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Section: New Results

Macroscopic limits of stochastic neural networks and neural fields

Pinwheel-Dipole configuration in cat visual cortex

Participants : Jérôme Ribot [CIRB] , Alberto Romagnoni [CIRB] , Chantal Milleret [CIRB] , Daniel Bennequin [CIRB] , Jonathan Touboul.

One fascinating aspect of the brain is its ability to process information in a fast and reliable manner. The functional architecture is thought to play a central role in this task, by encoding efficiently complex stimuli and facilitating higher level processing. In the early visual cortex of higher mammals, information is processed within functional maps whose layout is thought to underlie visual perception. The possible principles underlying the topology of the different maps, as well as the role of a specific functional architecture on information processing, is however poorly understood.

These results shed new light on the principles at play in the emergence of functional architecture of cortical maps, as well as their potential role in processing information.

Absorption properties of stochastic equations with Hölder diffusion coefficients

Participants : Jonathan Touboul, Gilles Wainrib [ENS] .

In [29] , we address the absorption properties of a class of stochastic differential equations around singular points where both the drift and diffusion functions vanish. According to the Hölder coefficient alpha of the diffusion function around the singular point, we identify different regimes. Stability of the absorbing state, large deviations for the absorption time, existence of stationary or quasi-stationary distributions are discussed. In particular, we show that quasi-stationary distributions only exist for alpha < 3/4, and for alpha in the interval (3/4, 1), no quasi-stationary distribution is found and numerical simulations tend to show that the process conditioned on not being absorbed initiates an almost sure exponential convergence towards the absorbing state (as is demonstrated to be true for alpha = 1). Applications of these results to stochastic bifurcations are discussed.

On a kinetic FitzHugh-Nagumo model of neuronal network

Participants : Stéphane Mischler [CEREMADE] , Cristóbal Quiñinao [CIRB] , Jonathan Touboul.

We investigate in [33] the existence and uniqueness of solutions of a McKean-Vlasov evolution PDE representing the macroscopic behavior of interacting Fitzhugh-Nagumo neurons. This equation is hypoelliptic, nonlocal and has unbounded coefficients. We proved existence of a solution to the evolution equation and non trivial stationary solutions. Moreover, we demonstrated uniqueness of the stationary solution in the weakly nonlinear regime. Eventually, using a semigroup factorisation method, we showed exponential nonlinear stability in the small connectivity regime.