Sébastien Arthaud

The paper develops two polygenic mouse models of depression, H-TST and H-FST, to identify biomarkers of antidepressant response in humans.

This study shows that automatic deep learning models for mouse sleep scoring struggle to generalize across labs due to signal variability and label noise, and proposes four robust models trained on diverse data.

This paper creates a transgenic mouse model that mimics human neuromelanin accumulation in catecholaminergic neurons, leading to age-related neurodegenerative deficits.