International audienceThe cortex is a very large network characterized by a complex connectivity including at least two scales: a microscopic scale at which the interconnections are non-specific and very dense, while macroscopic connectivity patterns connecting different regions of the brain at larger scale are extremely sparse. This motivates to analyze the behavior of networks with multiscale coupling, in which a neuron is connected to its $v(N)$ nearest-neighbors where $v(N)=o(N)$, and in which the probability of macroscopic connection between two neurons vanishes. These are called singular multi-scale connectivity patterns. We introduce a class of such networks and derive their continuum limit. We show convergence in law and propagation...
International audienceRealistic networks display heterogeneous transmission delays. We analyze here ...
International audienceRealistic networks display heterogeneous transmission delays. We analyze here ...
In this article, we are interested in the behavior of a fully connectednetwork of $N$ neurons, where...
International audienceThe cortex is a very large network characterized by a complex connectivity inc...
International audienceNetworks of the brain are composed of a very large number of neurons connected...
International audienceNetworks of the brain are composed of a very large number of neurons connected...
International audienceNetworks of the brain are composed of a very large number of neurons connected...
55 pages, 9 figuresWe derive the mean-field equations arising as the limit of a network of interacti...
The development of new experimental techniques in parallel with a continuous increase of computation...
International audienceABSTRACT: We derive the mean-field equations arising as the limit of a network...
International audienceABSTRACT: We derive the mean-field equations arising as the limit of a network...
International audienceWe consider the problem of the limit of bio-inspired spatially extended neuron...
International audienceABSTRACT: We derive the mean-field equations arising as the limit of a network...
International audienceABSTRACT: We derive the mean-field equations arising as the limit of a network...
We consider an idealized network, formed by N neurons individually described by the FitzHugh-Nagumo ...
International audienceRealistic networks display heterogeneous transmission delays. We analyze here ...
International audienceRealistic networks display heterogeneous transmission delays. We analyze here ...
In this article, we are interested in the behavior of a fully connectednetwork of $N$ neurons, where...
International audienceThe cortex is a very large network characterized by a complex connectivity inc...
International audienceNetworks of the brain are composed of a very large number of neurons connected...
International audienceNetworks of the brain are composed of a very large number of neurons connected...
International audienceNetworks of the brain are composed of a very large number of neurons connected...
55 pages, 9 figuresWe derive the mean-field equations arising as the limit of a network of interacti...
The development of new experimental techniques in parallel with a continuous increase of computation...
International audienceABSTRACT: We derive the mean-field equations arising as the limit of a network...
International audienceABSTRACT: We derive the mean-field equations arising as the limit of a network...
International audienceWe consider the problem of the limit of bio-inspired spatially extended neuron...
International audienceABSTRACT: We derive the mean-field equations arising as the limit of a network...
International audienceABSTRACT: We derive the mean-field equations arising as the limit of a network...
We consider an idealized network, formed by N neurons individually described by the FitzHugh-Nagumo ...
International audienceRealistic networks display heterogeneous transmission delays. We analyze here ...
International audienceRealistic networks display heterogeneous transmission delays. We analyze here ...
In this article, we are interested in the behavior of a fully connectednetwork of $N$ neurons, where...