Reviews: Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks

The authors propose a variant of the backpropagation through time (BPTT) algorithm for spiking neural networks (SNNs). An interesting aspect is that, instead of unrolling the network computation over time, backpropagation over spike trains is performed. The algorithm is tested on various datasets, achieving state-of-the-art results for SNNs. The approach is very original and innovative. The results are very good and of interest for the community interested in spiking neural networks.