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Angelo Arleo (DR2 CNRS, Team leader)


Adaptive NeuroComputation Group
Lab. of Neurobiology of Adaptive Processes (UMR7102)
University Pierre & Marie Curie
Box 12, Building B, 5th floor (room 519B)
9 quai St. Bernard, 75005 Paris, France
Phone: +33 (0)1 44 27 27 80
Fax: +33 (0)1 44 27 26 69
mail: angelo dot arleo at upmc dot fr

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My research is centred on adaptive neural computation and brain information processing. It focuses on the neural coding mechanisms that allow animals and humans to (i) interact with the environment through manifold sensory modalities, and (ii) learn contextual representations mediating high-level cognitive functions. The objective is to cross-link different neural levels, from single cell to system processing. Such an integrative approach calls upon a combination of theoretical and experimental neuroscience tools. Also, the validation of models through robotic implementations inscribes some aspects of my research within a neuroengineering framework. This interdisciplinary methodology finds its ground in my educational background (PhD in Computational Neuroscience and Neurorobotics at the Swiss Federal Institute of Technology of Lausanne (EPFL), Switzerland, and my further research training (postdoctoral training on in vivo electrophysiological recordings at the Collège de France-CNRS in Paris; Habilitation to Direct Research, HDR, in Life Science, University Pierre and Marie Curie, Paris).

In 2012 I was appointed as a Director of Research (DR2) at the French National Center for Scientific Research, CNRS, which I joined in 2007 as a CR1 researcher. Ever since 2007, I've been establishing the new Adaptive NeuroComputation (ANC) group, which is part of the unit UMR7102 of Neurobiology of Adaptive Processes, at the University Pierre & Marie Curie, in Paris. From 2004 to 2006, I have been working as an associate researcher at the Neural Information Dynamics group, at the SONY Computer Science Laboratory (CSL), in Paris. From 2001 to 2003, I held a post-doctoral position and then an associate researcher position at the Laboratory of Physiology of Perception and Action (LPPA), at the Collège de France-CNRS in Paris. From 1997 to 2000, I have been a Ph.D. student and an assistant researcher at the Laboratory of Computational Neuroscience, at the Swiss Federal Institute of Technology of Lausanne (EPFL). Finally, in 1996 I worked for my Master's Degree project at the Institute for Systems, Informatics and Safety of the Joint Research Centre (EU), Italy.

