Spiking Neural Networks (SNNs) represent the third generation of Artificial Neural Networks (ANNs), directly inspired by the human brain's remarkable energy efficiency. Unlike traditional ANNs, communication between neurons in SNNs occurs through discrete spikes, with information encoded in the timing of these spikes. This spike-based communication makes SNNs highly suitable for deployment on dedicated digital hardware co-processors. In the digital domain, spikes can be treated as single-bit events, active when a spike occurs and inactive otherwise. This reduces the memory footprint and interconnect resources, thanks to the small (1-bit) activations, and conserves power by updating neurons only when spikes are received.