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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 4F. Alexandre.

    Autonomous Machine Learning, in: ERCIM News, October 2016, no 107.

    https://hal.inria.fr/hal-01401888
  • 5C. Héricé, R. Khalil, M. E. Moftah, T. Boraud, M. Guthrie, A. Garenne.

    Decision making under uncertainty in a spiking neural network model of the basal ganglia, in: Journal of Integrative Neuroscience, December 2016, vol. 15, no 3, pp. 1-24. [ DOI : 10.1142/S021963521650028X ]

    https://hal.archives-ouvertes.fr/hal-01407859
  • 6E. Le Masson, F. Alexandre.

    [Re] How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks, in: ReScience, December 2016, vol. 2, no 1. [ DOI : 10.1371/journal.pcbi.1004060 ]

    https://hal.inria.fr/hal-01418735
  • 7C. Piron, D. Kase, M. Topalidou, M. Goillandeau, H. Orignac, T.-H. Nguyen, N. P. Rougier, T. Boraud.

    The Globus Pallidus Pars Interna in Goal-Oriented and Routine Behaviors: Resolving a Long-Standing Paradox, in: Movement Disorders, 2016. [ DOI : 10.1002/mds.26542 ]

    https://hal.archives-ouvertes.fr/hal-01317968

Articles in Non Peer-Reviewed Journals

Invited Conferences

  • 9X. Hinaut.

    Reservoir Computing for Robot Language Acquisition, in: IROS Workshop on Machine Learning Methods for High-Level Cognitive Capabilities in Robotics, Daejon, South Korea, October 2016.

    https://hal.inria.fr/hal-01417683

International Conferences with Proceedings

  • 10F. Alexandre.

    Beyond Machine Learning: Autonomous Learning, in: 8th International Conference on Neural Computation Theory and Applications (NCTA), Porto, Portugal, November 2016, pp. 97 - 101. [ DOI : 10.5220/0006090300970101 ]

    https://hal.inria.fr/hal-01401895
  • 11F. Alexandre, M. Carrere.

    Modeling Neuromodulation as a Framework to Integrate Uncertainty in General Cognitive Architectures, in: The Ninth Conference on Artificial General Intelligence, New-York, United States, July 2016. [ DOI : 10.1007/978-3-319-41649-6_33 ]

    https://hal.inria.fr/hal-01342902
  • 12M. Carrere, F. Alexandre.

    A System-Level Model of Noradrenergic Function, in: 25th International Conference on Artificial Neural Networks (ICANN), Barcelona, Spain, September 2016, pp. 214 - 221. [ DOI : 10.1007/978-3-319-44778-0_25 ]

    https://hal.inria.fr/hal-01401890
  • 13M. Carrere, F. Alexandre.

    Modeling the sensory roles of noradrenaline in action selection, in: The Sixth Joint IEEE International Conference Developmental Learning and Epigenetic Robotics (IEEE ICDL-EPIROB), Cergy-Pontoise / Paris, France, September 2016.

    https://hal.inria.fr/hal-01401882
  • 14X. Hinaut, J. Twiefel.

    Recurrent Neural Network Sentence Parser for Multiple Languages with Flexible Meaning Representations for Home Scenarios, in: IROS Workshop on Bio-inspired Social Robot Learning in Home Scenarios, Daejon, South Korea, October 2016.

    https://hal.inria.fr/hal-01417667
  • 15X. Hinaut, J. Twiefel, S. Wermter.

    Recurrent Neural Network for Syntax Learning with Flexible Predicates for Robotic Architectures, in: The Sixth Joint IEEE International Conference Developmental Learning and Epigenetic Robotics (ICDL-EPIROB), Cergy, France, September 2016.

    https://hal.inria.fr/hal-01417697
  • 16L. Mici, X. Hinaut, S. Wermter.

    Activity recognition with echo state networks using 3D body joints and objects category, in: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges, Belgium, April 2016, pp. 465 - 470.

    https://hal.inria.fr/hal-01417710
  • 17B. Teja Nallapu, N. P. Rougier.

    Dynamics of reward based decision making a computational study, in: ICANN 2016, Barcelona, France, ICANN 2016 - The 25th International Conference on Artificial Neural Networks, September 2016.

    https://hal.inria.fr/hal-01333210
  • 18J. Twiefel, X. Hinaut, M. Borghetti, E. Strahl, S. Wermter.

