Event-driven simulation of the tempotron spiking neuron

Bo Zhao, Qiang Yu, Ruoxi Ding, Shoushun Chen, Huajin Tang

Abstract: This paper presents an event-driven method for the simulation of the tempotron spiking neuron. We propose an efficient dummy-spike-based approach to deal with the two-exponential decay postsynaptic potential kernel. Experimental results show that event-driven simulation runs much faster than conventional time-driven simulation. We also propose a simple but efficient method to solve a same-timestamp problem encountered in event-driven simulation of a simplified tempotron neuron which uses only single-exponential decay.