Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

• 1I. Chraibi Kaadoud.
  Sequence learning and rules extraction from recurrent neural networks : application to the drawing of technical diagrams, Université de Bordeaux, March 2018.
  https://tel.archives-ouvertes.fr/tel-01771685

Articles in International Peer-Reviewed Journals

• 2F. C. Y. Benureau, N. P. Rougier.
  Re-run, Repeat, Reproduce, Reuse, Replicate: Transforming Code into Scientific Contributions, in: Frontiers in Neuroinformatics, January 2018, vol. 11, https://arxiv.org/abs/1708.08205. [ DOI : 10.3389/fninf.2017.00069 ]
  https://hal.inria.fr/hal-01577578
• 3T. Boraud, A. Leblois, N. P. Rougier.
  A Natural History of Skills, in: Progress in Neurobiology, December 2018, vol. 171, pp. 114-124. [ DOI : 10.1016/j.pneurobio.2018.08.003 ]
  https://hal.inria.fr/hal-01874690
• 4T. F. Drumond, T. Viéville, F. Alexandre.
  Bio-inspired analysis of deep learning on not-so-big data using data-prototypes, in: Frontiers in Computational Neuroscience, January 2019, vol. 12. [ DOI : 10.3389/fncom.2018.00100 ]
  https://hal.inria.fr/hal-01954911
• 5C. El Khoueiry, D. Moretti, R. Renom, F. Camera, R. Orlacchio, A. Garenne, F. Poulletier De Gannes, E. Poque-Haro, I. Lagroye, B. Veyret, N. Lewis.
  Decreased spontaneous electrical activity in neuronal networks exposed to radiofrequency 1800 MHz signals, in: Journal of Neurophysiology, December 2018, vol. 120, n^o 6, pp. 2719-2729.
  https://hal.inria.fr/hal-01943451
• 6X. Hinaut, J. Twiefel.
  Teach Your Robot Your Language! Trainable Neural Parser for Modelling Human Sentence Processing: Examples for 15 Languages, in: IEEE Transactions on Cognitive and Developmental Systems, 2018.
  https://hal.inria.fr/hal-01964541
• 7R. Kassab, F. Alexandre.
  Pattern Separation in the Hippocampus: Distinct Circuits under Different Conditions, in: Brain Structure and Function, July 2018, vol. 223, n^o 6, pp. 2785-2808. [ DOI : 10.1007/s00429-018-1659-4 ]
  https://hal.inria.fr/hal-01931720
• 8M. Romero, M. Duflot-Kremer, T. Viéville.
  Le jeu du robot : analyse d’une activité d’informatique débranchée sous la perspective de la cognition incarnée, in: Review of science, mathematics and ICT education, 2018.
  https://hal.inria.fr/hal-01950335
• 9N. P. Rougier, K. Hinsen.
  Correspondance. Code review poses extra challenges, in: Nature, April 2018, 309 p, Correspondence. [ DOI : 10.1038/d41586-018-04628-w ]
  https://hal.inria.fr/hal-01773411
• 10N. P. Rougier.
  A Density-Driven Method for the Placement of Biological Cells Over Two-Dimensional Manifolds, in: Frontiers in Neuroinformatics, March 2018, vol. 12, Corresponding code at https://github.com/rougier/spatial-computation. [ DOI : 10.3389/fninf.2018.00012 ]
  https://hal.inria.fr/hal-01617732
• 11M. Topalidou, D. Kase, T. Boraud, N. P. Rougier.
  A Computational Model of Dual Competition between the Basal Ganglia and the Cortex, in: eNeuro, December 2018, pp. ENEURO.0339–17.2018.
  https://hal.inria.fr/hal-01925643

Articles in National Peer-Reviewed Journals

• 12M. Romero, S. Noirpoudre, T. Viéville.
  Que disent les sciences de l’éducation à propos de l’apprentissage du code ?, in: Revue de l'association EPI, May 2018.
  https://hal.inria.fr/hal-01969400

Invited Conferences

• 13S. Pagliarini, X. Hinaut, A. Leblois.
  Learning an inverse model for vocal production: toward a bio-inspired model, in: European Birdsong Meeting, Odense, Denmark, April 2018.
  https://hal.inria.fr/hal-01963115
• 14N. P. Rougier.
  Reproducibility in Machine Learning, in: ICML 2018 - Workshop on reproducibility in machine learning, Stockholm, Sweden, July 2018.
  https://hal.archives-ouvertes.fr/hal-01856189
• 15N. P. Rougier.
  We Redo Science, in: Bernstein Conference - PhD Symposium, Berlin, Germany, September 2018.
  https://hal.inria.fr/hal-01856196

