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Biographie courte


Après un diplôme d'ingénieur à l'ENSIIE (anciennement sous la tutelle du CNAM) à Evry, j'ai effectué un DEA (Master) de Sciences Cognitives puis une thèse entre l'Université Pierre et Marie Curie et le Collège de France dirigée par Agnès Guillot et Sidney I. Wiener. Cette thèse a porté 1) d'une part, sur l'étude des mécanismes du cerveau qui permettent aux mammifères de se représenter l'espace, d'y naviguer, de choisir leurs actions à entreprendre et d'apprendre par essai-erreur à adapter ce choix à l'environnement ; 2) d'autre part, sur la conception, en s'inspirant de ces mécanismes, d'algorithmes permettant aux robots de faire preuve de plus d'adaptativité et d'autonomie dans des environnements changeants. En 2008, j'ai effectué un séjour au Japon dans le laboratoire de Kenji Doya à Okinawa Institute of Science and Technology. Puis j'ai effectué un post-doctorat à l'INSERM à Lyon, où mes travaux étaient à l'interface entre l'équipe de neurophysiologie d'Emmanuel Procyk, et l'équipe de modélisation et robotique de Peter F. Dominey.

Depuis 2010, je suis chargé de recherches au CNRS, affecté à l'Institut des Systèmes Intelligents et de Robotique (ISIR UMR 7222) au sein de l'Université Pierre et Marie Curie (UPMC) - Paris 6. J'ai obtenu mon Habilitation à Diriger des Recherches (HDR) en Biologie à l'UPMC le 6 mai 2014.


