Spikes are all-or-none electrical impulses that biological neurons emit when
sufficiently stimulated. They are the only information vector between neurons. The spike times are known to play an important role in how neurons process information. Spiking neural networks (SNN) are thus more biologically realistic than the artificial neural networks (ANN) used in deep learning, and are arguably the most viable option if one wants to understand how the brain computes at the neuronal description level. But SNNs are also appealing for AI, because they can be implemented efficiently on low-power neuromorphic chips.
Link: https://bluemeet.aut.ac.ir/ch/ee-webinar/guest