Sean E. Coursey

This study characterizes human cerebral cortex metabolic connectivity using PET-FDG data, finding a superior-inferior gradient driven by low-frequency signals.

The paper examines the relationship between fMRI-based network metrics and glucose metabolism across different brain states and diseases, finding state- and network-dependent metabolic associations.

This study uses EEG-PET-MRI to show how hemodynamic and metabolic dynamics change during wakefulness and NREM sleep, revealing coupled temporal patterns and distinct network activity.

This study shows that incorrect baseline modeling in fPET-FDG can create false metabolic activity patterns, affecting GLM analyses.