Publication list also available on Google scholar.

Papers - Talks - Students


    1. A. Dolcemascolo, A. Miazek, R. Veltz, F. Marino, and S. Barland Effective low-dimensional dynamics of a mean-field coupled network of slow-fast spiking lasers arXiv e-prints, 2019 nonlinear sciences - chaotic dynamics physics - optics Arxiv, Bibtex
    1. Q. Cormier, E. Tanré, and R. Veltz Long time behavior of a mean-field model of interacting neurons Stochastic Processes and their Applications, 2019 mathematics - probability (www), Arxiv, Bibtex
    1. B. Aymard, F. Campillo, and R. Veltz Mean-field limit of interacting 2D nonlinear stochastic spiking neurons arXiv e-prints, 2019 mathematics - numerical analysis Arxiv, Bibtex
    1. N. Fournier, E. Tanré, and R. Veltz On a toy network of neurons interacting through their dendrites Annales de l'Institut Henri Poincaré (B) Probabilités et Statistiques, 2019 (www), Arxiv, Bibtex
    1. A. Song, O. Faugeras, and R. Veltz A neural field model for color perception unifying assimilation and contrast PLOS Computational Biology, 2019 (www), Bibtex
    1. R. Veltz PseudoArcLengthContinuation.jl 2019 pseudo arclength continuation (www), Bibtex
    1. T. Górski, R. Veltz, M. Galtier, H. Fragnaud, J. S. Goldman, B. Teleńczuk, and A. Destexhe Dendritic sodium spikes endow neurons with inverse firing rate response to correlated synaptic activity Journal of Computational Neuroscience, 45(3), 2018 (www), Bibtex
    1. A. Dolcemascolo, B. Garbin, B. Peyce, R. Veltz, and S. Barland Resonator neuron and triggering multipulse excitability in laser with injected signal Phys. Rev. E, 98, 2018 (www), Bibtex
    1. A. Drogoul and R. Veltz Exponential stability of the stationary distribution of a mean field of spiking neural network 2018 (www), Bibtex
    1. A. Drogoul and R. Veltz Hopf bifurcation in a nonlocal nonlinear transport equation stemming from stochastic neural dynamics Chaos: An Interdisciplinary Journal of Nonlinear Science, 27(2), 2017 (www), Bibtex
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    1. R. Veltz and T. J. Sejnowski Periodic Forcing of Inhibition-Stabilized Networks: Nonlinear Resonances and Phase-Amplitude Coupling Neural Computation, 27(12), 2477-2509, 2015 oscillation gamma band theta band (www), PDF, Bibtex
    1. R. Veltz A new twist for the simulation of hybrid systems using the true jump method arXiv [math], 2015 mathematics - numerical analysis (www), Bibtex
    1. R. Veltz and O. Faugeras ERRATUM: A Center Manifold Result for Delayed Neural Fields Equations SIAM Journal on Mathematical Analysis, 47(2), 2015 (www), Bibtex
    1. R. Veltz, P. Chossat, and O. Faugeras On the Effects on Cortical Spontaneous Activity of the Symmetries of the Network of Pinwheels in Visual Area V1 The Journal of Mathematical Neuroscience (JMN), 5(1), 2015 visual hallucinations invariant torus poincaré–hopf (www), Bibtex
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    1. J. Rankin, E. Tlapale, R. Veltz, O. Faugeras, and P. Kornprobst Bifurcation analysis applied to a model of motion integration with a multistable stimulus Journal of computational neuroscience, 34(1), 2013 Bibtex
    1. R. Veltz and O. Faugeras A center manifold result for delayed neural fields equations SIAM Journal on Mathematical Analysis, 45(3), 2013 Bibtex
    1. J. M. Cortes, M. Desroches, S. Rodrigues, R. Veltz, M. A. Munoz, and T. J. Sejnowski Short-term synaptic plasticity in the deterministic Tsodyks-Markram model leads to unpredictable network dynamics Proceedings of the National Academy of Sciences, 110(41), 2013 (www), Bibtex
    1. R. Veltz Interplay between synaptic delays and propagation delays in neural field equations SIAM Journal on Applied Dynamical Systems, 12(3), 2013 (www), Bibtex
    1. R. Veltz and O. Faugeras Stability of the stationary solutions of neural field equations with propagation delays The Journal of Mathematical Neuroscience (JMN), 1(1), 2011 (www), Bibtex
    1. R. Veltz An analytical method for computing Hopf bifurcation curves in neural field networks with space-dependent delays Comptes Rendus Mathematique, 349(13), 2011 (www), PDF, Bibtex
    1. R. Veltz and O. Faugeras Local/global analysis of the stationary solutions of some neural field equations SIAM Journal on Applied Dynamical Systems, 9(3), 2010 Bibtex
    1. R. Veltz and O. Faugeras Illusions in the ring model of visual orientation selectivity arXiv preprint arXiv:1007.2493, 2010 (www), Bibtex
    1. O. Faugeras, R. Veltz, and F. Grimbert Persistent neural states: stationary localized activity patterns in nonlinear continuous n-population, q-dimensional neural networks Neural computation, 21(1), 2009 (www), PDF, Bibtex
    1. M. Clerc, R. Veltz, D. Guiraud, J. L. Divoux, and others The 3d potential induced by functional electrical stimulation with multi-contact cuff electrodes: simulation and validation International Functional Electrical Stimulation Society Conference, 2008 Bibtex


    Talks


    1. R. Veltz Analysis of a mean field of 2d spiking neurons, theory and numerics , International Meeting UK-France Programme, Royal Society, 2019
    2. R. Veltz On a toy network of neurons interacting through nonlinear dendritic compartments , Mean-field approaches to the dynamics of neuronal networks, EITN, 2018
    3. R. Veltz On a toy network of neurons interacting through nonlinear dendritic compartments , Random Structures on the Brain, Lorentz Center in Leiden, The Netherlands, 2017
    4. R. Veltz Oscillatory dynamics in a stochastic spiking neural network , BANFF: Brain Dynamics and Statistics, Alberta Canada, 2017
    5. R. Veltz Two examples of temporal rhythms generated by neural mass/field equations , Centre for Math. Medicine and Biology, University of Nottingham, 2013


    Students


    1. A. Delrocq Models of WDR neurons in dorsal horn , Master 1, co-supervised with E. Deval, 2019
    2. S. Ebert Dynamical synapses in the retina , Master 1, co-supervised with B. Cessac, 2019
    3. Q. Cormier Study of mean field models of spiking neural networks , PhD, co-supervised with E.Tanré, 2017
    4. Q. Cormier Study of a mean field model of spiking neural network , Master 2, ENS Lyon, co-supervised with E.Tanré, 2017
    5. P. Helson Study of plasticity laws , PhD, co-supervised with E.Tanré, 2016
    6. R. Forquet Modelling of synaptic plasticity , Master 1, co-supervised with H. Marie, 2016
    7. C. Baron Modelling of synaptic plasticity , Master 1, co-supervised with H. Marie, 2016
    8. Q. Cormier Study of plasticity laws , Master 1, ENS Lyon, co-supervised with E.Tanré, 2015
    9. S. Almeida Simulation of PDMP , Undergraduate, 2014
    10. A. Razetti Simulation of PDMP , Undergraduate, 2014