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2013

2012

2011

2010

2009

  • Martinet, L.-E.; Sheynikhovich, D.; Benchenane, K. and Arleo, A. Integrating a hippocampal and a cortical model for spatial navigation planning. In Fourth Computational Cognitive Neuroscience Conference (CCNC'09), Boston, USA, 2009.
  • Martinet, L.-E.; Sheynikhovich, D. and Arleo, A. A cortical column model for studying spatial navigation planning. In Quatrième conférence française de Neurosciences Computationnelles (Neurocomp'09), vol. 4, pages 24, Bordeaux, France, 2009.
  • Martinet, L.-E.; Sheynikhovich, D.; Meyer, J.-A. and Arleo, A. Multimodal encoding in a cortical model for spatial navigation planning. In BMC Neuroscience - Eighteenth Annual Computational Neuroscience Meeting, vol. 10 (Suppl1), pages 338, Berlin, Germany, 2009.
  • Passot, J.-B.; Rondi-Reig, L. and Arleo, A. Cerebellum and spatial cognition: a connectionist approach. In Verleysen, M., editors, Proceedings of the European Symposium on Artificial Neural Network: Advances in Computational Intelligence and Learning, vol. 17, pages 287-292, 2009.
  • Passot, J.-B.; Arabo, A.; Sheynikhovich, D.; Rondi-Reig, L. and Arleo, A. Studying the role of the cerebellum in spatial cognition through a neurocomputational approach. In Renaud, S. and Saighi, S., editors, Proceedings of the Conference NeuroComp, vol. 4, pages 26, 2009.
  • Passot, J.-B.; Rondi-Reig, L. and Arleo, A. Modeling cerebellar learning for spatial cognition. In BMC Neuroscience - Eighteenth Annual Computational Neuroscience Meeting, vol. 10 (Suppl1), pages 141, 2009.
  • Sheynikhovich, D.; Chavarriaga, R.; Strösslin, T.; Arleo, A. and Gerstner, W. Is there a geometric module for spatial orientation? Insights from a rodent navigation model. Psychological Review, 116(3): 540-566, 2009.
  • Sheynikhovich, D.; Otani, S. and Arleo, A. Role of dopamine for long-term plasticity in the rat prefrontal cortex: a computational model. In Renaud, S. and Saighi, S., editors, Proceedings of the Conference NeuroComp, vol. 4, pages 30, 2009.
  • Sheynikhovich, D.; Chavarriaga, R.; Strösslin, T.; Arleo, A. and Gerstner, W. Is There a Geometric Module for Spatial Orientation?: Insights From a Rodent Navigation Model. In Proceedings of the 4th Computational Cognitive Neuroscience Conf, Boston, USA, 2009.
  • Bologna, L. L.; Maggiali, M.; Sandini, G. and Arleo, A. Encoding/Decoding of spatiotemporal signals from an artificial touch sensor. In Proceedings of the Humanoids Conference, Paris, France, 2009.
  • Brasselet, R.; Johansson, R. S. and Arleo, A. Optimal context separation of spiking haptic signals by second-order somatosensory neurons. In Bengio, Y. et al., editors, Advances in Neural Information Processing Systems 22, vol. 22, pages 180-188, 2009.
  • Brasselet, R.; Johansson, R. S. and Arleo, A. Fast encoding/decoding of haptic microneurography data based on first spike latencies. In Renaud, S. and Saighi, S., editors, Proceedings of the Conference NeuroComp, vol. 4, pages 5, 2009.
  • Brasselet, B.; Johansson, R. S.; Coenen, O. J.-M. D. and Arleo, A. Fast encoding/decoding of haptic microneurography data based on first spike latencies. In BMC Neuroscience - Eighteenth Annual Computational Neuroscience Meeting, vol. 10 (Suppl1), pages 349, 2009.
  • Brasselet, R.; Johansson, R. S. and Arleo, A. Fast encoding/decoding of haptic microneurography data based on first-spike latency. In Proceedings of the Humanoids Conference, Paris, France, 2009.
  • Martinet, L-E.; Sheynikhovich, D.; Meyer, J-A. and Arleo, A. A cortical model for spatial navigation planning. In Journées Francophones Planification Décision Apprentissage (JFPDA 2009), Paris, France, 2009.
  • Martinet, L-E.; Sheynikhovich, D.; Meyer, J-A. and Arleo, A. Multimodal encoding in a cortical model for spatial navigation planning. In Colloque des Jeunes Chercheurs en Sciences Cognitives (CJCSC'09), Toulouse, France, 2009.

2008

  • Martinet, L.-E.; Fouque, B.; Passot, J.-B.; Meyer, J. A. and Arleo, A. Modelling the cortical columnar organisation for topological state-space representation, and action planning. In Asada, M. et al., editors, LNAI – Simulation of Adaptive Behavior, vol. 5040, pages 137-147, Springer-Verlag, 2008.
  • Martinet, L.-E.; Passot, J.-B.; Fouque, B.; Meyer, J. A. and Arleo, A. Map-Based Spatial Navigation: A Cortical Column Model for Action Planning. In Freksa, C. et al., editors, LNAI - Spatial Cognition, vol. 5248, pages 39-55, Springer-Verlag, 2008.
  • David, F. O.; Arleo, A.; Leresche, N. and Lambert, R. C. Dynamical effects of the T-current potentiation upon the oscillatory activity of thalamocortical neurons associated to sleep: a predictive model. In Proceedings of the Workshop on Mathematical Neuroscience, Edinburgh, UK, 2008.
  • David, F. O.; Arleo, A.; Leresche, N. and Lambert, R. C. Dynamical effects of the T-current potentiation upon the oscillatory activity of thalamocortical neurons associated to sleep: a predictive model. In FENS Abstracts, vol. 4: 047.8, 2008.

