Vinod H. Srihari

This paper introduces a feedback approach to connectome-based predictive modeling to identify which brain systems standardized tests and clinical symptoms reflect, enabling better-targeted test development.

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 connectome-based predictive modeling to show that circuits related to clinical symptoms and cognitive deficits are localized in specific brain networks.

The paper develops a deep learning framework to classify first-episode psychosis using multimodal data from neuroimaging, EEG, and facial features.