Recurrent spiking neural networks (RSNNs) hold great potential for advancing artificial general intelligence, as they draw inspiration from the biological nervous system and show promise in modeling complex dynamics.

Deep learning models achievetremendous successes across amultitude oftasks, yettheir training and inference often yield high computational costs and long processing times [11,22].