2007

2006

  • Bezzi, M.; Nieus, T.; Arleo, A.; D'Errico, A.; D'Angelo, E. and Coenen, O. J.-M. Quantitative characterization of information transmission in a single neuron. In Ijspeert, A. J. et al., editors, Proceedings of the EPFL-Latsis Symposium on Dynamical principles for neuroscience and intelligent biomimetic devices, Switzerland, 2006.
  • Bezzi, M.; Arleo, A.; Coenen, O. J.-M.; Nieus, T. and D'Angelo, E. Quantitative characterization of information transmission in a single neuron. In Alexandre, F. et al., editors, Proceedings of Neurocomp Conference, vol. 1, pages 134-136, 2006.

2005

  • Arleo, A.; Battaglia, F.; Déjean, C.; Zugaro, M. B. and Wiener, S. I. Rat anterodorsal thalamic head direction neurons are modulated by hippocampal theta rhythm. In Society for Neuroscience Abstracts, No. 198.18, Washington DC, USA, 2005.
  • Arleo, A. Thesis of Habilitation to Direct Research: The neural bases of spatial cognition and information processing in the brain. Life Science Dept, University Pierre and Marie Curie Paris, France, 2005.
  • Arleo, A. and Gerstner, W. Head direction cells and place cells in models for navigation and robotic applications. In Wiener, S. I. and Taube, J. S., editors, Head direction cells and the neural mechanisms of spatial orientation, chpt. 19, pages 433-457, MIT Press, 2005.
  • Bezzi, M.; Arleo, A. and Coenen, O. J.-M. D. Exploring the neural code by information theory. In Aquilano, D. et al., editors, Proceedings of the NeuroMat Workshop, pages 183-189, Milan, Italy, 2005.
  • Bezzi, M.; Nieus, T.; Arleo, A.; D'Angelo, E. and Coenen, O. J.-M. Reti neuronali impulsive per il controllo di robot: il progetto SpikeForce. In Atti del Convegno Nazionale ANIPLA-BIOSYS 2005, pages 226-235, Milan, Italy, 2005.
  • Rondi-Reig, L.; Petit, G.; Arleo, A and Burguiere, E. The starmaze: a new paradigm to characterize multiple spatial navigation strategies. In Measuring Behavior, 5th Int Conf on Methods and Techniques in Behavioral Research, pages 386-390, Wageningen, 2005.
  • D'Angelo, E.; Nieus, T.; Bezzi, M.; Arleo, A. and Coenen, O. J. M. Modeling synaptic transmission and quantifying information transfer in the granular layer of the cerebellum. In Cabestany, J. et al., editors, LNCS - Computational Intelligence and Bioinspired Systems, vol. 3512, pages 107-114, 2005.
  • d'Erfurth, A.; Peyrache, A.; Guillot, A. and Arleo, A. Un modèle computationnel biomimétique de navigation pour le robot-rat Psikharpax. In Guéré, E., editors, Proceedings of the National Conference RJCIA, pages 327-330, resses Universitaires Grenoble, 2005.
  • Coenen, O. J. M.; Bezzi, M.; Arleo, A.; Nieus, T.; D'Errico, A. and D'Angelo, E. Quantitative characterization of information transmission in a single neuron. In Society for Neuroscience Abstracts, vol. No. 823.3, Washington DC, USA, 2005.
  • Boucheny, C.; Brunel, N. and Arleo, A. A continuous attractor network model without recurrent excitation: maintenance and integration in the head direction cell system. Journal of Computational Neuroscience, 18(2): 205-227, 2005.
  • Burguière, E.; Arleo, A.; Hojjati, M.; Elgersma, Y.; De Zeeuw, C. I.; Berthoz, A. and Rondi-Reig, L. Spatial navigation impairment in mice lacking cerebellar LTD: a motor adaptation deficit?. Nature Neuroscience, 8(10): 1292-1294, 2005.

