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

Mein Concerns: The main motivation of the paper, to solve Backprop in spiking neurons, is not an open problem in computational neuroscience. In fact, learning in spiking neural networks using standard methods is not a problem at all as recent work shows. It has been demonstrated multiple times that Backprop can be applied without much changes by applying pseudo-derivatives to circumvent the non-differentiable spikes. This works very well in practice and scales up to midscale benchmark problems (and possibly beyond) without performance loss compared to classical (analog) neural networks. In this context it hard to pinpoint the main innovation of the manuscript.