activity
20092021
most citedNoise-induced behaviors in neural mean field dynamics

97 citations · 144 across the 19 of their papers we have counts for

collaborators

19 papers

q-bio.NC2021★ 3 cited

Spatial and color hallucinations in a mathematical model of primary visual cortex

Olivier D. Faugeras, Anna Song, Romain Veltz

We study a simplified model of the representation of colors in the primate primary cortical visual area V1. The model is described by an initial value problem related to a Hammerst…

math.PR2019★ 2 cited

The meanfield limit of a network of Hopfield neurons with correlated synaptic weights

Olivier Faugeras, James Maclaurin, Etienne Tanre

We study the asymptotic behaviour for asymmetric neuronal dynamics in a network of Hopfield neurons. The randomness in the network is modelled by random couplings which are centere…

q-bio.NC2018★ 19 cited

A neural field model for color perception unifying assimilation and contrast

Anna Song, Olivier Faugeras, Romain Veltz

We address the question of color-space interactions in the brain, by proposing a neural field model of color perception with spatial context for the visual area V1 of the cortex. O…

math.PR2014★ 2 cited

Clarification and complement to "Mean-field description and propagation of chaos in networks of Hodgkin-Huxley and FitzHugh-Nagumo neurons"

Mireille Bossy, Olivier Faugeras, Denis Talay

In this note, we clarify the well-posedness of the limit equations to the mean-field -neuron models proposed in Baladron et al. and we prove the associated propagation of chaos…

math.PR2014★ 4 cited

On the Hamiltonian structure of large deviations in stochastic hybrid systems

Paul Bressloff, Olivier Faugeras

We develop the connection between large deviation theory and more applied approaches to stochastic hybrid systems by highlighting a common underlying Hamiltonian structure. A stoch…

math.PR2014

Asymptotic description of stochastic neural networks. II - Characterization of the limit law

Olivier Faugeras, James MacLaurin

We continue the development, started in of the asymptotic description of certain stochastic neural networks. We use the Large Deviation Principle (LDP) and the good rate function H…