Spiking Neural Network

Neural networks that process information through discrete temporal events (spikes) rather than continuous values — the computational model underlying neuromorphic systems.

Unlike artificial neural networks that use continuous activations, spiking neural networks (SNNs) communicate through precisely-timed pulses. Information is encoded in spike timing, frequency, and patterns across populations of neurons.

Systems Connection

An SNN is a system whose components (neurons) communicate through discrete flows (spikes). The state of the network is distributed across membrane potentials and synaptic weights. Emergent computation arises from temporal dynamics — the precise timing of spikes enables computations impossible with rate-based coding.

See Also

• Neuromorphics — parent domain
• Temporal Coding — how spikes encode information
• Synaptic Plasticity — how SNNs learn