Computational neuroscience and Artificial Intelligence

Track directors: Jonathan Vacher (Université Paris Cité) et Benoît Girard (CNRS / Sorbonne Université)
Capacity: 15

General organization

The master’s student must register to one of the tracks. These tracks ensure the acquisition of genuine expertise in the concepts, methods, and techniques specific to each discipline, enhancing the clarity of skills associated with the diploma. The program establishes a common cultural foundation from the first year (M1) through a core curriculum and introductory courses to the different disciplines. In the second year (M2), the majority of courses are fully interdisciplinary and open to students from all tracks. Our goal is to cultivate cognitivists equipped with both robust disciplinary expertise and a broad interdisciplinary culture, essential elements for fostering meaningful collaboration across disciplines.

M1 – Semester 1

Master core curriculum

CORE-102 Data camp (3 ECTS)
CORE-104 Ethics in cognitive sciences (3 ECTS), Katie Evans, Anouk Barberousse, Raja Chatila

Track core curriculum

NEURO-101 Introduction to Cognitive Neurocience (3 ECTS), Claire Sergent, Pierre Bourdillon
NEURO-102 Basic methods in Neuroimaging (3 ECTS), Laura Dugué
PSYCH-101 Introduction to Cognitive Psychology (3 ECTS), Thérèse Collins
NCIA-101 Introduction to Computational Neuroscience and AI (3 ECTS), Mehdi Khamassi, Benoît Girard

Options : 12 or 14 ECTS among these options

INT-101 Internship (1 day/week) (6 ECTS)
NEURO-103 Advanced methods in Neuroimaging (3 ECTS), Laura Dugué
PHILO-101 Scientific reasoning (5 ECTS), Isabelle Drouet
LING-101 Introduction au Traitement Automatique des Langues (in French) (3 ECTS), Guillaume Wisniewski
LING-102 Machine Learning for Natural Language Processing 2 (6 ECTS), Marie Candito
NEURO-104 Neuropsychology as a central paradigm in cognitive science (3 ECTS), Laurent Cohen, Paolo Bartolomeo
NEURO-SU-101 Fundamentals in Neuroscience (3 ECTS), Régis Lambert, Stéphanie Daumas
INFO-SU-101 Logique et représentation des connaissances (in French) (6 ECTS), Nicolas Maudet, Gauvain Bourgne
EXT-101 (external course) (6 ECTS)
EXT-102 (external course) (3 ECTS)

M1 – Semester 2

Master core curriculum

CORE-101 Experimental approach (3 ECTS), Christophe Pallier, Mark Wexler
CORE-103 How to write a literature review? (3 ECTS), Jonathan Vacher

Track core curriculum

NCIA-201 Advanced Computational Neuroscience (6 ECTS), Bruno Delord
NCIA-202 Bayesian Modeling of brain and behavior (3 ECTS), Jonathan Vacher, Jean Daunizeau
INFO-SU-201 Machine Learning (1st half) (lectures in French, slides and practical labs in English) (3 ECTS), Nicolas Baskiotis

Options : 12 ECTS among these options

CORE-102 Data camp (3 ECTS)
INT-201 Internship (1 day/week) (mandatory if not taken during S1) (6 ECTS)
NCIA-203 Hacking Cognition (3 ECTS), Laura Dugué
NCIA-204 Model-based neuroimaging (3 ECTS), Laura Dugué
NEURO-201 Advanced Cognitive Neuroscience (3 ECTS), Louise Kirsch
LING-201 Machine Learning for Natural Language Processing 1 (6 ECTS), Guillaume Wisniewski
SOC-201 Applying cognitive sciences (3 ECTS), Thérèse Collins
INFO-SU-202 Machine Learning (2nd half) (lectures in French, slides and practical labs in English) (3 ECTS), Nicolas Baskiotis
INFO-SU-203 Interfaces Humain-Machine (lectures in French, slides in English) (6 ECTS), Gilles Bailly, Baptiste Caramiaux
INFO-SU-205 Intelligence Artificielle et Manipulation Symbolique de l’Information (in French) (6 ECTS), Christophe Marsala, Gauvain Bourgne
INFO-SU-206 Apprentissage pour la Robotique (6 ECTS), Olivier Sigaud, Nicolas Bredèche, Stéphane Doncieux
MBIO-SU-201 Modèles mathématiques en neurosciences (in French) (6 ECTS), Michèle Thieullen, Delphine Salort