Journal articles49 documents

  • Marios Panayi, Mehdi Khamassi, Simon Killcross. The rodent lateral orbitofrontal cortex as an arbitrator selecting between model-based and model-free learning systems. Behavioral Neuroscience, American Psychological Association, In press, ⟨10.1037/bne0000454⟩. ⟨hal-03107588v2⟩
  • Evelien H.S. Schut, Irene Navarro Lobato, Alejandra Alonso, Steven Smits, Mehdi Khamassi, et al.. The Object Space Task reveals increased expression of cumulative memory in a mouse model of Kleefstra syndrome. Neurobiology of Learning and Memory, Elsevier, 2020, 173, pp.107265. ⟨10.1016/j.nlm.2020.107265⟩. ⟨hal-02941978⟩
  • Mehdi Khamassi, Benoît Girard. Modeling awake hippocampal reactivations with model-based bidirectional search. Biological Cybernetics (Modeling), Springer Verlag, 2020, ⟨10.1007/s00422-020-00817-x⟩. ⟨hal-02504897⟩
  • Marco Wittmann, Elsa Fouragnan, Davide Folloni, Miriam Klein-Flügge, Bolton Chau, et al.. Global reward state affects learning and activity in raphe nucleus and anterior insula in monkeys. Nature Communications, Nature Publishing Group, 2020, 11 (1), ⟨10.1038/s41467-020-17343-w⟩. ⟨hal-03098645⟩
  • Mariacarla Staffa, Silvia Rossi, Adriana Tapus, Mehdi Khamassi. Special Issue on Behavior Adaptation, Interaction, and Artificial Perception for Assistive Robotics. International Journal of Social Robotics, Springer, 2020, 12, pp.613 - 616. ⟨10.1007/s12369-020-00655-8⟩. ⟨hal-02864719⟩
  • Abolfazl Zaraki, Mehdi Khamassi, Luke Wood, Gabriella Lakatos, Costas Tzafestas, et al.. A Novel Reinforcement-Based Paradigm for Children to Teach the Humanoid Kaspar Robot. International Journal of Social Robotics, Springer, 2019, ⟨10.1007/s12369-019-00607-x⟩. ⟨hal-02408941⟩
  • Lisa Genzel, Evelien Schut, Tim Schröder, Ronny Eichler, Mehdi Khamassi, et al.. The object space task shows cumulative memory expression in both mice and rats. PLoS Biology, Public Library of Science, 2019, 17 (6), pp.e3000322. ⟨10.1371/journal.pbio.3000322⟩. ⟨hal-02323650⟩
  • François Cinotti, Virginie Fresno, Nassim Aklil, Etienne Coutureau, Benoît Girard, et al.. Dopamine blockade impairs the exploration-exploitation trade-off in rats. Scientific Reports, Nature Publishing Group, 2019, 9 (1), ⟨10.1038/s41598-019-43245-z⟩. ⟨hal-02121649⟩
  • François Cinotti, Alain Marchand, Matthew Roesch, Benoît Girard, Mehdi Khamassi. Impacts of inter-trial interval duration on a computational model of sign-tracking vs. goal-tracking behaviour. Psychopharmacology, Springer Verlag, 2019. ⟨hal-02270920⟩
  • Mehdi Khamassi, Raja Chatila, Alain Mille. Éthique et sciences cognitives. Intellectica - La revue de l’Association pour la Recherche sur les sciences de la Cognition (ARCo), Association pour la Recherche sur la Cognition, 2019. ⟨hal-02324092⟩
  • George Velentzas, Theodore Tsitsimis, Iñaki Rañó, Costas Tzafestas, Mehdi Khamassi. Adaptive reinforcement learning with active state-specific exploration for engagement maximization during simulated child-robot interaction. Paladyn: Journal of Behavioral Robotics, De Gruyter, 2018, 9 (1), pp.235-253. ⟨10.1515/pjbr-2018-0016⟩. ⟨hal-02324073⟩
  • Romain Cazé, Mehdi Khamassi, Lise Aubin, Benoît Girard. Hippocampal replays under the scrutiny of reinforcement learning models. Journal of Neurophysiology, American Physiological Society, 2018, ⟨10.1152/jn.00145.2018⟩. ⟨hal-02323528⟩
  • Mehdi Khamassi, George Velentzas, Theodore Tsitsimis, Costas Tzafestas. Robot Fast Adaptation to Changes in Human Engagement During Simulated Dynamic Social Interaction With Active Exploration in Parameterized Reinforcement Learning. IEEE Transactions on Cognitive and Developmental Systems, Institute of Electrical and Electronics Engineers, Inc, 2018, 10 (4), pp.881-893. ⟨10.1109/TCDS.2018.2843122⟩. ⟨hal-02324064⟩
  • Laurent Dollé, Ricardo Chavarriaga, Agnès Guillot, Mehdi Khamassi. Interactions of spatial strategies producing generalization gradient and blocking: A computational approach. PLoS Computational Biology, Public Library of Science, 2018, 14 (4), pp.e1006092. ⟨10.1371/journal.pcbi.1006092⟩. ⟨hal-02324053⟩
  • Nassim Aklil, Benoît Girard, Ludovic Denoyer, Mehdi Khamassi. Sequential Action Selection and Active Sensing for Budgeted Localization in Robot Navigation. International Journal of Semantic Computing, World Scientific, 2018, 12 (01), pp.109-127. ⟨10.1142/S1793351X18400068⟩. ⟨hal-02324047⟩
  • Sophie Bavard, Maël Lebreton, Mehdi Khamassi, Giorgio Coricelli, Stefano Palminteri. Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences. Nature Communications, Nature Publishing Group, 2018, 9, pp.4503. ⟨10.1038/s41467-018-06781-2⟩. ⟨hal-01927184⟩
