A neuronal model intended to target highly sonorant periods of a speech stream is presented. The model—“Spike-V”—uses habituation and Hebbian learning in opposition to each other to dynamically adjust its behavior. Acting in realtime, driven by only the signal, Spike-V produces a spike-train in which each spike corresponds to roughly the center of a period of high sonority (i.e. a vowel) in the...

A twofold spike-timing dependent stochastic synaptic model is used along with a leaky Integrate-and-Fire neuronal model to predict the spike timing of a single post-synaptic neuron in the lateral geniculate nucleus, knowing the spike train on the pre-synaptic side (i.e. in a retinal ganglion cell). In this synaptic model, spike-timing dependency is introduced for both the magnitude and relaxati...

In the cortex, the timing of successive action potentials is highly irregular. The interpretation of this irregularity has led to two divergent views of cortical organization. On the one hand, the irregularity might arise from stochastic forces. If so, the irregular interspike interval reflects a random process and implies that an instantaneous estimate of the spike rate can be obtained by aver...

in order to investigate the indices of drought tolerance, correlation coefficient and path analysis at deficit irrigation and nitrogen experiment, this experiment was conducted as split plot arranged in a randomized complete block design (rcbd) with three replications during 2000-2003 for wheat at maragheh agricultural research station of dari. the treatments were included four levels of defici...

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 activity. The model neuron is driven with in-vivo-like current injected, and we test to which extent it is possible to predict the spike train of...

Reduced models of neuronal activity such as integrate-and-fire models allow a description of neuronal dynamics in simple, intuitive terms and are easy to simulate numerically. We present a method to fit an integrate-and-fire-type model of neuronal activity, namely a modified version of the spike response model, to a detailed Hodgkin-Huxley-type neuron model driven by stochastic spike arrival. I...