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Sequential activation of neurons that occurs during "offline" states, such as sleep or awake rest, is correlated with neural sequences recorded during preceding exploration phases. This so-called reactivation, or replay, has been observed in a number of different brain regions such as the striatum, prefrontal cortex, primary visual cortex and, most(More)
Neuronal variability has been thought to play an important role in the brain. As the variability mainly comes from the uncertainty in biophysical mechanisms, stochastic neuron models have been proposed for studying how neurons compute with noise. However, most papers are limited to simulating stochastic neurons in a digital computer. The speed and the(More)
We propose a new estimation method for the characterization of the Hodgkin-Huxley formalism. This method is an alternative technique to the classical estimation methods associated with voltage clamp measurements. It uses voltage clamp type recordings, but is based on the differential evolution algorithm. The parameters of an ionic channel are estimated(More)
Nowadays, many software solutions are currently available for simulating neuron models. Less conventional than software-based systems, hardware-based solutions generally combine digital and analog forms of computation. In previous work, we designed several neuromimetic chips, including the Galway chip that we used for this paper. These silicon neurons are(More)
Anaesthetic agents are known to affect extra-synaptic GABAergic receptors, which induce tonic inhibitory currents. Since these receptors are very sensitive to small concentrations of agents, they are supposed to play an important role in the underlying neural mechanism of general anaesthesia. Moreover anaesthetic agents modulate the encephalographic(More)
When dealing with non-linear estimation issues, metaheuristics are often used. In addition to genetic algorithms (GAs), simulating annealing (SA), etc., a great deal of interest has been paid to differential evolution (DE). Although this algorithm requires less iterations than GAs or SA to solve optimization issues, its computational cost can still be(More)
— This paper presents an original method to adjust parameters for a neuromimetic IC based on neuron conductance-based models (Hodgkin-Huxley formalism). To adjust the chip, we use a Metaheuristic, the Differential Evolution algorithm (DE). We detail the DE for its implementation in our hardware neural simulator. The DE estimates in the same time all the(More)