Functional Brain Connectivity Studies

Connectome-based brain fingerprints predict early cognitive decline in Parkinson's patients with minor hallucinations

The paper uses connectome-based brain fingerprinting to identify early cognitive decline markers in Parkinson's patients with minor hallucinations using resting-state fMRI.

Growth in early infancy drives optimal brain functional connectivity which predicts cognitive flexibility in later childhood

Bayesian generative modeling reveals a multi-modal hierarchical architecture in the mouse functional connectome

The paper uses Bayesian generative modeling to show the mouse brain's functional connectome has multiple co-dominant organizational configurations rather than a single structure.

Connectome Principal Component Drives Cross-Dataset Replication and Clinical Prediction in Symptom Lesion Network Mapping

This study shows that symptom lesion network mapping (sLNM) results are biased toward the first principal component of the normative connectome, leading to spurious convergence and non-specific clinical predictions, which can be corrected by controlling for PC1.

High-order brain interactions distinguish wakefulness, anaesthesia, and recovery induced by deep brain stimulation

The paper uses multivariate information theory to analyze brain states and finds that higher-order interactions distinguish wakefulness, anaesthesia, and recovery.

Brain states recur across diverse narrative contexts during longitudinal viewing

The paper identifies recurring brain states during longitudinal viewing of a TV series, showing that the repertoire is individual-specific and adapts to narrative content.

Minute- and second-scale hippocampal network dysfunctions in the 3xTgAD mouse model of Alzheimer's disease are prevented by TSPO knockout

This study shows that TSPO knockout prevents hippocampal network dysfunctions in 3xTgAD mice without affecting amyloid or tau levels.

Poorer physical function is associated with elevated spatial entropy in the aging brain network landscape

The paper assesses spatial entropy in brain network landscapes of older adults and finds higher entropy in specific regions correlates with worse physical function and higher BMI.

Reorganization of Human Brain Waves Across Diverse States of Consciousness

This study identifies four wave propagation motifs in the human brain across different states of consciousness and shows how they reconfigure in diminished and psychedelic states.

Objective Quality Assessment for Precision Functional MRI Data

The paper introduces NSI, an objective measure to assess data quality for precision functional MRI, aligning with expert evaluations and enabling principled decisions on data sufficiency.

Decoding Cognitive States from fMRI Using Classical Machine Learning and Temporal Dynamics Analysis: An Interpretable Approach Using the Human Connectome Project

This paper uses classical machine learning and temporal dynamics analysis to classify task-induced brain states from fMRI data, showing that temporal activity patterns are critical for distinguishing cognitive states.

Information-Theoretic Functional Connectivity Characterizes Multiscale Network Reorganization in Postoperative Cognitive Decline

This study identifies network reorganization patterns in postoperative cognitive decline using static and dynamic connectivity measures from resting-state fMRI.

Electrophysiological lag threads reveal a temporal hierarchy of the human cortex

This paper identifies electrophysiological lag threads in resting-state MEG data, revealing a frequency-specific temporal hierarchy of the human cortex that links fast neural dynamics to slower hemodynamic propagation.

Protocol Update: The Normative Modelling Paradigm for Computational Psychiatry

This paper updates the normative modelling protocol for computational psychiatry, including new methods, software tools, and models for neuroimaging data analysis.

Cortical eigenmode coordinates provide compact subject-level signatures across structural MRI, resting-state fMRI, and EEG

The paper introduces cortical eigenmode coordinates as a shared framework for multimodal neuroimaging data, showing they provide compact and interpretable subject-level signatures across structural MRI, resting-state fMRI, and EEG.

Behavioural and neural signatures across diverse cognitive demands in a multimodal electroencephalography-functional magnetic resonance imaging design

This study introduces a compact multimodal EEG-fMRI framework to assess cognitive domains and demands, showing consistent behavioural and neural patterns across modalities.

Linking time-lagged functional dynamics to spatial constraints in resting-state fMRI

The paper uses linear state-space models to analyze resting-state fMRI data from mice, decomposing the Jacobian matrix to link time-lagged functional dynamics with spatial constraints.

Brain-wide distributed processing underlying natural vision and audition

This study investigates brain dynamics during natural vision and audition by analyzing information flow between brain regions in sighted, blind, and deaf participants, revealing how distributed processing supports perception.

The Brain Encyclopedia Atlas Project (BEAP): A Literature-Synthesis-Derived Functional Atlas of the Human Brain

BEAP synthesizes functional neuroanatomy from literature to create a spatially integrated atlas of human brain regions.

Aberrant cortical subcortical somatosensory network organization is associated with impaired tactile-motion perception in akinetic-rigid Parkinson's disease

The paper investigates tactile-motion perception deficits in Parkinson's disease by analyzing functional MRI connectivity and finds altered sensorimotor network organization associated with impaired perception.

Patterns of Typical and Atypical Age-related Brainstem Volume losses

This study uses structural MRI and machine learning to identify subtypes of age-related brainstem volume loss and their associations with functional decline.

Brain dynamics of attentional, default-mode and limbic networks are disrupted at rest in Post-COVID-19 Syndrome

This paper identifies altered dynamic brain states in Post-COVID-19 Syndrome using resting-state fMRI, showing reduced attentional states and increased limbic-DMN states linked to cognitive impairment and inflammation.

Assessment of Coupled Phase Oscillators-Based Modeling in Swine Brain Connectome

The paper evaluates a Kuramoto model to simulate functional connectivity in swine brains, showing good agreement with empirical data but limited changes post-traumatic brain injury.

The Hidden Landscape of Missed Effects in Human Functional Neuroimaging

The paper identifies inflated effect sizes in functional neuroimaging studies and proposes a correction method to improve study planning and detection of brain effects.

The dual interpretation of edge time series: Time-varying connectivity versus statistical interaction

The paper demonstrates that edge time series, a method for tracking connectivity changes, are equivalent to interaction terms in a linear model and show connectivity has unique explanatory power beyond brain activity.

Dynamic Estimation of Spatially Interactive Networks (DESINE) Reveals Constrained Brain Repertoire in Schizophrenia Linked to Clinical and Cognitive Symptoms

DESINE quantifies dynamic spatial network interactions in schizophrenia, finding reduced variability and rigidity linked to cognitive and clinical symptoms.

Regional reconfiguration of functional brain networks during childhood and adolescence: evaluating age and sex effect

The paper evaluates age and sex effects on regional functional brain network reconfiguration during childhood and adolescence using resting-state fMRI data.

Human white matter tracts aligned with canonical functional brain networks

The paper aligns white matter tracts with canonical functional brain networks using an atlas and meta-analytic decoding, revealing structural-functional organization.

A Unified Form of Batch Harmonization Equation for Normative Modeling: A Location Scale Framework

This paper introduces a unified framework for batch harmonization in normative modeling, showing how existing methods can be expressed as special cases of a single location-scale equation.

Generalized Normative Modeling: A One-Step Hierarchical Kernel Framework for Multi-Site Brain Charts with Self-Correcting Z-Scores

This paper introduces GNM, a hierarchical framework for multi-site brain normative modeling that produces site-invariant z-scores and preserves age-related signals better than existing methods.