Optimal synchronization in small-world biological neural networks with time-varying weights

In this paper, a new model of small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with time-varying weights is proposed. Then the synchronization phenomenon of small-world biological neural networks evoked by the learning rate is studied. The study shows that there exists an optimal synchronization state by changing the learning rate.