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Poisson Model of Spike Generation (2000)
| Citations: | 7 - 0 self |
BibTeX
@MISC{Heeger00poissonmodel,
author = {David Heeger and Professor David Heeger},
title = {Poisson Model of Spike Generation},
year = {2000}
}
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Abstract
ring rate to be very large at particular moments in time so that the probability of firing would then be arbitrarily close to 1. Certain features of neuronal firing, however, violate the independent spike hypothesis. Following the generation of an action potential, there is an interval of time known as the absolute refractory period during which the neuron can not fire another spike. For a longer interval known as the relative refractory period, the likelihood of a spike being fired is much reduced. Bursting is another non-Poisson feature of neuronal spiking. Some neurons fire action potentials is clusters or bursts, and these tend to be poorly described a purely Poisson spike-generation process. Below, I present ways of extending the Poisson model to account for refractoriness and bursting. 1 Probability and Random Processes A random variable is a number assigned to every outcome of an experiment. This could be the outcome of the roll of a die, or th
