Aaron Kucyi

The paper identifies distinct electrophysiological patterns in interdigitated default and frontoparietal networks using EEG-fMRI data.

This study shows that neuroimaging research on intimate partner violence underrepresents the most affected survivors due to biases in eligibility, participation, and quality control.

This paper introduces a multi-session simultaneous EEG-fMRI dataset with continuous behavior and mental experience measures from 24 healthy adults.

This study introduces and validates a method called real-time fMRI-triggered experience-sampling to capture spontaneous thoughts with improved temporal precision relative to neural activity.

The paper examines dynamic fMRI correlates of adolescent rumination and finds that adult models do not generalize, suggesting developmental differences in neural correlates of rumination.

The paper shows that brain sensitivity to heartbeat signals varies with momentary affective arousal during spontaneous thought, and this effect is stronger in individuals with higher trait anxiety.

The paper identifies a reliable brain state associated with trait mindfulness in adolescents using dynamic functional connectivity analysis of fMRI data.

The paper uses connectome predictive modeling to identify neural correlates of trait mindfulness subscales in resting-state fMRI data from three samples.

This study examines individual differences in neural representations of mind-wandering using dense sampling and functional MRI, finding both consistent and variable patterns across individuals.

The paper develops a functional brain network model to predict stimulus-independent, task-unrelated thought across different populations and contexts.

The paper predicts future changes in sedentary behavior using resting state functional connectivity and baseline measures in older adults.

The paper identifies two brain states during a sustained attention task, showing one is behaviorally optimal and the other suboptimal, and examines their modulation by motivation, mind wandering, and ADHD.

The paper examines dynamic anticorrelated activity between brain networks during attentional tasks and rest, finding time-lagged interactions linked to attentional performance.