Before revision:  In this paper, to ease these limitations : 1) We designed a highly parallel multi-pathway network architecture, inspired by the Inception module in the Artificial Neural Network (ANN) literature . 2) We extended the classic vote-based spike decoding scheme to a Vote-for-All (VFA) decoding layer to reduce the information loss in the spike decoding . 3) We proposed to use adaptive repolarization (i.e. resetting) in the spiking neuron model to  further accelerate the network's learning.
After revision:  In this paper, to ease these limitations : 1) designed a high-parallelism network architecture, inspired by the Inception module in the Artificial Neural Network (ANN) literature . 2) We extended the classic vote-based spike decoding scheme to a Vote-for-All (VFA) decoding layer to reduce the information loss in the spike decoding . 3) We proposed to use adaptive repolarization (i.e. resetting) in the spiking neuron model to further accelerate the network's learning.