Spontaneous episodic activity occurs throughout the developing nervous system because immature circuits are hyperexcitable. It is not fully understood how the temporal pattern of this activity is regulated. Here, we study the role of activity-dependent depression of network excitability in the generation and regulation of spontaneous activity in the embryonic chick spinal cord. We demonstrate t...

In this paper, we propose an extended relocation model for warehouses configuration in a supply chain network, in which uncertainty is associated to operational costs, production capacity and demands whereas, existing researches in this area are often restricted to deterministic environments. In real cases, we usually deal with stochastic parameters and this point justifies why the relocation m...

Current network modeling practices usually assess the network performance at specified time interval, i.e. every 5 or 10 years time horizon. Furthermore, they are usually based on partially predictable data, which are being generated through various stochastic procedures. In this research, a new quantitative based methodology which combines combinatorial optimization modeling and transportation...

We numerically investigate the influence of intrinsic channel noise on the dynamical response of delay-coupling in neuronal systems. The stochastic dynamics of the spiking is modeled within a stochastic modification of the standard Hodgkin-Huxley model wherein the delay-coupling accounts for the finite propagation time of an action potential along the neuronal axon. We quantify this delay-coupl...

Petri nets and their extensions are appropriate formalisms for modeling and analysis of communication systems and networks. A number of timed and stochastic extensions have been introduced for Petri nets. Stochastic activity networks (SANs) is one of these extensions that have been used in several projects for modeling and simulation in this area. We have recently introduced coloured stochastic...

A biologically plausible, stochastic, neural network model that exhibits spontaneous transitions between a low-activity (normal) state and a high-activity (epileptic) state is studied by computer simulation. Brief excursions of the network to the high-activity state lead to spontaneous population bursting similar to the behavior observed in hippocampal slices bathed in a high-potassium medium. ...