Replicating the function of neural system in real organism is non-trivial, given the fact that the machinery underlying the observed behaviour is not fully understood32. Existing works have proposed different paradigms to model the behaviour neural system. For example, previous work uses a network of nonlinear oscillator to construct the Central Pattern Generator11. We believe the use of different models has its own pros and cons. The oscillator with inherent properties of limit cycle and attraction point could generate the basic pattern with no intervention from higher control system. The high-level neural system is encoded as a look-up table11, which is pre-computed and discretized. In comparison, the current work, which is based on spiking neuron models, provides a unified representation of neural system. The spiking pattern of the unit neurons can be used to seamlessly connect the procedures of sensory processing, high-level commands and low-level control strategy. Such a unified representation lays the foundation for processing sensory information via large-scale networks.