Mnemosyne: mnemonic synergy


Voir la version en français

Mnemosyne is a research team in computer science modeling neural networks, with the aim to study synergies between different kinds of learning. Our objective is to better understand these synergies and the impact of certain dysfunctions by realizing efficient computer models and by driving reproducible experiments dedicated to the emulation of autonomous behaviors and the realization of cognitive functions. They have an impact in the fields of Machine Learning, Artificial Intelligence and Situated Cognition, but they also question our neuroscientific and medical colleagues and offer them new objects of study at the level of neuronal and behavioral phenomena. Our research can be presented according to themes corresponding to learn to predict values and to learn to control behavior.

Selected publications

Team leader
Nicolas Rougier

Team member(s)

Nicolas Rougier (Team leader)

Chercheurs, Praticiens hospitaliers...

André Garenne (University Teacher- Researcher)
Frédéric Alexandre (Team leader)
Thierry Vieville (Researcher - PhD (DR))
Xavier Hinaut (Researcher)
Amélie Aussel (Researcher)

Ingénieur(e)s, technicien(ne)s


Luca Pedrelli


Pramod Kaushik
Guillaume Padiolleau
Snigdha Dagar
Remya Sankar
Nikolaos Vardalakis
Chloé Mercier
Hugo Chateau-Laurent
Subba Reddy Oota
Maeva Andriantsoamberomanga