Marisa N. Spann

This study shows that flexible brain state engagement predicts cognitive control across multiple psychiatric disorders using machine learning and three transdiagnostic datasets.

The paper uses network control theory to show fetal brain controllability follows a U-shaped trajectory during pregnancy, co-developing with synaptic functions and synchronizing with maternal controllability changes.

The paper uses white-matter controllability at birth to predict social engagement and language outcomes in toddlers.

This study predicts brain age and deviations from normative trajectories in neonatal connectomes using structural and functional data from infants.

This study examines how maternal prenatal discrimination and acculturation affect fetal growth, birth outcomes, and infant brain connectivity in adolescent Latinx women.

The paper uses task-based functional MRI connectomes to predict cognitive phenotypes across psychiatric diseases and shows differences in connectomes by disease category and symptom severity.

This study uses connectome-based predictive modeling on fMRI data to identify functional brain networks that predict social ability measures in autism spectrum disorder.