Gerstner W, Ritz R, van Hemmen J L
Institut für Physik, Technischen Universität München, Germany.
Biol Cybern. 1993;68(4):363-74. doi: 10.1007/BF00201861.
A model of an associative network of spiking neurons with stationary states, globally locked oscillations, and weakly locked oscillatory states is presented and analyzed. The network is close to biology in the following sense. First, the neurons spike and our model includes an absolute refractory period after each spike. Second, we consider a distribution of axonal delay times. Finally, we describe synaptic signal transmission by excitatory and inhibitory potentials (EPSP and IPSP) with a realistic shape, that is, through a response kernel. During retrieval of a pattern, all active neurons exhibit periodic spike bursts which may or may not be synchronized ('locked') into a coherent oscillation. We derive an analytical condition of locking and calculate the period of collective activity during oscillatory retrieval. In a stationary retrieval state, the overlap assumes a constant value proportional to the mean firing rate of the neurons. It is argued that in a biological network an intermediate scenario of 'weak locking' is most likely.
提出并分析了一个具有静止状态、全局锁定振荡和弱锁定振荡状态的脉冲神经元联想网络模型。该网络在以下意义上接近生物学。首先，神经元产生脉冲，我们的模型包括每个脉冲后的绝对不应期。其次，我们考虑轴突延迟时间的分布。最后，我们用具有现实形状的兴奋性和抑制性电位（EPSP和IPSP）来描述突触信号传递，即通过响应核。在模式检索过程中，所有活跃神经元都会表现出周期性脉冲串，这些脉冲串可能会也可能不会同步（“锁定”）成相干振荡。我们推导了锁定的分析条件，并计算了振荡检索期间集体活动的周期。在静止检索状态下，重叠度假定为与神经元平均放电率成比例的恒定值。有人认为，在生物网络中，“弱锁定”的中间情况最有可能出现。
