Cole Harris Korponay

This paper identifies physiological arousal as a major source of individual differences in functional brain networks, showing strong correlations between arousal and network properties across multiple sessions and samples.

The paper identifies human striatal population states resembling canonical SPN states and shows their modulation by task demands, arousal, and behavior using fMRI data.

QuNex Recipes provide a framework for creating executable, human-readable workflows to ensure reproducibility in neuroimaging research.

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

The paper uses unsupervised machine learning to analyze fMRI data from an emotional face matching task, identifying large-scale brain networks and their relation to cognition and mental health.

The paper identifies a systematic inflation of functional connectivity in fMRI scans over time and proposes a solution to mitigate this artifact.

The paper curates and provides analysis-ready diffusion MRI data for pediatric brain white-matter research, including automated quality control using a trained neural network.

The paper uses fMRI temporal-unwrapping to analyze corticostriatal communication timing, finding distinct temporal organization of node-pair coactivation patterns.

The paper identifies distinct misconfigurations of striatal connectivity profiles in smokers, revealing trait and state-specific alterations linked to nicotine dependence severity.

The paper quantifies functional connectivity profile laterality in corticostriatal circuits, identifies laterality hotspots, and shows their predictive value for language task performance.

This study maps corticostriatal projections from macaque area 44, showing distinct connectivity patterns in the caudate nucleus and putamen, and their convergence with motor and non-motor projections.