosis reduces interhemispheric BOLD coherence at ~0.1 Hz, especially in watershed areas, suggesting impaired vasomotor activity affects resting-state functional connectivity.

Providing context: Extracting non-linear and dynamic temporal motifs from brain activity

This paper introduces a deep learning model to analyze resting-state fMRI dynamics, finding that context embeddings better predict schizophrenia diagnosis and correlate with age and symptom severity.

Estimating individual-level changes in functional brain connectivity and correspondence with topology changes

The paper evaluates six change scores for functional brain connectivity using ABCD Study data to determine their effectiveness in capturing topology changes over time.

Weak brain-mental health associations in population neuroimaging tasks reflect a signal evocation bottleneck

The paper investigates why large-scale neuroimaging tasks yield weak brain-mental health associations, finding a signal evocation bottleneck in common fMRI tasks.

Toward Granular Brain Intrinsic Connectivity Networks and Insights into Schizophrenia

This study uses sgr-ICA with 500 components on a large rsfMRI dataset to identify fine-grained intrinsic connectivity networks (ICNs) and reveals dysconnectivity patterns in schizophrenia.

Mapping functional, structural, and transcriptomic correlates of homotopic connectivity

The paper maps the relationship between homotopic functional connectivity and anatomical, functional, and transcriptomic organization in the human cerebral cortex, showing preserved regional patterns across neuropsychiatric disorders.

The spatial layout of antagonistic brain regions is explicable based on geometric principles

The paper uses kriging to show that task-induced brain activity increases can be predicted from activity decreases, revealing topographically determined antagonistic relationships.

Convergent and Divergent Brain-Cognition Development

The paper examines how stable and changing brain network features predict cognitive development in adolescents using rs-fMRI and cognitive data from the ABCD Study.

Nonequilibrium dynamics elicited as the origin of perturbative complexity

The paper investigates how non-equilibrium dynamics in the brain relate to complexity in response to stimuli, finding reduced asymmetry and irreversibility in states of reduced consciousness.

Benchmarking methods for mapping functional connectivity in the brain

This study benchmarks 239 pairwise interaction statistics for functional connectivity mapping, finding substantial variation in their topological, neurobiological, and behavioral properties.

Evidence of functional connectivity disruptions between auditory and non-auditory regions in adolescents living with HIV

This study investigates functional connectivity disruptions in the auditory system of adolescents with HIV, finding reduced connectivity in auditory regions and associations with neurocognitive impairments.

ComBatLS: A location- and scale-preserving method for multi-site image harmonization

ComBatLS improves multi-site image harmonization by preserving biological variance in features, outperforming existing methods in sex-imbalanced site scenarios and reducing sex biases.

Resting-state functional dynamics alterations relate to plasma amyloid markers and explain memory impairments in the TgF344-AD model of Alzheimer's disease

The paper examines resting-state fMRI dynamics in a rat model of Alzheimer's disease, linking functional changes to amyloid levels and memory impairments, with better predictive power from pre-plaque stage CAPs.

Triple network dynamics and future alcohol consumption in adolescents

This study uses brain network dynamics to predict future alcohol consumption in adolescents, finding sex-specific associations between network states and drinking behavior.

Leveraging multivariate information for community detection in functional brain networks

This paper introduces a community detection algorithm for functional brain networks that accounts for higher-order interactions and identifies redundant modules, revealing new organizational patterns in the transmodal cortex.

Higher-order EEG microstate syntax and surrogate testing

The paper evaluates surrogate data generation methods for EEG microstate syntax analysis, finding that Markov chain surrogates are valid while shuffling is not.

Event-marked Windowed Communication: Inferring activity propagation from neural time series

This paper introduces EWC, a method to infer discrete neural communication from continuous time series data, showing it is faster and effective at capturing directional signaling.

Context-Dependent PSIICOS: A Novel Framework for Functional Connectivity Estimation Accounting for Task-Related Power Leakage

CD-PSIICOS improves functional connectivity estimation by reducing task-related power leakage artifacts in MEG data, outperforming the original PSIICOS method.