Before revision:  Overall, our work provides an alternative way to directly implement nonlinear computations in spike coding networks, and expands our understanding about the potential functions of multiplicative synapses. Furthermore, due to the high accuracy and low energy usage of our approach , this work may be of interest for neuromorphic computing.
After revision:  Overall, our work provides an alternative way to directly implement nonlinear computations in spiking neural networks, while keeping all the attractive features of standard SCNs (such as robustness, irregular and sparse firing, and interpretable connectivity). Finally, we discuss the biological plausibility of our approach, and how the high accuracy and low energy usage of our approach , this work may be of interest for neuromorphic computing.