I am a doctor in theoretical physics. I got a Master degree in theoretical physics at the center of theoretical physics, Marseille in 1990. I did my pHD in the ONERA Center of Research in Toulouse with M. Samuelides. Then I spent two years (1994-1996) in Bielefeld, Germany, as a post doc in Ph. Blanchard’s team, in the group of mathematical physics BiBoS. I was lecturer (Maitre de Conférences) in physics in Nice University from September 1996 to September 2010. I got my Habilitation à Diriger les Recherches in 2001. I am now Directeur de Recherches (Senior Research Scientist) at INRIA Sophia-Antipolis. I have been member of the Non Linear Institute of Nice (INLN) from 1996 to 2008, of the Laboratoire Jean-Alexandre Dieudonné from 2008 to 2010. I am research director at INRIA since 2010 and head of the Biovision team since January 2016.
My research was initially modeling and analysis of large sized dynamical systems arising in various fields such as physics, biology, sociology, computers networks. I have worked on subjects such as self-organized criticality, linear response in chaotic systems, social networks, communications networks. My main interest concerns neuronal networks dynamics. I have developed methods combining dynamical systems theory, statistical physics and ergodic theory allowing to classify dynamics arising in canonical neuronal networks models like integrate and fire models or firing rate models. I have applied these methods for the study of synaptic and intrinsic plasticity, dynamical learning, spike coding, spike train statistics analysis, mean-field dynamics. I am now involved in developing models for the visual system, especially the retina, as well as numerical methods and software for neuroscientists.
- Jenny Kartsaki (2017-2020) co-direction with Evelyne Sernagor. “How Specific Classes of Retinal Cells Contribute to
Vision: a Computational Model”. Funding Leverhulme Trust.
- Selma Souihel (2016-2019), “Generic and specific computational principles for the visual anticipation of motion trajectories”. Funding ANR Trajectory.
- Dora Karvouniari (2014-2018), “Retinal waves: theory, numerics, experiments“. Funding EDSTIC.
- Rodrigo Cofré (2011-2014), “Neuronal Networks, Spike Trains Statistics and Gibbs Distributions“. Funding EDSTIC.
- Hassan Nasser (2010-2014), “Analysis of large scale spiking networks dynamics with spatio-temporal constraints: application to Multi-Electrodes acquisitions in the retina“, Funding ERC (O. Faugeras).
- Horacio Rostro (2007-2010) with T. Viéville, “Computing with spikes, architecture, properties and implementation of emerging paradigms“. Funding Conacyt.
- Juan-Carlos Vasquez (2007-2010), “Analysis of Spike-train Statistics with Gibbs Distributions: Theory, Implementation and Applications“, Funding EDTSIC.
- B. Cessac, R. Cofre, Linear response for spiking neuronal networks with unbounded memory. Submitted to Journal of Mathematical Neuroscience.
- D. Karvouniari, L. Gil, O. Marre, S. Picaud, B.Cessac. A biophysical model explains the spontaneous bursting behavior in the developing retina, to appear in Scientific Reports.
- B. Cessac, P. Kornprobst, S. Kraria, H. Nasser, D. Pamplona, G. Portelli, T. Viéville PRANAS: a new platform for retinal analysis and simulation, Frontiers in Neuroinformatics, Vol 11, page 49, (2017)
- R. Herzog, M.-J. Escobar , A. G. Palacios, B. Cessac, Dimensionality Reduction and Reliable Observations in Maximum Entropy Models on Spiking Networks, submitted.
- G. Hilgen, S. Pirmoradian, D. Pamplona, P. Kornprobst, B. Cessac, M. H. Hennig, and E. Sernagor. Pan-retinal characterization of light responses from ganglion cells in the developing mouse retina.Scientific Reports, 2017.
- Bruno Cessac, Arnaud Le Ny, Eva Löcherbach. On the mathematical consequences of binning spike trains. Neural Computation, January 2017, Vol. 29, No. 1, Pages 146-170.
