Sentence examples for model of spike from inspiring English sources
We examined which components of the simple model of spike generation are responsible for different components of the somatic action potential.
The FHN model is a phenomenological model of spike generation, comprising of 2 variables.
In this paper, a novel, simplified and computationally efficient model of spike response model (SRM) neuron with spike-time dependent plasticity (STDP) learning is presented.
In these studies, and in the present paper, beyond-pairwise correlations are defined by comparing with a pairwise maximum entropy (PME) model of spike trains: that is, a statistical model built with minimal assumptions about collective spiking beyond the rates of spiking in single cells and correlations in the spikes from cell pairs.
The goal of our mathematical modeling is to seek a simplest or minimal mechanism to mimic the three response patterns shown by biological neurons, rather than giving a detailed biophysical model of spike generation.
In a regression model of spike rates, predictors for LFP-derived PC1 and PC2 steal variance away from a "chosen value" predictor but not from other task-related predictors.
A stochastic model of spike-timing-dependent plasticity (STDP) proposes that spike timing influences the probability but not the amplitude of synaptic strength change at single synapses.
Izhikevich, E. M. Simple model of spiking neurons.
We present a model of spiking neuron that emulates the output of the usual static neurons with sigmoidal activation functions.
Here, we use a biophysically-based model of spiking cells in the basal ganglia (Terman et al., Journal of Neuroscience, 22, 2963-2976, 2002; Rubin and Terman, Journal of Computational Neuroscience, 16, 211-235, 2004) to provide computational evidence that alternative temporal patterns of DBS inputs might be equally effective as the standard high-frequency waveforms, but require lower amplitudes.
To answer this, we compare the population spike-count distribution (P_{mathrm{EIF}} k)) from the EIF model against that which would be predicted for a pairwise maximum entropy (PME) model of spiking neurons.