2004

  • Arleo, A.; Smeraldi, F. and Gerstner, W. Cognitive navigation based on nonuniform Gabor space sampling, unsupervised growing networks, and reinforcement learning. IEEE Transactions on Neural Networks, 15(3): 639-652, 2004.
  • Wiener, S. I.; Arleo, A.; Déjean, C.; Boucheny, C.; Khamassi, M. and Zugaro, M. B. Optic field flow signals update the activity of head direction cells in the rat anterodorsal thalamus. In FENS Abstracts, vol. 2: A007.19, Lisbon, Portugal, 2004.
  • Arleo, A.; Boucheny, C.; Degris, T.; Brunel, N. and Wiener, S. I. Head direction cells and spatial orientation in rats: Experimental findings and computational modeling. In Proceedings of the Workshop on Neurorobotic Models in Neuroscience and Neuroinformatics, Los Angeles, USA, 2004.
  • Arleo, A.; Déjean, C.; Boucheny, C.; Khamassi, M.; Zugaro, M.B. and Wiener, S. I. Optic field flow signals update the activity of head direction cells in the rat anterodorsal thalamus. In Proceedings of the XXIII Int Congress of the Barany Society, Paris, France, 2004.
  • Arleo, A.; Degris, T.; Boucheny, C. and Wiener, S. I. The neural basis of spatial orientation in rats: Electrophysiology, computational modeling, and robotics. In Meyer, J.-A. and Guillot, A., editors, Proceedings of the Int. Conference Towards Artificial Rodents, Paris, France, 2004.
  • Zugaro, M. B.; Arleo, A.; Déjean, C.; Burguière, E.; Khamassi, M. and Wiener, S. I. Rat anterodorsal thalamic head direction neurons depend upon dynamic visual signals to select anchoring landmark cues. European Journal of Neuroscience, 20(2): 530-536, 2004.
  • Degris, T.; Lachèze, L.; Boucheny, C. and Arleo, A. A spiking neuron model of head-direction cells for robot orientation. In Schaal, S. et al., editors, Proceedings of the Eighth International Conference on Simulation of Adaptive Behavior, From Animals to Animats, vol. 8, pages 255-263, MIT Press, 2004.
  • Degris, T.; Sigaud, O.; Wiener, S. I. and Arleo, A. Rapid response of head direction cells to reorienting visual cues: A computational model. Neurocomputing, 58-60C: 675-682, 2004.
  • Burguière, E.; Rutteman, M.; Arleo, A.; Wiener, S. I.; Zeeuw, C.I. De; Berthoz, A. and Rondi-Reig, L. Deficit during spatial navigation in L7-PKCI mice lacking cerebellar Long-Term Depression: a motor learning problem?. In FENS Abstracts, vol. 2, A042.5, Lisbon, Portugal, 2004.
  • Coenen, O. J.-M.; Boucheny, C.; Bezzi, M.; Marchal, D.; Arnold, M. P.; Ros, E.; Carillo, R. O. E. M.; Gis, R.; Barbour, B.; Arleo, A.; Nieus, T. and D'Angelo, E. Adaptive spiking cerebellar models and real-time simulations. In Society for Neuroscience Abstracts, No. 827.4, San Diego, USA, 2004.
  • Bezzi, M.; Nieus, T.; Arleo, A.; D'Angelo, E. and Coenen, O. J.-M. Information transfer at the mossy fiber-granule cell synapse of the cerebellum. In Society for Neuroscience Abstracts, No. 827.5, San Diego, USA, 2004.
  • Wiener, S. I. and Arleo, A. Neurobiologically based proposals for structuring navigation strategies for autonomous agents. In Meyer, J.-A. and Guillot, A., editors, Proceedings of the Int Conference Towards Artificial Rodents, Paris, France, 2004.
  • Wiener, S. I.; Arleo, A.; Déjean, C.; Boucheny, C.; Khamassi, M. and Zugaro, M.B. Optic field flow signals update the activity of head direction cells in the rat anterodorsal thalamus. In Society for Neuroscience Abstracts, No. 209.2, San Diego, USA, 2004.

