Stochastic

The Stochastic rule is a simple spiking activity generator that fires based on a fixed probability. At each time step, the neuron independently samples a random value to determine whether it spikes. This rule can be used to simulate spontaneous spiking activity or probabilistic inputs to a network.

The update behavior is defined as:

\[P(\text{spike}) = p \\ a = \begin{cases} 1.0, & \text{if spiked} \\ 0.0, & \text{otherwise} \end{cases}\]

Where:

• \(p\) is the firing probability (between 0 and 1),
• \(a\) is the neuron’s activation,
• A spike is recorded if a randomly drawn number is less than \(p\).

This rule produces binary output and should be used with spiking neuron networks or event-driven simulations.

Parameters

• Firing Probability: The probability that the neuron will spike (i.e., emit an activation of 1.0) at each time step.

For all other parameters, see common neuron properties