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Axe Interdisciplinaire de Recherche de l’Université de Nice – Sophia Antipolis

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INRIA de Nice – Sophia Antipolis

Institut National de Recherche en Informatique et Automatique

vendredi 10 octobre 2014


Voir en ligne : Site de l’Institut

Equipes concernées au sein de l’Institut :


Equipe-Projet TOSCA

Site de l’équipe : http://www-sop.inria.fr/tosca/index.html

Composition :

Denis Talay (Responsable)
James Inglis
Etienne Tanré

Voici extraits de notre rapport d’activité 2012 un résumé succinct des intérêts de Tosca pour les Neurosciences et la biologie plus généralement.

Neuroscience and Biology
The interest of TOSCA in biology is developing in three main directions : neuroscience, molecular dynamics and population dynamics. In neuroscience, stochastic methods are developed to analyze stochastic resonance effects, to solve inverse problems and to investigate mean-field/McKean-Vlasov equations. For example, we are studying probabilistic interpretations and Monte Carlo methods for divergence form second-order differential operators with discontinuous coefficients, motivated by the 3D MEG inverse problem. Our research in molecular dynamics focuses on the development of Monte Carlo methods for the Poisson-Boltzmann equation which also involves a divergence form operator, and of original algorithms to construct improved simulation techniques for protein folding or interaction. Finally, our interest in population dynamics comes from ecology, evolution and genetics. For example, we are studying the emergence of diversity through the phenomenon of evolutionary branching in adaptive dynamics. Some collaborations in biostatistics on cancer problems are also being initiated.

Références en lien avec les Neurosciences
- J. Inglis and E. TanreÌ studied with F. Delarue and S. Rubenthaler (Univ. Nice – Sophia Antipolis) the global solvability of a networked system of integrate-and-fire neurons proposed in the neuroscience literature. In the mean-field limit the equation resembles a McKean-Vlasov equation, but is highly non-standard and previous attempts at rigorous analysis were not satisfactory. We here bridge this gap, and shed light on a surprisingly complicated problem [33], http://hal.inria.fr/hal-00747565.
- O. Faugeras, T. Papadopoulos, J. Touboul, M. Bossy, D. Talay, and E. Tanré. The statistics of spikes trains for some types of neuron models. In Neurocomp 2006. 23-24 octobre 2006.
- M. Bossy, A. Grorud, K. Pakdaman, D. Talay, and E. Tanré. Stochasticresonance for the lif model : a stochastic approach. In Neurocomp 2006. 23-24 octobre 2006.
- Global solvability of a networked integrate-and-fire model of McKean-Vlasov type http://hal.inria.fr/hal-00747565

Collaborations locales :

François Delarue et Sylvain Rubenthaler (Laboratoire J.A. Dieudonné)