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Mathematical and Computational Neuroscience

  • Leader : Olivier Faugeras
  • Research center(s) : CRI Sophia Antipolis - Méditerranée
  • Field : Digital Health, Biology and Earth
  • Theme : Computational Neuroscience and Medicine
  • Partner(s) : Université Nice - Sophia Antipolis,CNRS
  • Collaborator(s) : Laboratoire Jean-Alexandre Dieudonné (JAD) (UMR7351)

Team presentation

NeuroMathComp focuses on the exploration of the brain from the mathematical and computational perspectives. We want to unveil the principles that govern the functioning of neurons and assemblies thereof and to use our results to bridge the gap between biological and computational vision. Our work is very mathematical but we make heavy use of computers for numerical experiments and simulations. We have close ties with several top groups in biological neuroscience. We are pursuing the idea that the "unreasonable effectiveness of mathematics" can also be brought to bear on neuroscience, as in physics. Computational neuroscience attempts to build models of neurons at a variety of levels, microscopic, i.e. the minicolumn containing of the order of one hundred or so neurons, mesoscopic, i.e. the macrocolumn containing of the order of 10.000-100.000 neurons, and macroscopic, i.e. a cortical area such as the primary visual area V1. Modeling such assemblies of neurons and simulating their behaviour involves putting together a mixture of the most recent results in neurophysiology with such advanced mathematics as dynamic systems theory, bifurcation theory, probability theory, stochastic calculus, and statistics, as well as the use of simulation tools. We were part of the Odyssée team that was created in 2002 by Olivier Faugeras. NeuroMathComp is a joint project team between INRIA (Méditerranée and Rocquencourt), Ecole Normale Supérieure de Paris (DI), Université de Nice Sophia-Antipolis (JAD Laboratory) and CNRS (LIENS, UMR 8548. LJAD, UMR 6621)

Research themes

We have four main research directions
  • Modeling of spiking neurons
  • Neural fields
  • Mean-field approaches
  • Visual perception modeling

International and industrial relations

We have many international relations through our EC-funded (FACETS, SEARISE) and ERC-funded ( NerVi) grants.

Keywords: Neuroscience Neurons Neuronal populations Cortical areas Visual areas Stochastic calculus Mean field Bifurcations Neurally inspired computer algorithms