  • Guillaume Viejo, Benoît Girard, Emmanuel Procyk, Mehdi Khamassi. Adaptive coordination of working-memory and reinforcement learning in non-human primates performing a trial-and-error problem solving task. Behavioural Brain Research, Elsevier, 2018, 355, pp.76-89. ⟨10.1016/j.bbr.2017.09.030⟩. ⟨hal-01624253⟩
  • Brian Lee, Ronny Gentry, Gregory Bissonette, Rae Herman, John Mallon, et al.. Manipulating the revision of reward value during the intertrial interval increases sign tracking and dopamine release. PLoS Biology, Public Library of Science, 2018, 16 (9), pp.e2004015. ⟨10.1371/journal.pbio.2004015⟩. ⟨hal-02324085⟩
  • Raja Chatila, Erwan Renaudo, Mihai Andries, Omar Chavez-Garcia, Pierre Luce-Vayrac, et al.. Toward Self-Aware Robots. Frontiers in Robotics and AI, Frontiers Media S.A., 2018, 5, pp.88. ⟨10.3389/frobt.2018.00088⟩. ⟨hal-01856931⟩
  • Nicolas Rougier, Konrad Hinsen, Frédéric Alexandre, Thomas Arildsen, Lorena Barba, et al.. Sustainable computational science: the ReScience initiative. PeerJ Computer Science, PeerJ, 2017, 3, pp.e142. ⟨10.7717/peerj-cs.142⟩. ⟨hal-01592078⟩
  • Guillaume Viejo, Benoît Girard, Mehdi Khamassi. [Re] Speed/accuracy trade-off between the habitual and the goal-directed processes. The ReScience journal, GitHub, 2016, 2 (1), ⟨10.5281/zenodo.45852⟩. ⟨hal-01524285⟩
  • Raja Chatila, Mehdi Khamassi. La conscience d'une machine. Interstices, INRIA, 2016. ⟨hal-01352801⟩
  • Mehdi Khamassi, Stéphane Doncieux. Nouvelles approches en Robotique Cognitive. Intellectica - La revue de l’Association pour la Recherche sur les sciences de la Cognition (ARCo), Association pour la Recherche sur la Cognition, 2016, 2016/1 (65), pp.7-25. ⟨hal-01375651⟩
  • Benoît Girard, Mehdi Khamassi. Coopération de systèmes d’apprentissage par renforcement multiples.. Techniques de l'Ingenieur, Techniques de l'ingénieur, 2016, pp.S7793. ⟨hal-01524743⟩
  • Mehdi Khamassi, Benoît Girard, Aurélie Clodic, Sandra Devin, Erwan Renaudo, et al.. Integration of Action, Joint Action and Learning in Robot Cognitive Architectures. Intellectica - La revue de l’Association pour la Recherche sur les sciences de la Cognition (ARCo), Association pour la Recherche sur la Cognition, 2016, 2016/1 (65), pp.169-203. ⟨10.3406/intel.2016.1794⟩. ⟨hal-01375666⟩
  • Mehdi Khamassi, René Quilodran, Pierre Enel, Peter Dominey, Emmanuel Procyk. Behavioral Regulation and the Modulation of Information Coding in the Lateral Prefrontal and Cingulate Cortex. Cerebral Cortex, Oxford University Press (OUP), 2015, 25 (9), pp.3197-3218. ⟨10.1093/cercor/bhu114⟩. ⟨hal-01219972⟩
  • Stefano Palminteri, Mehdi Khamassi, Mateus Joffily, Giorgio Coricelli. Contextual modulation of value signals in reward and punishment learning. Nature Communications, Nature Publishing Group, 2015, pp.article 8096. ⟨10.1038/ncomms9096⟩. ⟨halshs-01236045⟩
  • Guillaume Viejo, Mehdi Khamassi, Andrea Brovelli, Benoît Girard. Modeling choice and reaction time during arbitrary visuomotor learning through the coordination of adaptive working memory and reinforcement learning. Frontiers in Behavioral Neuroscience, Frontiers, 2015, 9, pp.225. ⟨10.3389/fnbeh.2015.00225⟩. ⟨hal-01215419⟩
  • Erwan Renaudo, Benoît Girard, Raja Chatila, Mehdi Khamassi. Respective Advantages and Disadvantages of Model-based and Model-free Reinforcement Learning in a Robotics Neuro-inspired Cognitive Architecture. Procedia Computer Science, Elsevier, 2015, 71, pp.178-184. ⟨10.1016/j.procs.2015.12.194⟩. ⟨hal-01250157⟩
  • Florian Lesaint, Olivier Sigaud, Jeremy Clark, Shelly Flagel, Mehdi Khamassi. Experimental predictions drawn from a computational model of sign-trackers and goal-trackers. Journal of Physiology - Paris, Elsevier, 2015, 109 (1-3), pp.78-86. ⟨10.1016/j.jphysparis.2014.06.001⟩. ⟨hal-01219979⟩
  • Pierre de Loor, Alain Mille, Mehdi Khamassi. Intelligence artificielle: l'apport des paradigmes incarnés. Intellectica - La revue de l’Association pour la Recherche sur les sciences de la Cognition (ARCo), Association pour la Recherche sur la Cognition, 2015, Sciences de la cognition: réflexions prospectives, 2 (64), pp.27-52. ⟨hal-01250421⟩
  • Florian Lesaint, Olivier Sigaud, Shelly Flagel, Terry Robinson, Mehdi Khamassi. Modelling Individual Differences in the Form of Pavlovian Conditioned Approach Responses: A Dual Learning Systems Approach with Factored Representation. PLoS Computational Biology, Public Library of Science, 2014, 10 (2), pp.e1003466. ⟨10.1371/journal.pcbi.1003466⟩. ⟨hal-00947727⟩
  • Florian Lesaint, Olivier Sigaud, Mehdi Khamassi. Accounting for Negative Automaintenance in Pigeons: A Dual Learning Systems Approach and Factored Representations. PLoS ONE, Public Library of Science, 2014, ⟨10.1371/journal.pone.0111050⟩. ⟨hal-01219998⟩
