Ana Solodkin

The paper develops TVBase, a platform that projects biomedical knowledge onto a 3D brain atlas to support neuroimaging analysis and hypothesis generation.

The paper combines brain simulations with machine learning to improve dementia classification by integrating PET and MRI data with simulated electrophysiological features.

The paper demonstrates that each individual's brain has a converging optimal working point in The Virtual Brain model that predicts fMRI and EEG features, with inter-individual differences driven by structural connectivity.

The paper uses computational modeling to link molecular pathways with neural dynamics in Alzheimer’s disease, showing how Abeta burden affects brain activity and potential reversibility with memantine.

This paper introduces a novel diffusion tensor imaging (DTI) method to accurately delineate the rat basolateral amygdala (BLA) and validates it against histological techniques.

This study uses personalized Virtual Brain models to show that local and global brain dynamics correlate with cognitive differences in Alzheimer’s disease and related conditions.