【摘要】 研究一种简化的整合-激发神经网络的集体行为。该模型显示出短时行为并快速收敛到周期激发模式,同时伴有局部的同步脉冲发放行为。用标准欧拉算法研究了该模型的动态行为,结果显示当用标准欧拉算法研究用以描述大型整合-激发神经网络的动态行为的微分方程时,必须用很小的时间步长才能准确产生局部的同步脉冲发放。为此,提出一种改进的欧拉算法,该方法用一个线性插值来确定激发时间,大大提高了网络的性能。更多还原

【Abstract】 The collective behavior of an integrate-and-fire(IF)network is investigated.It is shown that the model exhibits the short-time behavior and rapidly converges to(approximately)periodic firing patterns with locally synchronized action potentials.The dynamics of the IF neurons is studied with the standard Euler algorithm.It is shown that very small time steps are required to reproduce correctly the local synchronization when the differential system describing their dynamics is integrated with the standard Euler algorithm.And a simple improvement of this algorithm is proposed.The improved Euler algorithm determines the firing time by adding a linear interpolation scheme,which greatly improves the performance of the network.更多还原