  • Angelo Arleo, Cyril Dejean, Pierre Allegraud, Mehdi Khamassi, Michaël Zugaro, et al.. Optic Flow Stimuli Update Anterodorsal Thalamus Head Direction Neuronal Activity in Rats. Journal of Neuroscience, Society for Neuroscience, 2013, 33 (42), pp.16790-16795. ⟨10.1523/JNEUROSCI.2698-13.2013⟩. ⟨hal-02137209⟩
  • Ignasi Cos, Mehdi Khamassi, Benoît Girard. Modeling the Learning of Biomechanics and Visual Planning for Decision-Making of Motor Actions.. Journal of Physiology - Paris, Elsevier, 2013, 107 (5), pp.399-408. ⟨10.1016/j.jphysparis.2013.07.004⟩. ⟨hal-01000837⟩
  • Mark Humphries, Mehdi Khamassi, Kevin Gurney. Dopaminergic control of the exploration-exploitation trade-off via the basal ganglia. Frontiers in Neuroscience, Frontiers, 2012, 6 (9), pp.1-14. ⟨10.3389/fnins.2012.00009⟩. ⟨hal-00688928⟩
  • Ken Caluwaerts, Mariacarla Staffa, Steve N'Guyen, Christophe Grand, Laurent Dollé, et al.. A biologically inspired meta-control navigation system for the Psikharpax rat robot.. Bioinspiration and Biomimetics, IOP Publishing, 2012, 7 (2), pp.025009. ⟨10.1088/1748-3182/7/2/025009⟩. ⟨hal-01000945⟩
  • Mehdi Khamassi, Mark Humphries. Integrating cortico-limbic-basal ganglia architectures for learning model-based and model-free navigation strategies. Frontiers in Behavioral Neuroscience, Frontiers, 2012, ⟨10.3389/fnbeh.2012.00079⟩. ⟨hal-01219958⟩
  • Mehdi Khamassi, Stéphane Lallée, Pierre Enel, Emmanuel Procyk, Peter Dominey. Robot cognitive control with a neurophysiologically inspired reinforcement learning model. Frontiers in Neurorobotics, Frontiers, 2011, 5 (1), pp.1-13. ⟨10.3389/fnbot.2011.00001⟩. ⟨hal-00688931⟩
  • Adrien Peyrache, Karim Benchenane, Mehdi Khamassi, Sidney Wiener, Francesco Battaglia. Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolution.. Journal of Computational Neuroscience, Springer Verlag, 2010, 29 (1-2), pp.309-25. ⟨10.1007/s10827-009-0154-6⟩. ⟨hal-00551873⟩
  • Adrien Peyrache, Karim Benchenane, Mehdi Khamassi, Sidney Wiener, Francesco Battaglia. Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolution. Journal of Computational Neuroscience, Springer Verlag, 2010, 29 (1-2), pp.309-325. ⟨10.1007/s10827-009-0154-6⟩. ⟨hal-02364218⟩
  • Adrien Peyrache, Karim Benchenane, Mehdi Khamassi, Sidney Wiener, Francesco Battaglia. Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolution. Journal of Computational Neuroscience, Springer Verlag, 2010, 29 (1-2), pp.309-325. ⟨10.1007/s10827-009-0154-6⟩. ⟨hal-02131243⟩
  • Karim Benchenane, Adrien Peyrache, Mehdi Khamassi, Patrick Tierney, Yves Gioanni, et al.. Coherent theta oscillations and reorganization of spike timing in the hippocampal- prefrontal network upon learning. Neuron, Elsevier, 2010, 6 (6), pp.921-936. ⟨10.1016/j.neuron.2010.05.013⟩. ⟨hal-00554482⟩
  • Adrien Peyrache, Karim Benchenane, Mehdi Khamassi, Sidney Wiener, Francesco Battaglia. Sequential Reinstatement of Neocortical Activity during Slow Oscillations Depends on Cells' Global Activity.. Frontiers in Systems Neuroscience, Frontiers, 2010, 3, pp.18. ⟨10.3389/neuro.06.018.2009⟩. ⟨hal-00551877⟩
  • Adrien Peyrache, Mehdi Khamassi, Karim Benchenane, Sidney Wiener, Francesco Battaglia. Replay of rule-learning related neural patterns in the prefrontal cortex during sleep.. Nature Neuroscience, Nature Publishing Group, 2009, 12 (7), pp.919-26. ⟨10.1038/nn.2337⟩. ⟨hal-00551868⟩
  • Mehdi Khamassi, Antonius B Mulder, Eiichi Tabuchi, Vincent Douchamps, Sidney I Wiener. Anticipatory reward signals in ventral striatal neurons of behaving rats.. European Journal of Neuroscience, Wiley, 2008, 28 (9), pp.1849-66. ⟨10.1111/j.1460-9568.2008.06480.x⟩. ⟨hal-00618294⟩
  • Jean-Arcady Meyer, Agnès Guillot, Benoît Girard, Mehdi Khamassi, Patrick Pirim, et al.. The Psikharpax project: Towards building an artificial rat. Robotics and Autonomous Systems, Elsevier, 2005, 50 (4), pp.211-223. ⟨10.1016/j.robot.2004.09.018⟩. ⟨hal-00016391⟩
  • Mehdi Khamassi, Loïc Lachèze, Benoît Girard, Alain Berthoz, Agnès Guillot. Actor-critic models of reinforcement learning in the basal ganglia: From natural to artificial rats. Adaptive Behavior, SAGE Publications, 2005, 13 (2), pp.131-148. ⟨10.1177/105971230501300205⟩. ⟨hal-00016390v2⟩
  • Michaël B Zugaro, Angelo Arleo, Cyril Déjean, Eric Burguière, Mehdi Khamassi, et al.. Rat anterodorsal thalamic head direction neurons depend upon dynamic visual signals to select anchoring landmark cues.. European Journal of Neuroscience, Wiley, 2004, 20 (2), pp.530-6. ⟨10.1111/j.1460-9568.2004.03512.x⟩. ⟨hal-00618299⟩

