Paul J. Laurienti

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.

This paper introduces a method to quantify spatial entropy in brain network community structure and shows it decreases in specific brain regions during cognitive tasks.

This study investigates the feasibility of identifying participant identity and task-related neural patterns from single-frame functional brain connectivity data.

This study uses dynamic functional connectivity to compare brain state dynamics during mindfulness and control conditions after stress in moderate to heavy drinkers, finding differences in salience and default mode network activity.

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

MIND-Map is a toolbox that uses HSMM to estimate brain dynamic states, analyze their dynamics, and compare network dynamics between samples, with a method to determine the optimal number of states.

The paper examines how resting-state brain networks modify the relationship between amyloid beta and cognitive/physical function in older adults, suggesting brain networks as a buffer against amyloid's negative effects.

The paper compares synchronous and asynchronous functional brain networks using fMRI data, finding differences in global and local efficiency and age-related interactions.

This study compares stress and affect levels in middle-aged and younger adults during alcohol consumption and abstinence, finding age-related differences in stress reduction and affect.

The paper identifies increased connectivity between sensorimotor cortex and anterior cingulate cortex as a marker of physical resilience in older adults with high white matter hyperintensity volumes.

This paper introduces a mixed-modeling framework to analyze dynamic brain networks and their associations with phenotypic traits, demonstrating its use in linking fluid intelligence to dynamic connectivity patterns in resting-state fMRI data.

The paper introduces a regression framework to relate brain network distances to phenotypic traits and controls for confounding variables using simulation and HCP data.

The paper investigates if healthy alcohol consumers rate alcohol desire and craving similarly using related descriptors, finding consistent differences in ratings during drinking, abstinence, and alcohol cue exposure.