Galia Avidan

The paper analyzes resting-state fMRI-electrogastrogram data to reveal the time-averaged and time-varying structure of the gastric network, showing it is dynamically reconfiguring and coordinated by multisensory integration.

This study examines inter-subject functional connectivity during movie watching and finds correlations with face recognition scores, revealing dynamics in attentional and memory networks.

This paper introduces connectome embedding to model individual differences in brain structure-function-behavior relationships, showing improved prediction of age and intelligence.

The paper develops a deep learning framework to predict brain age from MRI scans and identifies brain regions associated with aging, showing improved replicability and alignment with existing literature.

This study uses fMRI to compare neural circuit topology for face processing in congenital prosopagnosia and controls, finding altered connectivity patterns and severity-dependent differences.