论文标题
小世界神经网络中的相干共振和随机同步：在存在峰值依赖性可塑性的情况下的相互作用
Coherence resonance and stochastic synchronization in a small-world neural network: An interplay in the presence of spike-timing-dependent plasticity
论文作者
论文摘要
相干共振（CR），随机同步（SS）和峰值依赖性可塑性（STDP）是生物神经网络中无处不在的动力学过程。是否存在最佳网络和STDP配置，其中CR和SS的明显是一个基本的关注问题，仍然难以捉摸。我们希望这种配置能够使大脑能够使这些现象的协同和最佳使用能够有效地处理信息。本文考虑了一个小世界网络，该网络是由通道噪声和STDP驱动的Hodgkin-Huxley神经元，并具有不对称的Hebbian时间窗口。数值结果表明特定的网络拓扑和STDP参数间隔，其中CR和SS可以同时增强。我们的结果表明，最佳调整的固有背景噪声，STDP规则和网络拓扑可以在增强神经系统中的点火和同步的时间精度方面发挥建设性作用。
Coherence resonance (CR), stochastic synchronization (SS), and spike-timing-dependent plasticity (STDP) are ubiquitous dynamical processes in biological neural networks. Whether there exists an optimal network and STDP configuration at which CR and SS are both pronounced is a fundamental question of interest that is still elusive. We expect such a configuration to enable the brain to make synergistic and optimal use of these phenomena to process information efficiently. This paper considers a small-world network of excitable Hodgkin-Huxley neurons driven by channel noise and STDP with an asymmetric Hebbian time window. Numerical results indicate specific network topology and STDP parameter intervals in which CR and SS can be simultaneously enhanced. Our results imply that an optimally tuned inherent background noise, STDP rule, and network topology can play a constructive role in enhancing both the time precision of firing and the synchronization in neural systems.