2003

  • Zugaro, M. B.; Arleo, A.; Berthoz, A. and Wiener, S. I. Rapid spatial reorientation and head direction cells. Journal of Neuroscience, 23(8): 3478-3482, 2003.
  • Wiener, S. I. and Arleo, A. Persistent activity in limbic system neurons: neurophysiological and modeling perspectives. Journal of Physiology P, 97(4-6): 547-555, 2003.
  • Déjean, C.; Zugaro, M. B.; Arleo, A. and Wiener, S. I. La parallaxe de mouvement décide quels repères visuels mettent à jour les cellules de direction de la tête chez le rat. In Proceedings of 6th French Society for Neuroscience Meeting, Rouen, France, 2003.
  • Degris, T.; Brunel, N. and Arleo, A. Rapid response of head direction cells to reorienting visual cues: A computational model. In De Schutter, E., editors, Proceedings of the Computational Neuroscience Meeting, Elsevier, 2003.
  • Arleo, A. Hippocampal place cells and head direction cells: Computational Modeling and Electrophysiological Experiments. In Buelthoff, H. H. et al., editors, Proceedings of the 6th Perception Conference, pages 40-41, Knirsch Verlag Germany, 2003.
  • Zugaro, M. B.; Arleo, A.; Déjean, C. and Wiener, S. I. Dynamic visual signals are crucial for the selection of anchoring distal cues by anterodorsal thalamic head direction cells. In Society for Neuroscience Abstracts, No. 519.16, New Orleans, USA, 2003.

2002

  • Strösslin, T.; Krebser, C.; Arleo, A. and Gerstner, W. Combining Multimodal Sensory Input for Spatial Learning. In Dorronsoro, J. R., editors, LNCS - Artificial Neural Networks, vol. 2415, pages 87-92, Springer, 2002.
  • Arleo, A. Processing multimodal sensory information for spatial learning and navigation: Computational modeling, robotics, and rat experiments. In Prescott, T. and Webb, B., editors, Proceedings of the Workshop on Robotics and Theoretical Biology, pages 9, Edinburgh, U.K., 2002.
  • Zugaro, M. B.; Arleo, A.; Berthoz, A. and Wiener, S. I. Rapid reorientation in rat anterodorsal thalamic head direction cells. In Society for Neuroscience Abstracts, No. 584.7, Orlando, USA, 2002.
  • Arleo, A. and Gerstner, W. A model of rat spatial learning system: studying the interrelation between idiothetic and allothetic cues. In FENS Abstracts, vol. 1: A075.6, 2002.
  • Zugaro, M. B.; Arleo, A.; Berthoz, A. and Wiener, S. I. Rapid reorientation in rat anterodorsal thalamic head direction cells. In FENS Abstracts, vol. 1: A041.37, 2002.

2001

2000

1999

  • Arleo, A. and Gerstner, W. Neuro-mimetic navigation systems: A computational model of the rat Hippocampus. In Drogoul, A. and Meyer, J.-A., editors, Proceedings of the Conference on Situated Artificial Intelligence (IAS99), pages 193-211, Hermès, Paris, 1999.
  • Arleo, A. and Gerstner, W. A vision-driven model of hippocampal place cells and temporally asymmetric LTP-induction for action learning. In Willshaw, D. and Murry, A., editors, Proceedings of the Ninth International Conference on Artificial Neural Networks, vol. 1, pages 132-137, IEE Press, London, 1999.
  • Arleo, A.; del R. Millán, J. and Floreano, D. Efficient learning of variable-resolution cognitive maps for autonomous indoor navigation. IEEE Transctions on Robotics and Automation, 15(6): 990-1000, 1999.
  • Arleo, A.; del R. Millán, J. and Gerstner, W. Hippocampal spatial model for state space representation in reinforcement learning. Technical Report 99/316, Swiss Federal Institute of Technology, Lausanne, Switzerland, 1999.
  • Arleo, A. and Gerstner, W. Spatial models and autonomous navigation in neuromimetic systems. In Proceedings of the 3rd Int Conference on Cognitive and Neural Systems, Boston, MA, 1999.

1998

  • Arleo, A.; Floreano, D. and Gerstner, W. Modélisation de l'hippocampe: Représentation spatiale et navigation des systèmes autonomes. In Journées des Jeunes Chercheurs en Robotique, JJCR10, pages 25-30, Amiens, France, 1998.

1997

  • del R. Millán, J. and Arleo, A. Neural network learning of variable grid-based maps for the autonomous navigation of robots. In Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation, pages 40-45, IEEE Computer Society Press, 1997.
  • Arleo, A. and del R. Millán, J. Software application NELVAM, NEural network Learning of VAriable grid-based Maps, European Copyright ref. 2545.

1996

  • Arleo, A. Neural networks based on active local learning for efficient exploration of unknown environments. Master's Thesis, University of Mathematical Science, Milan, Italy, 1996.

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