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Master and pHD subjects.

Master of Computer Science in Computational Biology from Nice Sophia Antipolis University

Web page KEOPS: Algorithms for modeling the visual system:
From natural vision to numerical applications.

Bruno Cessac is a doctor in theoretical physics. He got a Master degree in theoretical physics at the center of theoretical physics, Marseille in 1990. He did his pHD in the ONERA Center of Research in Toulouse with M. Samuelides. Then he spent two years (1994-1996) in Bielefeld, Germany, as a post doc in Ph. Blanchard’s team, in the group of mathematical physics BiBoS. He was lecturer (Maitre de Conférences) in Nice University from September 1996 to September 2010.  He is now  Directeur de Recherches (Senior Research Scientist) at INRIA Sophia-Antipolis. He has been member of the Non Linear Institute of Nice (INLN) from 1996 to 2008,  of the Laboratoire Jean-Alexandre Dieudonné from 2008 to 2010. He is in the NeuroMathComp INRIA project team since 2006.

His research interests are modeling and analysis of large sized dynamical systems arising in various fields such as physics, biology, sociology, computers networks. He has worked on subjects such as self-organized criticality, linear response in chaotic systems, social networks, communications networks. His main interest concerns neuronal networks dynamics. He has 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. He is currently applying these methods on the study of synaptic and intrinsic plasticity, spike coding, spike train statistics analysis, neural masses dynamics, with applications to vision.

Some recent publications

• B. Cessac and A. Palacios, "Spike train statistics from empirical facts to theory: the case of the retina", In Mathematical Problems in Computational Biology and Biomedicine, F. Cazals and P. Kornprobst, Springer, to appear.


• H. Rostro-Gonzalez, , B. Cessac, T. Viéville, “ Parameter estimation in spiking neural networks: a reverse-engineering approach », J. Neural Eng. 9 (2012) 026024.

• The role of the asymptotic dynamics in the design of FPGA-based hardware implementations of gIF-type neural networks, Horacio Rostro-Gonzalez, Bruno Cessac, Bernard Girau, Cesar Torres-Huitzil, J. Physiol. Paris,  vol. 105, n° 1–3, pages 91—97, (2011).
  

• J.C. Vasquez, A. Palacios, O. Marre, M.J. Berry II, B. Cessac, Gibbs distribution analysis of temporal correlation structure on multicell spike trains from retina ganglion cells, J. Physiol. Paris, in press (2012).

• Cessac, B (2011) Statistics of spike trains in conductance-based neural networks: Rigorous results, The Journal of Mathematical Neuroscience , 1:8  (2011).

• Cessac, B (2010) A discrete time neural network model with spiking neurons: II: Dynamics with noise. J Math Biol Journal of Mathematical Biology: Volume 62, Issue 6 (2011), Page 863-900.

• B. Cessac, ``Neural Networks as dynamical systems'', International Journal of Bifurcations and Chaos , Volume: 20, Issue: 6, (2010), 1585-1629.

• B. Cessac, H. Rostro, J.C. Vasquez, T. Viéville , “How Gibbs distributions may naturally arise from synaptic adaptation mechanisms” , J. Stat. Phys,136, (3), 565-602 (2009).



• O. Faugeras, J. Touboul, B. Cessac, “A constructive mean field analysis of multi population neural networks with random synaptic weights and stochastic inputs”, Front. Comput. Neurosci. (2009) 3:1.

• Cessac B., Viéville T., ``On Dynamics of Integrate-and-Fire Neural Networks with Adaptive Conductances.'', Front. Comput. Neurosci. (2008) 2:2.

• Siri B., Berry H., Cessac B., Delord B., 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 Comp., vol 20, num. 12, pp 2937-2966.

• B. Cessac ``A discrete time neural network model with spiking neurons. Rigorous results on the spontaneous dynamics'', J. Math. Biol., Volume 56, Number 3, 311-345 (2008).

• Cessac B., "Does the complex susceptibility of the Hénon map have a pole in the upper-half plane ? A numerical investigation.", Nonlinearity, 20, 2883-2895 (2007).

• Samuelides M., Cessac B., "Random recurrent neural networks dynamics.", EPJ Special Topics "Topics in Dynamical Neural Networks : From Large Scale Neural Networks to Motor Control and Vision", Vol. 142, Num. 1, 7-88, (2007).

• Cessac B., Samuelides M., "From Neuron to Neural Networks dynamics. ", EPJ Special Topics "Topics in Dynamical Neural Networks : From Large Scale Neural Networks to Motor Control and Vision", Vol. 142, Num. 1, 89-122, (2007).

• Cessac B., Sepulchre J.A., "Linear Response in a class of simple systems far from equilibrium". , Physica D, Volume 225, Issue 1 , 13-28 (2006)

• Cessac B., Sepulchre J.A., "Transmitting a signal by amplitude modulation in a chaotic network'", Chaos 16, 013104, (2006).

Complete list.

(2009) Lecture in Ecole de Physique des Houches. 

Documents publiés sous licence Creative Commons

(1994-1996 ) Dynamical systems, 2nd year (Sup' Aero, Toulouse).  (1994-1996 ) Introduction to chaos theory, 2nd year (Sup' Aero, Toulouse). (2008- ) Neuronal dynamics. Lecture, M2, master Omega, physics,Université de Nice; master of Computational Biology, Ecole Polytechnique Universitaire de Nice, Ecole des Houches. (2000) Ergodic theory for physicists. Lecture for the researchers of INLN. (2008-) Thermodynamics. Lecture and exercises, L2, physics. Université de Nice. (2008- ) 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.

Systèmes dynamiques Chaos Neurons and synapses. Neural Networks Dynamics. Neural masses. Théorie ergodique pour physiciens Bases de thermodynamique Transitions de Phase; Machines Thermiques; Physique statistique. Probabilités Algèbre linéaire

Current PhD students

Rodrigo Cofre

Hassan Nasser

 Postdoc:   Reproducing spike train statistics of biological neuronal networks.

• Hugues Berry
• Philippe Blanchard
• Rodrigo Cofré
  
• Emmanuel Daucé
  
• Bruno Delord
• Olivier Faugeras
• Pierre Kornprobst
  
• Tyll Krueger
• Olivier Marre
  
• Hassan Nasser
  

• Adrian Palacios.
• Vivien Robinet
  
• Horacio Rostro
  
• Manuel Samuelides
• Jacques-Alexandre Sepulchre
• Jonathan  Touboul
• Juan-Carlos Vasquez
  
• Thierry Viéville

Bruno Cessac
INRIA, NeuroMathComp project team
2004 Route des Lucioles
06902 Sophia Antipolis Cedex 2

Email: bruno.cessac@inria.fr
Phone: +33-4-9238-5035
Fax: +33-4-9238-7845

Team assistant: Marie-Cecile Lafont

Email: Marie-Cecile.Lafont@inria.fr
Phone: +33-4-9238-7979
Fax: +33-4-9238-7845