Neuron is the basic building block of an SNN and several interconnected neurons form the input, hidden and output layers. This neuron imitates the general [integrate and fire model] (http://neuronaldynamics.epfl.ch/online/Ch1.S3.html).
- In the absence of stimulus, the membrane possesses a resting potential. Every input spike from connected neurons increases or decrease its membrane potential.
- When the potential crosses a threshold value, neuron enters into refractory period in which no new input is allowed and the potential remains constant.
- To avoid strong negative polarization of membrane, its potential is limited by Pmin.
- As long as Pn>Pmin, there is a constant leakage of potential.
Above graph shows the membrane potential throughout the 50 time units (TU) as a result of input spike train. Below is the corresponding randomly generated input spike train.
