Computational Neuroscience


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The Computational Neuroscience team 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)

Chercheurs, Praticiens hospitaliers...

Frédéric Alexandre (Researcher)
Thierry Vieville (Researcher - PhD (DR))
Xavier Hinaut (Researcher)
Amélie Aussel (Researcher)

Ingénieur(e)s, technicien(ne)s



Snigdha Dagar
Nikolaos Vardalakis
Chloé Mercier
Hugo Chateau-Laurent
Subba Reddy Oota
Maeva Andriantsoamberomanga
Fjola Hyseni
Naomi Chaix-Eichel
Nathan Trouvain

Neuropsychologist(s) and speech therapist(s)

Ingénieur(s) hospitalier(s) et ARC