We study the effects of synaptic plasticity on the determination of firing period and relative phases in a network of two oscillatory neurons coupled with reciprocal inhibition. We combine the phase response curves of the neurons with the short-term synaptic plasticity properties of the synapses to define Poincaré maps for the activity of an oscillatory network. Fixed points of these maps correspond to the phase-locked modes of the network. These maps allow us to analyze the dependence of the resulting network activity on the properties of network components. Using a combination of analysis and simulations, we show how various parameters of the model affect the existence and stability of phase-locked solutions. We find conditions on the synaptic plasticity profiles and the phase response curves of the neurons for the network to be able to maintain a constant firing period, while varying the phase of locking between the neurons or vice versa. A generalization to cobwebbing for two-dimensional maps is also discussed.

中文翻译：

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突触可塑性对两个振荡神经元网络中相位和周期锁定的影响。

我们研究突触可塑性对确定两个振荡神经元网络中的放电周期和相对相位的影响，并伴有相互抑制。我们将神经元的相位响应曲线与突触的短期突触可塑性特性相结合，以定义振荡网络活动的庞加莱映射。这些地图的固定点对应于网络的锁相模式。这些地图使我们能够分析由此产生的网络活动对网络组件属性的依赖性。结合分析和模拟，我们展示了模型的各种参数如何影响锁相解的存在性和稳定性。我们发现网络的突触可塑性曲线和神经元相位响应曲线的条件能够保持恒定的放电周期，同时改变神经元之间的锁定相位，反之亦然。还讨论了对二维地图的蜘蛛网的概括。