Carrisa V. Cocuzza

The paper examines brain network dynamics in individuals with and without psychiatric diagnoses, finding that these dynamics can differentiate symptom profiles more effectively than diagnostic categories.

The paper investigates the functional roles of hierarchical and direct connectivity pathways in human visual cortex using empirical neural network models and 7T MRI data, finding they generate complementary representational dynamics.

The paper shows longer scans improve prediction accuracy in brain-wide association studies while reducing costs, with 30-minute scans being the most cost-effective.

This paper introduces DELSSOME, a deep learning framework that accelerates biophysical brain circuit model optimization, enabling faster parameter estimation and lifespan trajectory analysis of cortical E/I ratios.

The paper examines how specific lifetime stressor characteristics and brain network connectivity predict anxiety and depression symptoms in adolescents.

The paper demonstrates that distributed network flows can generate localized visual category selectivity in human visual cortex using fMRI data and computational models.

This paper identifies widespread functional connectivity differences in cocaine use disorder (CUD) and links these patterns to dopamine D2/3 receptor densities across the brain.

The paper shows that brain network features predicting internalizing and externalizing traits differ between children and adults, with more similarity within categories in children and distinct features in adults.

The paper quantifies the functional importance of task-state functional connectivity in shaping cognitive task activations and finds it improves prediction accuracy beyond resting-state connectivity.

The paper investigates dynamic network properties of cognitive control networks in humans using a high-control-demand task, revealing distinct roles for the frontoparietal and cingulo-opercular networks.

The paper shows that task-evoked activations inflate task-state functional connectivity estimates and demonstrates that flexible modeling of hemodynamic responses effectively corrects this inflation.