Spiking Neuron Model with Improved Plausibility using Artificial Bee Colony Algorithm

This paper presents an artificial bee colony algorithm optimized Izhikevich neuron simulation, which more closely matches the various spike patterns produced by biological neurons compared to the existing works. Here, the artificial bee colony algorithm is used to find the coefficients for the approximated function of the Izhikevich model. From the simulation results, it can be seen that the obtained model closely matches with the theoretical model for the entire membrane potential range. An optimized Izhikevich neuron model is presented here, which is more biologically plausible than the existing works, and at the same time utilizes less hardware, making it suitable for neuroprosthetic applications.