Book sections4 documents

  • Frédéric Alexandre, Peter Ford Dominey, Philippe Gaussier, Benoît Girard, Mehdi Khamassi, et al.. When Artificial Intelligence and Computational Neuroscience meet. Springer. A guided tour of artificial intelligence research, Interfaces and applications of artificial intelligence, 3, 2020, Interfaces and Applications of Artificial Intelligence, 978-3-030-06170-8. ⟨hal-01735123⟩
  • Mehdi Khamassi, Frédéric Decremps. APPRENTISSAGE DE LA DEMARCHE SCIENTIFIQUE ET DE L'ESPRIT CRITIQUE : UN ENSEIGNEMENT DE SORBONNE UNIVERSITE POUR LES ETUDIANTS D'AUJOURD'HUI, CITOYENS DE DEMAIN. Bertezene, S. and Vallat, D. (Eds.) Guider la raison qui nous guide : Agir et penser en complexité, 2019. ⟨hal-02324100⟩
  • Mehdi Khamassi, Elisabeth Pacherie. L'ACTION. Collins, T., Andler, D. and Tallon-Baudry, C. La cognition : du neurone à la société, Gallimard, 2018. ⟨hal-02324111⟩
  • Mehdi Khamassi, Pierre Enel, Peter Dominey, Emmanuel Procyk. Medial prefrontal cortex and the adaptive regulation of reinforcement learning parameters. Progress in Brain Research. Decision Making Neural and Behavioural Approaches, 2013, ⟨10.1016/B978-0-444-62604-2.00022-8⟩. ⟨hal-01628829⟩

Theses1 document

  • Mehdi Khamassi. Complementary roles of the rat prefrontal cortex and striatum in reward-based learning and shifting navigation strategies. Cognitive Sciences. Université Pierre et Marie Curie - Paris VI, 2007. English. ⟨tel-00688927⟩

Habilitation à diriger des recherches1 document

  • Mehdi Khamassi. Coordination of parallel learning processes in animals and robots. Neurons and Cognition [q-bio.NC]. Université Pierre et Marie Curie (UPMC) - Paris 6, 2014. ⟨tel-01074544⟩