M2 – Semester 3

Master core curriculum

INT-301 Internship preparation (1 day/week) (6 ECTS)

Options : 18 ECTS among these options

NCIA-301 Computational psychiatry (6 ECTS), Fabien Vinckier, Philippe Domenech, Renaud Jardri
NCIA-302 Advanced bayesian modeling and model comparison (6 ECTS), Jonathan Vacher, Jean Daunizeau
NCIA-303 Integrative modeling of living organisms (6 ECTS), Romain Brette
NCIA-304 Reinforcement learning applied to Cognitive Science (6 ECTS), Mehdi Khamassi, Olivier Sigaud, Benoît Girard
NCIA-305 Human-AI Interactions (6 ECTS), Gilles Bailly, Baptiste Caramiaux

Options : 6 ECTS among these options

CORE-104 Ethics in Cognitive Sciences (only for direct entrance to M2) (3 ECTS), Katie Evans, Anouk Barberousse, Raja Chatila
IPS-SU-301 Human experimentation and statistics (only for direct entrance to M2) (3 ECTS), Stéphane Genet, Emmanuel Guigon
NEURO-301 Attention (6 ECTS), Laura Dugué
NEURO-302 Decision-making (6 ECTS), Mathias Pessiglione
LING-301 Computational language modeling and cognition (6 ECTS), Benoît Crabbe
MMA-UPC-301 Machine learning and optimization (6 ECTS), Jonathan Vacher
MMA-UPC-302 Generative modeling of images (6 ECTS), Jonathan Vacher
MVA-301 Algorithms for speech and natural language processing (6 ECTS), Emmanuel Dupoux
INFO-SU-301 Advanced machine learning (6 ECTS), Patrick Gallinari
INFO-SU-302 Reinforcement learning (RL) and advanced deep RL (6 ECTS), Olivier Sigaud, Patrick Gallinari
INFO-SU-303 Reconnaissance des formes et IA (in French) (6 ECTS), Matthieu Cord
INFO-SU-304 Explainable AI (6 ECTS), Marie-Jeanne Lesot
INFO-SU-305 IA pour la robotique et les sciences cognitives (lectures in French, slides in English) (6 ECTS), Nicolas Bredèche
MBIO-SU-301 Modèles probabilistes en neurosciences (in French) (6 ECTS), Michèle Thieullen
MBIO-SU-302 Fonctionnement des réseaux de neurones : analyse mathématique (in French) (6 ECTS), Delphine Salort
iMOV-SU-301 Vision from retina to primary visual cortex (6 ECTS), Gaël Orieux, Grégory Gauvain
iMOV-SU-302 Physiology of perception (6 ECTS), Olivier Marre, Grégory Gauvain
MSR-SU-301 Perception and action (3 ECTS), Emmanuel Guigon, Malika Auvray
MSR-SU-302 Social robotics (6 ECTS), Mohamed Chetouani
CNN-Saclay-301 Closed-loop neuroscience (3 ECTS), Valérie Ego-Stengel
CNN-Saclay-302 Dynamical system and computational neuroscience (3 ECTS), Antoine Chaillet
M2A-SU-301 Apprentissage statistique (in French) (3 ECTS), Gérard Biau
M2A-SU-302 Introduction à l’apprentissage automatique (in French) (3 ECTS), Maxime Sangnier
M2A-SU-303 Méthodes du premier ordre pour l’optimisation non convexe et non lisse (in French) (3 ECTS), Pauline Tan
M2A-SU-304 Optimisation stochastique & généralisation pour le ML (in French) (3 ECTS), Claire Boyer

M2 – Semester 4

Master core curriculum

INT-401 Internship (full time) (30 ECTS)