Amy F. Kuceyeski

Lesion-Derived Estimated Functional and Structural Connectomes Predict Post-Stroke Recovery Outcomes

The paper develops a pipeline to estimate structural and functional connectomes from lesion masks to predict post-stroke recovery outcomes, showing better performance than traditional methods.

Economic hardship mediates differences in brain network dynamics associated with family history of substance use disorder in a sex-specific manner

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.

Mapping Individualized Developmental Imbalance in Youth and Its Association with Psychopathology

The paper introduces a framework to quantify individualized developmental imbalance in youth using predictive normative modeling and shows it predicts psychopathological vulnerability.

Longitudinal multimodal neuroimaging after traumatic brain injury

This study uses longitudinal multimodal neuroimaging to analyze changes in brain injury biomarkers over time, revealing dynamic relationships between structural, functional, and PET-derived measures.

Controlling the human connectome with spatially diffuse input signals

This paper adapts network control theory to model spatially diffuse input signals in the human brain, showing reduced energy for state transitions and matching existing neurobiological maps.

The progression of sex differences in brain networks across the lifespan

The paper analyzes sex differences in brain networks across the lifespan using a new AI-based method, finding minimal differences in early childhood, pronounced in adulthood, and diverging in later life.

TSPO-PET Reveals Higher Inflammation in White Matter Disrupted by Paramagnetic Rim Lesions in Multiple Sclerosis

The paper uses TSPO-PET to show higher inflammation in white matter disrupted by paramagnetic rim lesions in MS patients, linked to disability.

Cocaine use disorder is associated with lower brain state transition energy particularly in higher order and excitatory networks

This study finds that cocaine use disorder is linked to reduced brain state transition energy in specific networks, particularly those involved in excitatory and higher-order functions.

View, engage, predict: enhancing brain-behavior mapping with naturalistic movie-watching fMRI

This study uses naturalistic movie-watching fMRI to predict cognitive scores and sex through a deep neural network framework, showing improved performance over resting-state FC.

Psilocybin Prolongs the Neurovascular Coupling Response in Mouse Visual Cortex

This study shows psilocybin prolongs neurovascular coupling in mouse visual cortex, affecting blood flow without altering neural responses, and suggests implications for interpreting human neuroimaging data.

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.

Inferring macroscopic intrinsic neural timescales using optimal control theory

The paper develops a framework using optimal control theory to estimate brain structure-function interactions from MRI data, showing correlations between self-inhibition parameters and neural timescales across species.

Time-resolved network control analysis links reduced control energy under DMT with the serotonin 2a receptor, signal diversity, and subjective experience.

This study uses network control theory to show DMT reduces brain control energy, correlates with EEG entropy and subjective experience, and links these effects to serotonin 2a receptor distribution.

Predicting cognition using estimated structural and functional connectivity networks and artificial intelligence in multiple sclerosis

This study uses estimated structural and functional connectivity networks from MRI and AI to predict cognition in multiple sclerosis patients, finding strong predictive accuracy for follow-up scores.

Sex-specific differences in brain activity dynamics of youth with a family history of substance use disorder

This study examines sex-specific brain activity dynamics in youth with and without a family history of substance use disorder, finding differences in transition energy across brain networks.

Release the Krakencoder: A unified brain connectome translation and fusion tool

The paper introduces Krakencoder, a tool that translates and fuses structural and functional brain connectomes across atlases and processing strategies, achieving higher identifiability than existing models.

Altered structural connectivity and functional brain dynamics in individuals with heavy alcohol use

This study examines brain dynamics and structural connectivity in individuals with heavy alcohol use using multimodal imaging and finds reduced brain complexity and increased control energy.

Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes

This study compares data-driven and theory-based biomarkers for predicting chronic motor outcomes after stroke, finding data-driven models perform better, especially when using structural disconnection measures.

Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease

The paper investigates how brain network structure, neuromodulation, and disease influence transitions between cognitive activation patterns using multimodal neuroimaging data.

Brain tissue cerebrospinal fluid fraction increases quadratically in normal aging

The paper uses multi-compartment T2 relaxometry to show that parenchymal cerebrospinal fluid fraction increases quadratically with age in brain tissue.

The sequence of regional structural disconnectivity due to multiple sclerosis lesions

The paper identifies early structural disconnection biomarkers in multiple sclerosis linked to disability and cognitive impairment progression.

Larger lesion volume in people with multiple sclerosis is associated with increased transition energies between brain states and decreased entropy of brain activity

This study examines how brain lesion volume in multiple sclerosis patients correlates with changes in brain activity dynamics and entropy.

A graph-matching based metric of functional connectome distance between pairs of individuals varies with their ages, cognitive performances and familial relationships.

This study introduces a graph-matching based metric to quantify functional connectome differences between individuals and finds it correlates with age, cognitive performance, and familial relationships.

LSD and psilocybin flatten the brain's energy landscape: insights from receptor-informed network control theory

This paper shows that LSD and psilocybin reduce brain control energy and increase entropy by flattening the brain's energy landscape, using network control theory and PET data.

Increased prevalence of a frontoparietal brain state is associated with better motor recovery in individuals with pontine stroke affecting dominant-hand corticospinal tract

The paper examines brain activity patterns in stroke patients, finding that increased time in a frontoparietal brain state correlates with better motor recovery in those with dominant-hand corticospinal tract damage.

Chronic stroke sensorimotor impairment is related to smaller hippocampal volumes: An ENIGMA analysis

This study finds that smaller ipsilesional hippocampal volume is associated with worse upper limb sensorimotor impairment in chronic stroke patients, with a stronger effect in women.

Global brain health modulates the impact of lesion damage on post-stroke sensorimotor outcomes

This study shows that global brain health, measured by brain age, influences post-stroke sensorimotor outcomes and mediates the effect of lesion damage.

Estimated regional white matter hyperintensity burden, resting state functional connectivity, and cognitive functions in older adults

The paper examines the relationship between white matter hyperintensity burden, resting state functional connectivity, and cognitive functions in older adults, finding associations with memory retrieval but not other cognitive tasks.

Predicting Individual Task Contrasts From Resting-state Functional Connectivity using a Surface-based Convolutional Network

This paper introduces BrainSurfCNN, a surface-based CNN that predicts task-based contrast maps from resting-state fMRI, achieving state-of-the-art accuracy and generalization.