Gerard Sanacora

The paper develops a data-driven method to identify individualized disordered connectivity patterns from fMRI data, revealing diverse neurobiological mechanisms underlying transdiagnostic psychiatric symptoms.

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.

This study shows that depletion of PFC GFAP+ astroglia induces anhedonia-like behavior, while their activation reverses stress-induced anhedonia, highlighting their role in depression.

This study identifies 178 independent risk loci for depression through a large meta-analysis across multiple cohorts, including fine-mapping and transcriptome-wide association findings.

This study shows that pretreatment with rapamycin increases the antidepressant response rate of ketamine at 2 weeks but does not affect its acute effects.