Spike-timing-dependent plasticity enhances chaotic resonance in small-world network

Abstract

Weak signals can be detected by a nonlinear system with an appropriate chaotic current input, known as the chaotic resonance (CR). Based on Watts–Strogatz small-world network, the effects of Spike-timing-dependent plasticity (STDP) on CR were systematically investigated. Numerical simulations showed that, under moderately strong chaotic current inputs, CR is enhanced due to the increase in average coupling strength after STDP learning. The above-mentioned phenomenon was observed even with changes in frequency and the network topology. For networks with different initial coupling strengths, their responses to weak signals after STDP learning are almost the same, indicating that networks with weaker coupling strengths have better plasticity. In addition, the effects of adjusting STDP windows on CR is also investigated. It was found that CR is promoted by STDP with a relatively larger long-time potentiation window, while, suppressed by a STDP with a relatively larger long-time depression window. Also, the area difference between long-time depression and long-time potentiation windows is highly correlated with average coupling strength after STDP learning. These conclusions might provide novel insights into weak signal detection and information transmission in different adaptive neural networks.