Analysis of noise-induced phase synchronization in nervous systems: from algorithmic perspective

In many cases, a key step in neuronal information processing is phase synchronization of neurons (as oscillators). Substantial evidence suggests that an universal mechanism is behind the synchronization. Recently, stochastic equations were proposed to model the synchronization. However, it is unclear what force ultimately drives this universal mechanism. From algorithmic perspective, we analyze solutions of these stochastic equations. The result enhances the current analysis for the phase synchronization; importantly, it shows that noise is the ultimate driving force.