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Maximization of information transmission by a spiking-neuron model predicts changes of synaptic connections that depend on timing of pre- and postsynaptic spikes and on the postsynaptic membrane potential. Under the assumption of Poisson firing statistics, ...
A neuron that is stimulated repeatedly by the same time-dependent stimulus exhibits slightly different spike timing at each trial. We compared the exact solution of the time-dependent firing rate for a stochastically spiking neuron model with refractorines ...
In the present paper we propose a novel method for the identification and modeling of neural networks using extracellular spike recordings. We create a deterministic model of the effective network, whose dynamic behavior fits experimental data. The network ...
We propose a simple method to map a generic threshold model, namely the Spike Response Model, to artificial data of neuronal activity using a minimal amount of a priori information. Here, data are generated by a detailed mathematical model of neuronal acti ...
This work investigates the capacity of Integrate-and-Fire-type (I&F-type) models to quantitatively predict spike trains of real neurons in various laboratory and in vivo-like settings. A step-by-step methodology is developed to build an equivalent effectiv ...
We introduce a two-dimensional integrate-and-fire model that combines an exponential spike mechanism with an adaptation equation, based on recent theoretical findings. We describe a systematic method to estimate its parameters with simple electrophysiologi ...
We study the influence of coupling strength and network topology on synchronization behavior in pulse-coupled networks of bursting neurons. We find that the stability of the completely synchronous state in networks of coupled Hindmarsh-Rose neurons only de ...
We study the influence of coupling strength and network topology on synchronization behavior in pulse-coupled networks of bursting Hindmarsh-Rose neurons. Surprisingly, we find that the stability of the completely synchronous state in such networks only de ...
We investigate the propagation of pulses of spike activity in a neuronal network with feed-forward couplings. The neurons are of the spike-response type with a firing probability that depends linearly on the membrane potential. AFter firing neurons enter a ...
We demonstrate that single-variable integrate-and-fire models can quantitatively capture the dynamics of a physiologically-detailed model for fast-spiking cortical neurons. Through a systematic set of approximations, we reduce the conductance based model t ...
