Joseph Giorgio

This study shows that dopamine compensates for amyloid-induced dysfunction in the default mode network to support learning in preclinical Alzheimer's disease.

This paper identifies a posterior predominant amyloid PET binding pattern in multiple cohorts, showing its clinical and biological relevance and suggesting the need for more nuanced analysis methods.

The paper introduces CoMA-UNet, a method to synthesize tau PET from MRI using covariates, showing strong agreement with true PET and utility in clinical tasks.

This study uses [18F]-SynVesT-1 PET to analyze synaptic density in aging and Alzheimer's Disease, finding associations with amyloid-beta, tau, and cognitive performance.

This study investigates adaptive visual processing in the human brain using ultra-high field imaging, revealing suppressive recurrent processing and dissociable connectivity mechanisms.

This study uses machine learning to predict future regional tau accumulation in asymptomatic and early Alzheimer's disease using multimodal data, showing improved accuracy over traditional measures.