The aim and objectives of this chapter is to present other types of artificial
neuromorphic neurons with capability of reset and recovery. For this reason, the first
section starts with the integrate-and-fire neuron, which has the propensity for reset. The
second section introduces probability theory owing to the fact that many processes in
the brain and central nervous system obey probability laws. The third section
introduces another artificial neuromorphic neuron which employs a Poisson process
and is closer in behaviour to a biological neuron.
Keywords: Bayes theorem, Binomial, Bernoulli, Charging, Depolarization,
Density function, Excitatory, Expected-value, Inhibitory, Mean, Moment, ODE,
Pseudo-random-number-generator, Poisson, Steady-state, Synaptic strength, Spike,
Threshold potential, Uniform distribution, Variance.