International Conferences with Proceedings

• 16F. Alexandre.
  Different learning architectures contribute to value prediction in human cognition, in: AIC 2018 : 6th International Workshop on Artificial Intelligence and Cognition, Palermo, Italy, July 2018.
  https://hal.inria.fr/hal-01931492
• 17X. Hinaut.
  Which Input Abstraction is Better for a Robot Syntax Acquisition Model? Phonemes, Words or Grammatical Constructions?, in: 2018 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), Tokyo, Japan, September 2018, Corresponding code at https://github.com/neuronalX/Hinaut2018_icdl-epirob.
  https://hal.inria.fr/hal-01889919
• 18L. Khacef, B. Girau, N. P. Rougier, A. Upegui, B. Miramond.
  Neuromorphic hardware as a self-organizing computing system, in: WCCI 2018 - IEEE World Congress on Computational Intelligence, Workshop NHPU : Neuromorphic Hardware In Practice and Use, Rio de Janeiro, Brazil, IEEE, July 2018, pp. 1-4.
  https://hal.archives-ouvertes.fr/hal-01790776
• 19S. Pagliarini, X. Hinaut, A. Leblois.
  A bio-inspired model towards vocal gesture learning in songbird, in: 2018 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), Tokyo, Japan, September 2018, Corresponding code at https://github.com/spagliarini/2018-ICDL-EPIROB.
  https://hal.inria.fr/hal-01906459
• 20S. Pagliarini, A. Leblois, X. Hinaut.
  Towards Biological Plausibility of Vocal Learning Models: a Short Review, in: ICDL-Epirob Workshop on Continual Unsupervised Sensorimotor Learning, Tokyo, Japan, September 2018.
  https://hal.inria.fr/hal-01942822
• 21M. Romero, B. Lille, T. Viéville, M. Duflot-Kremer, C. De Smet, D. Belhassein.
  Analyse comparative d’une activité d’apprentissage de la programmation en mode branché et débranché, in: Educode - Conférence internationale sur l'enseignement au numérique et par le numérique, Bruxelles, Belgium, August 2018.
  https://hal.inria.fr/hal-01861732
• 22N. P. Rougier, B. Esfahbod.
  Digital Typography Rendering, in: ACM SIGGRAPH Courses, Vancouver, Canada, August 2018.
  https://hal.inria.fr/hal-01815193
• 23A. Strock, N. P. Rougier, X. Hinaut.
  A Simple Reservoir Model of Working Memory with Real Values, in: 2018 International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, July 2018, https://arxiv.org/abs/1806.06545 - Corresponding code at https://github.com/anthony-strock/ijcnn2018. [ DOI : 10.1109/IJCNN.2018.8489262 ]
  https://hal.inria.fr/hal-01803594
• 24B. Teja Nallapu, F. Alexandre.
  A survival task for the design and the assessment of an autonomous agent, in: 7th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2018, Paris, France, July 2018.
  https://hal.inria.fr/hal-01931573
• 25B. Teja Nallapu, F. Alexandre.
  Cognitive Architecture and Software Environment for the Design and Experimentation of Survival Behaviors in Artificial Agents, in: IJCCI 2018 - 10th International Joint Conference on Computational Intelligence, Seville, Spain, September 2018.
  https://hal.inria.fr/hal-01931497
• 26A. Upegui, B. Girau, N. P. Rougier, F. Vannel, B. Miramond.
  Pruning Self-Organizing Maps for Cellular Hardware Architectures, in: AHS 2018 - 12th NASA/ESA Conference on Adaptive Hardware and Systems, Edinburgh, United Kingdom, IEEE, August 2018, pp. 272-279. [ DOI : 10.1109/AHS.2018.8541465 ]
  https://hal.archives-ouvertes.fr/hal-01826263

Scientific Books (or Scientific Book chapters)

• 27F. Alexandre.
  L'approche systémique : simuler moins pour modéliser plus en neurosciences, in: Actes du colloque "Modélisation: succès et limites", CNRS et Académie des Technologies, CNRS - Académie des Technologies, February 2018, 12 p.
  https://hal.inria.fr/hal-01933185
• 28X. Nogues, A. Garenne, X. Bouteiller, V. Fievet.
  Le cours de Biostatistiques, Dunod, April 2018.
  https://hal.inria.fr/hal-01939213