    Using Natural Language Feedback in a Neuro-inspired Integrated Multimodal Robotic Architecture, in: 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), New York City, United States, Proceedings of the 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), August 2016, pp. 52 - 57. [ DOI : 10.1109/ROMAN.2016.7745090 ]

    https://hal.inria.fr/hal-01417706
  • 19J. Twiefel, X. Hinaut, S. Wermter.

    Semantic Role Labelling for Robot Instructions using Echo State Networks, in: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges, Belgium, April 2016.

    https://hal.inria.fr/hal-01417701

Conferences without Proceedings

  • 20X. Hinaut.

    Recurrent Neural Network for Syntax Learning with Flexible Representations, in: IEEE ICDL-EPIROB Workshop on Language Learning, Cergy, France, December 2016.

    https://hal.inria.fr/hal-01417060
  • 21B. Teja Nallapu, N. P. Rougier, B. Raju Surampudi.

    The art of scaling up : a computational account on action selection in basal ganglia, in: 3rd Annual Conference on Cognitive Science (ACCS 2016), Gandhinagar, India, October 2016.

    https://hal.archives-ouvertes.fr/hal-01354041

Scientific Books (or Scientific Book chapters)

  • 22M.-J. U. Escobar, F. Alexandre, T. Viéville, A. Palacios.

    Rapid Prototyping for Bio–Inspired Robots, in: Rapid Roboting: Recent Advances on 3D Printers and Robotics, Intelligent Systems, Control and Automation: Science and Engineering, Springer, February 2017, 300 p.

    https://hal.inria.fr/hal-01427958
  • 23R. Kassab, F. Alexandre.

    A Modular Network Architecture Resolving Memory Interference through Inhibition, in: Computational Intelligence, J. Merelo (editor), Studies in Computational Intelligence, Springer, 2016, vol. 669, pp. 407-422. [ DOI : 10.1007/978-3-319-48506-5 ]

    https://hal.inria.fr/hal-01251022
  • 24N. P. Rougier.

    From Python to Numpy, Zenodo, December 2016. [ DOI : 10.5281/zenodo.218740 ]

    https://hal.inria.fr/hal-01422210

Internal Reports

  • 25B. Cessac, P. Kornprobst, S. Kraria, H. Nasser, D. Pamplona, G. Portelli, T. Viéville.

    ENAS: A new software for spike train analysis and simulation, Inria Sophia Antipolis ; Inria Bordeaux Sud-Ouest, October 2016, no RR-8958.

    https://hal.inria.fr/hal-01377307

Scientific Popularization

Other Publications

  • 32B. Cessac, P. P. Kornprobst, S. Kraria, H. Nasser, D. Pamplona, G. Portelli, T. Viéville.

    ENAS: A new software for spike train analysis and simulation, September 2016, Bernstein conference, Poster.

    https://hal.inria.fr/hal-01368757
  • 33C. Héricé, R. Khalil, M. Moftah, T. Boraud, M. Guthrie, A. Garenne.

    Decision-making in a neural network model of the basal ganglia, May 2016, Sixth International Symposium on Biology of Decision Making (SBDM 2016), Poster.

    https://hal.inria.fr/hal-01368504
  • 34N. P. Rougier.

    One critic for two actors, November 2016, GT8 Robotiques et neurosciences.

    https://hal.inria.fr/hal-01418327
  • 35M. Topalidou, D. Kase, T. Boraud, N. P. Rougier.

    Dissociation of reinforcement and Hebbian learning induces covert acquisition of value in the basal ganglia, June 2016, working paper or preprint. [ DOI : 10.1101/060236 ]

    https://hal.archives-ouvertes.fr/hal-01337332
  • 36M. Topalidou, D. Kase, T. Boraud, N. P. Rougier.

    Who's the teacher? Who's the pupil?, May 2016, Sixth International Symposium on Biology of Decision Making (SBDM2016), Poster.

    https://hal.inria.fr/hal-01347280
References in notes
  • 37F. Alexandre.

    Biological Inspiration for Multiple Memories Implementation and Cooperation, in: International Conference on Computational Intelligence, V. Kvasnicka, P. Sincak, J. Vascak, R. Mesiar (editors), 2000.
  • 38S. Amari.

