Bruno Cessac

Bruno Cessac

“The very substance of the ambitious is merely the shadow of a dream.”

William Shakespeare

Short Biblio. 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.

In the Biovision team my research is oriented toward 3 main goals: (i) Better understand how the modification of physiological parameters during development, addition of pharmacological substances, or pathologies induces changes in behavior in the retina and its functions; (ii) Model the effects of lateral connectivity – mainly amacrine cells – in retinal abilities such as motion anticipation; (iii) develop a realistic  retino-thalamico-cortical model
(V1). All this theoretical work is done in collaboration with neuroscientists labs: Institut de la Vision, Institut des Neurosciences de la Timone, faculty of medical science of Newcastle, Center of Neuroscience of Valparaiso, Institut des Neurosciences Paris-Saclay .

PhD Students

• Erwan Petit (2023-2026), “Activity waves in the retina: a modelling study”, Funding EDSTIC.
• Jérome Emonet (2021-2024) “A computational model of the retino-thalamo-cortical pathway to study saccadic suppression”, Funding ANR ShootingStar.
• Simone Ebert (2020-2023) “Dynamical Synapses in the Retinal Network”. Funding Institut Neuromod.
• 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 EDSTIC.

Recent publications

1. E. Kartsaki, G. Hilgen, E. Sernagor, B. Cessac, “How does the inner retinal network shape the ganglion cells receptive field : a computational study“, July 2023, Neural Computation, under review.
2. S. Ebert, T. Buffet, B. S. Sermet, O. Marre, B. Cessac Temporal pattern recognition in retinal ganglion cells is mediated by dynamical inhibitory synapses, Nature Comunication, under review, 2023
3. B. Cessac, D. Matzakou-Karvouniari, The non linear dynamics of retinal waves Physica D: Nonlinear Phenomena, Elsevier,Volume 439, November 2022, 133436  https://doi.org/10.1016/j.physd.2022.133436
4. B. Cessac, Retinal processing: insights from mathematical modelling, Journal of Imaging, MDPI, 2022, Special Issue Mathematical Modeling of Human Vision and Its Application to Image Processing, 8 (1), pp.14. ⟨10.3390/jimaging8010014⟩
5. G. Hilgen, E. Kartsaki, V. Kartysh, B. Cessac, E. Sernagor, A novel approach to the functional classification of retinal ganglion cells Open Biology, Royal Society, ⟨10.1101/2021.05.09.443323⟩
6. D. Pamplona, G. Hilgen, M. Hennig, B. Cessac, E. Sernagor, P. Kornprobst, “Receptive field estimation in large visual neuron assemblies using a super-resolution approach Journal of Neurophysiology, American Physiological Society, 2022, 127 (5), pp.1334–1347. ⟨10.1152/jn.00076.2021⟩
7. B. Cessac, I. Ampuero, R. Cofre, Linear response for spiking neuronal networks with unbounded memory. Entropy, MDPI, 2021, 23 (2), pp.155. ⟨10.3390/e23020155⟩
8. S. Souihel, B. Cessac, “On the potential role of lateral connectivity in retinal anticipation“, Journal of Mathematical Neuroscience, BioMed Central, 2021, 11, ⟨10.1186/s13408-020-00101-z⟩
9. R. Cofré, C. Maldonado, B. Cessac, “Thermodynamic Formalism in Neuronal Dynamicsand Spike Train Statistics“, Entropy 2020, 22, 1330.
10. B. Cessac, “The retina as a dynamical system”, in “Recent Trends in Chaotic, Nonlinear and Complex Dynamics”, World Scientific, J. Awrejcewicz, S. Rajasekar and M. Ragulskis Eds, 2020.
11. J. Vohryzek, G. Deco, B. Cessac, M. L. Kringelbach and J. Cabral,« Ghost attractors in spontaneous brain activity: wandering in a repertoire of functionally relevant BOLD phase-locking solutions », Frontiers in Systems Neuroscience, Frontiers, 2020, 14, ⟨10.3389/fnsys.2020.00020⟩.
12. B. Cessac, Linear response in neuronal networks: from neurons dynamics to collective response, Chaos, American Institute of Physics, 2019, 29 (103105).
13. D. Karvouniari, L. Gil, O. Marre, S. Picaud, B.Cessac. A biophysical model explains the spontaneous bursting behavior in the developing retina, Scientific Reports, Nature Publishing Group, 2019, 9 (1), pp.1-23.
14. B. Cessac, The retina: a fascinating object of study for a physicist, Proceedings of the Complex Systems Academy of Excellence, Complex systems Nice, 2018.
15. R. Herzog, M.-J. Escobar , A. G. Palacios, B. Cessac, Dimensionality Reduction and Reliable Observations in Maximum Entropy Models on Spiking Networks, BioArxiv, (2018).
16. 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)
17. 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, volume 7, Article number: 42330 (2017) .
18. 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.

Full publications list

Teaching

• (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

Hobbies

Sport: swimming, biking, jogging, hiking;

I am playing the guitare in a Jazz band, see here;

I wrote a theatrical play, see here.