MASCART , Cyrille

Stochastic and point processes are often used to model networks of spiking neurons. However, the number of neurons, even in a small mammal brain, is at least a few millions. There is therefore a strong need for efficient simulation algorithms. Nevertheless, traditional algorithms for point process simulation cannot simulate such large networks...

We present a new algorithm to efficiently simulate random models of large neural networks satisfying the property of time asynchrony. The model parameters (average firing rate, number of neurons, synaptic connection probability, and postsynaptic duration) are of the order of magnitude of a small mammalian brain, or of human brain areas. Through...

We derive new discrete event simulation algorithms for marked time point processes. The main idea is to couple a special structure, namely the associated local independence graph, as defined by Didelez [13], with the activity tracking algorithm [24] for achieving high performance asynchronous simulations. With respect to classical algorithms,...

article dans Nice Matin page Santé relatif à la "Semaine du cerveau"

Since the pioneering works of Lapicque [17] and of Hodgkin and Huxley [16], several types of models have been addressed to describe the evolution in time of the potential of the membrane of a neuron. In this note, we investigate a connected version of N neurons obeying the leaky integrate and fire model, previously introduced in [1, 2, 3, 7, 6,...

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