Can you explain more? Why would that be the case? What is being passed from one layer to the next is not a linear value but the delay until the next spike, which is very different.
But I understand that they simulate the spikes as integer events in the forward pass (as described here https://github.com/BICLab/Int2Spike) and calculate a continuous gradient based on high resolution weights for the backward pass.
This seems to be very similar to the straight-through-estimator (STE) approach that us usually used for quantization aware training. I may be wrong though.