Scientific Popularization

• 29M. Ciussi, N. Colombier, S.-C. Lefèvre, I. Yastrebova - Otmanine, M. Romero, C. De Smet, T. Viéville.
  Numérique et éducation … vous avez dit #CreaSmartEdtech ?, in: Blog Binaire LeMonde.fr, July 2018.
  https://hal.inria.fr/hal-01957475

Other Publications

• 30X. Hinaut.
  From Phonemes to Sentence Comprehension: A Neurocomputational Model of Sentence Processing for Robots, May 2018, SBDM2018 Satellite-Workshop on interfaces between Robotics, Artificial Intelligence and Neuroscience, Poster.
  https://hal.inria.fr/hal-01964524
• 31A. Strock, N. P. Rougier, X. Hinaut.
  A Simple Reservoir Model of Working Memory with Real Values, June 2018, Third workshop on advanced methods in theoretical neuroscience, Poster.
  https://hal.inria.fr/hal-01861784
• 32B. Teja Nallapu, F. Alexandre.
  Interaction between the limbic and sensori-motor cortico-basal loops : a systemic framework to explain animal behaviour, May 2018, SBDM 2018 - Eighth International Symposium on Biology of Decision Making, Poster.
  https://hal.inria.fr/hal-01820371
• 33J.-B. Zacchello, X. Hinaut, A. Leblois.
  Replication of Laje & Mindlin's model producing synthetic syllables, April 2018, European Birdsong Meeting, Poster.
  https://hal.inria.fr/hal-01964522

References in notes

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  Biological Inspiration for Multiple Memories Implementation and Cooperation, in: International Conference on Computational Intelligence, V. Kvasnicka, P. Sincak, J. Vascak, R. Mesiar (editors), 2000.
• 35S. Amari.
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• 37D. Bertsekas, J. Tsitsiklis.
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• 39S. Coombes.
  Waves, bumps and patterns in neural field theories, in: Biol. Cybern., 2005, vol. 93, pp. 91-108.
• 40P. Dayan, L. Abbott.
  Theoretical Neuroscience : Computational and Mathematical Modeling of Neural Systems, MIT Press, 2001.
• 41K. Doya.
  What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?, in: Neural Networks, 1999, vol. 12, pp. 961–974.
• 42J. 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, n^o 1, pp. 279-293. [ DOI : 10.1007/s12559-010-9083-y ]
  http://hal.inria.fr/inria-00536374/en
• 43W. Gerstner, W. Kistler.
  Spiking Neuron Models: Single Neurons, Populations, Plasticity, Cambridge University Press, Cambridge University Press, 2002.
• 44T. Mitchell.
  Machine Learning, Mac Graw-Hill Press, 1997.
• 45D. Mitra.
  Asynchronous relaxations for the numerical solution of differential equations by parallel processors, in: SIAM J. Sci. Stat. Comput., 1987, vol. 8, n^o 1, pp. 43–58.
• 46R. O'Reilly, Y. Munakata.
  Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain, MIT Press, Cambridge, MA, USA, 2000.
• 47N. P. Rougier, A. Hutt.
  Synchronous and Asynchronous Evaluation of Dynamic Neural Fields, in: J. Diff. Eq. Appl., 2009.
• 48N. P. Rougier.
  Dynamic Neural Field with Local Inhibition, in: Biological Cybernetics, 2006, vol. 94, n^o 3, pp. 169-179.
• 49L. Squire.
  Memory systems of the brain: a brief history and current perspective, in: Neurobiol. Learn. Mem., 2004, vol. 82, pp. 171-177.
• 50W. Taouali, T. Viéville, N. P. Rougier, F. Alexandre.
  No clock to rule them all, in: Journal of Physiology, 2011, vol. 105, n^o 1-3, pp. 83-90.
• 51T. Trappenberg.
  Fundamentals of Computational Neuroscience, Oxford University Press, 2002.
• 52T. Viéville.
  An unbiased implementation of regularization mechanisms, in: Image and Vision Computing, 2005, vol. 23, n^o 11, pp. 981–998.
  http://authors.elsevier.com/sd/article/S0262885605000909