    Dynamic of pattern formation in lateral-inhibition type neural fields, in: Biological Cybernetics, 1977, vol. 27, pp. 77–88.
  • 39D. H. Ballard, M. M. Hayhoe, P. K. Pook, R. P. N. Rao.

    Deictic codes for the embodiment of cognition, in: Behavioral and Brain Sciences, 1997, vol. 20, no 04, pp. 723–742.

    http://dx.doi.org/10.1017/S0140525X97001611
  • 40D. Bertsekas, J. Tsitsiklis.

    Parallel and Distributed Computation: Numerical Methods, Athena Scientific, 1997.
  • 41R. Brette, M. Rudolph, T. Carnevale, M. Hines, D. Beeman, J. Bower, M. Diesmann, A. Morrison, P. H. Goodman, F. C. Jr. Harris, M. Zirpe, T. Natschläger, D. Pecevski, B. Ermentrout, M. Djurfeldt, A. Lansner, O. Rochel, T. Viéville, E. Muller, A. Davison, S. E. Boustani, A. Destexhe.

    Simulation of networks of spiking neurons: a review of tools and strategies, in: Journal of Computational Neuroscience, 2007, vol. 23, no 3, pp. 349–398.
  • 42S. Coombes.

    Waves, bumps and patterns in neural field theories, in: Biol. Cybern., 2005, vol. 93, pp. 91-108.
  • 43P. Dayan, L. Abbott.

    Theoretical Neuroscience : Computational and Mathematical Modeling of Neural Systems, MIT Press, 2001.
  • 44K. Doya.

    What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?, in: Neural Networks, 1999, vol. 12, pp. 961–974.
  • 45J. Fix, N. P. Rougier, F. Alexandre.

    A dynamic neural field approach to the covert and overt deployment of spatial attention, in: Cognitive Computation, 2011, vol. 3, no 1, pp. 279-293. [ DOI : 10.1007/s12559-010-9083-y ]

    http://hal.inria.fr/inria-00536374/en
  • 46W. Gerstner, W. Kistler.

    Spiking Neuron Models: Single Neurons, Populations, Plasticity, Cambridge University Press, Cambridge University Press, 2002.
  • 47M. Guthrie, A. Leblois, A. Garenne, T. Boraud.

    Interaction Between Cognitive and Motor Cortico-Basal Ganglia Loops During Decision Making: A Computational Study, in: Journal of Neurophysiology, March 2013.

    http://hal.inria.fr/hal-00828004
  • 48T. Mitchell.

    Machine Learning, Mac Graw-Hill Press, 1997.
  • 49D. Mitra.

    Asynchronous relaxations for the numerical solution of differential equations by parallel processors, in: SIAM J. Sci. Stat. Comput., 1987, vol. 8, no 1, pp. 43–58.
  • 50R. O'Reilly, Y. Munakata.

    Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain, MIT Press, Cambridge, MA, USA, 2000.
  • 51N. P. Rougier, J. Fix.

    DANA: Distributed (asynchronous) Numerical and Adaptive modelling framework, in: Network: Computation in Neural Systems, December 2012, vol. 23, no 4, pp. 237-253. [ DOI : 10.3109/0954898X.2012.721573 ]

    http://hal.inria.fr/hal-00718780
  • 52N. P. Rougier, A. Hutt.

    Synchronous and Asynchronous Evaluation of Dynamic Neural Fields, in: J. Diff. Eq. Appl., 2009.
  • 53N. P. Rougier.

    Dynamic Neural Field with Local Inhibition, in: Biological Cybernetics, 2006, vol. 94, no 3, pp. 169-179.
  • 54L. Squire.

    Memory systems of the brain: a brief history and current perspective, in: Neurobiol. Learn. Mem., 2004, vol. 82, pp. 171-177.
  • 55W. Taouali, T. Viéville, N. P. Rougier, F. Alexandre.

    No clock to rule them all, in: Journal of Physiology, 2011, vol. 105, no 1-3, pp. 83-90.
  • 56T. Trappenberg.

    Fundamentals of Computational Neuroscience, Oxford University Press, 2002.
  • 57T. Viéville.

    An unbiased implementation of regularization mechanisms, in: Image and Vision Computing, 2005, vol. 23, no 11, pp. 981–998.

    http://authors.elsevier.com/sd/article/S0262885605000909


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