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Publications of Mathias Quoy

Journal papers
[A27] Gaussier, Philippe and Banquet, Jean-Paul and Cuperlier, Nicolas and Quoy, Mathias and Aubin, Lise and Jacob, Pierre-Yves and Sargolini, Francesca and Save, Etienne and Krichmar, Jeffrey and Poucet, Bruno, Merging information in the entorhinal cortex: what can we learn from robotics experiments and modeling?, Journal of Experimental Biology, 2018
[A26] Pitti, Alexandre and Gaussier, Philippe and Quoy, Mathias, Iterative free-energy optimization for recurrent neural networks (INFERNO), PLoS ONE, 12/3, e0173684, 2017
[A25] Mahé, S. and Braud, R. and Gaussier, P. and Quoy, M. and Pitti, A., Exploiting the Gain-Modulation Mechanism in Parieto-Motor Neurons: Application to Visuomotor Transformations and Embodied Simulation, Neural Networks, 62, 102-111, 2015
[A24] Pitti, Alexandre and Braud, Raphael and Mah\'e, Sylvain and Quoy, Mathias and Gaussier, Philippe, Neural Model for Learning-to-Learn of Novel Task Sets in the Motor Domain, Frontiers in Psychology: cognitive science, vol 4/771, 2013
[A23] Pitti, Alexandre and Kuniyoshi, Yasuo and Quoy, Mathias and Gaussier, Philippe, Modeling the Minimal Newborn's Intersubjective Mind: the Visuotopic-Somatotopic Alignment Hypothesis in the Superior Colliculus, PLoS ONE, vol 8/7, e69474, 2013
[A22] Hirel, J. and Gaussier, P. and Quoy, M. and Banquet, J.P. and Save, E. and Poucet, B., The Hippocampo-cortical Loop: Spatio-Temporal Learning and Goal-oriented Planning in Navigation, Neural Networks, vol 43, 8-21, 2013
[A21] Brocolini, L. and Lavandier, C. and Quoy, M. and Ribeiro, C., Measurements of acoustic environments for urban soundscapes: choice of homogeneous periods, optimization of durations and selection of indicators, Journal of the Acoustical Society of America, to be published, 2013
[A20] Laurence C Bray Jayet and Mathias Quoy and Philip H Goodman and Frederick C Harris, " A Circuit-Level Model of Hippocampal Place Field Dynamics Modulated by Entorhinal Grid and Suppression-Generating Cells", Frontiers in Neural Circuits, 4, 12 pages, 2010, 10.3389/fncir.2010.00122, circuits&ART_DOI=10.3389/fncir.2010.00122
[A19] Laroque, Ph. and Gaussier, N. and Cuperlier, N. and Quoy, M. and Gaussier, Ph., " Cognitive map plasticity and imitation strategies to improve individual and social behaviors of autonomous agents", Journal of Behavioral Robotics, 1(1), 25-36.
[A18] Siri, B. and Berry, H. and Cessac, B. and Delord, B. and Quoy, M., " A mathematical analysis of the effects of Hebbian learning rules on the dynamics and structure of discrete-time random recurrent neural networks", Neural Computation, 12(20), 2937-2966, 2008.
[A17] Cuperlier, N. and Quoy, M. and Gaussier, Ph., "Neurobiologically inspired mobile robot navigation and planning", Frontiers in NeuroRobotics, 1(1), on line, 2007.
[A16] Siri, B. and Quoy, M. and Delord, B. and Cessac, B. and Berry, H., " Effects of Hebbian learning on the dynamics and structure of random networks with inhibitory and excitatory neurons", Journ. NeuroPhysiology, Paris, 1-3(101), 138-150, 2007.
[A15] Berry, H. and Quoy, M., " Structure and Dynamics of Random Recurrent Neural Networks", Adaptive behavior, 14, 129-137, 2006.
[A14] Cuperlier, N. and Quoy, M. and Laroque, P. and Gaussier, P., " Transition cells and neural fields for navigation and planning", Lecture Notes in Computer Science, 346--355, 2005.
[A13] J.P. Banquet and P. Gaussier and M. Quoy and A. Revel and Y. Burnod, " A hierarchy of associations in hippocampo-cortical systems: cognitive maps and navigation strategies", Neural Computation, 17(6), 1339--1384, 2003.
[A12] P. Gaussier and P. Andry and J.P. Banquet and M. Quoy and J. Nadel and A. Revel, " Robots as models of the brain: what can we learn from modelling rat navigation and infant imitation games?", Lecture Notes in Artificial Intelligence, 2780, 377-385, 2003.
[A11] M. Quoy and S. Moga and P. Gaussier, " Dynamical neural networks for top-down robot control", IEEE transactions on Man, Systems and Cybernetics, Part A, 33(4), 523-532, 2003.
[A10] E. Dauc&andcute;, M. Quoy and B. Doyon, " Resonant spatio-temporal learning in large random neural networks", Biological Cybernetics, 87, 185-198, 2002.
[A9] J.P. Banquet and P. Gaussier and M. Quoy and A. Revel, " From reflex to planning: multimodal, versatile, complex systems in biorobotics", Behavioural Brain Science, 24(6), 1051-1053, 2001.
[A8] M. Quoy and J.P. Banquet and E. Daucé, " Learning and control with chaos: from biology to robotics", Behavioural Brain Science, 24(5), 824-826, 2001.
[A7] P. Gaussier and S. Moga and J.P. Banquet and M. Quoy, " From Perception-Action loops to imitation processes", Applied Artificial Intelligence, 1(7), 701-727, 1998.
[A6] E. Daucé and M. Quoy and B. Cessac and B. Doyon and M. Samuelides, " Self-organization and pattern-induced reduction of dynamics in recurrent networks", Neural Networks, 11, n.2521-533, 1998.
[A5] M. Samuelides and B. Doyon and B. Cessac and M. Quoy, " Spontaneous dynamics and associative learning in an asymmetric recurrent random neural network", Annals of Mathematics of Artificial Intelligence, 312-317, 1996.
[A4] B. Doyon and B. Cessac and M. Quoy and M. Samuelides, " On bifurcation and chaos in random neural networks", Acta Biotheoretica, 42(2/3), 215-225, 1994.
[A3] B. Cessac and B. Doyon and M. Quoy and M. Samuelides, " Mean-field equations, bifurcation map and route to chaos in discrete time neural networks", Physica D, 74, 24-44, 1994.
[A2] M. Quoy and B. Cessac and B. Doyon and M. Samuelides, " Dynamical behaviour of neural networks with discrete time dynamics " Neural Network World, 3(6), 845-848, 1993.
[A1] B. Doyon and B. Cessac and M. Quoy and M. Samuelides, "Control of the transition to chaos in neural networks with random connectivity", Int. Journ. of Bifurcation and Chaos, 3(2), pp-279-291, 1993.

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