- Fatihcan M. Atay, Sven Banisch, Philippe Blanchard, Bruno Cessac, Eckehard Olbrich. Perspectives on Multi-Level Dynamics, Discontinuity, Nonlinearity, and Complexity, Vol. 5 (3) (2016).
- Rodrigo Cofré, Bruno Cessac, “Exact computation of the maximum-entropy potential of spiking neural-network models”,Phys. Rev. E 89, 052117 (2014).
- Hassan Nasser, Bruno Cessac, Parameters estimation for spatio-temporal maximum entropy distributions: application to neural spike trains, Entropy (2014), 16(4), 2244-2277; doi:10.3390/e16042244.
- Jeremie Naudé, Bruno Cessac, Hugues Berry, and Bruno Delord, “Effects of Cellular Homeostatic Intrinsic Plasticity on Dynamical and Computational Properties of Biological Recurrent Neural Networks” The Journal of Neuroscience, 18 September 2013, 33(38): 15032-15043; doi: 10.1523/JNEUROSCI.0870-13. (2013).
- B. Cessac and R. Cofré, Spike train statistics and Gibbs distributions, J. Physiol. Paris, Volume 107, Issue 5, Pages 360-368 (November 2013). Special issue: Neural Coding and Natural Image Statistics.
- Rodrigo Cofré and Bruno Cessac Dynamics and spike trains statistics in conductance-based Integrate-and-Fire neural networks with chemical and electric synapses, Chaos, Solitons & Fractals, Volume 50, May 2013, Pages 13-31.
- Hassan Nasser, Olivier Marre, and Bruno Cessac. Spike trains analysis using gibbs distributions and monte-carlo method”, J. Stat. Mech. (2013) P03006.
- B. Cessac A. Palacios. Spike train statistics from empirical facts to theory: the case of the retina, in “Modeling in Computational Biology and Biomedicine: A Multidisciplinary Endeavor”, F. CAZALS, P. KORNPROBST (editors), Lectures Notes in Mathematical and Computational Biology (LNMCB), Springer-Verlag, 2013.
(1994-1996 ) Dynamical systems, 2nd year (Sup’ Aero, Toulouse).
(1994-1996 ) Introduction to chaos theory, 2nd year (Sup’ Aero, Toulouse).
(2000) Ergodic theory for physicists. Lecture for the researchers of INLN.
(2008-2010) Thermodynamics Bases, Phases transitions, Machines thermiques, Statistical physics. Lecture and exercises, L2, physics. Université de Nice.
(2008- 2010) Quantum mechanics. Lecture and exercises, L2, physics, Université de Nice.
(2002-2006; 2008) Non equilibrium Statistical physics. Exercises M1, physics. U. Nice.
(2002-2006) Statistical physics. Exercices L3. Université de Nice.
(2003-2006; 2008) Probability theory Lecture and exercices L3 physics and M1 geology.
(1996-) Numerical Simulation in physics. Lecture and exercics. L3 physics.
(1996-2000; 2002-2004) Non linear physics. Exercises M1. Université de Nice.
(1996-2000) Linear Algebra. Lecture and exercises. M1 Geology. Université de Nice.
(2003-2006) Language C. Lecture. M2 biomedical engineering. Université de Nice.
(2002-2003) Dynamique Qualitative. Première année de DEUG. TD (6H, 40 étudiants). Université de Nice.
(1990-1994) Electromagnetism. Exercises L2 Physics. Université de Toulouse.
(1990-1994) Quantum mechanics. Exercises L2 Physics. Université de Toulouse.
(1993-1994) Relativity. Exercises L2 Physics. Université de Toulouse.
(1990-1991) Mean-field theory, Lecture M1 Physics. Université de Toulouse.
(2008- ) Neuronal dynamics (Neurons and Synapses, Neuronal networks dynamics, Mean-Field models). Lecture, M2, master Omega, physics,Université de Nice;
master of Computational Biology, Ecole Polytechnique Universitaire de Nice, Ecole des Houches; master Mod4NeuCog, Université Côte d’Azur