Carrillo Richard R, Ros Eduardo, Barbour Boris, Boucheny Christian, Coenen Olivier
Department of Computer Architecture and Technology, E.T.S.I. Informática, University of Granada, E-18071 Granada, Spain.
Biosystems. 2007 Feb;87(2-3):275-80. doi: 10.1016/j.biosystems.2006.09.023. Epub 2006 Sep 10.
Most neural communication and processing tasks are driven by spikes. This has enabled the application of the event-driven simulation schemes. However the simulation of spiking neural networks based on complex models that cannot be simplified to analytical expressions (requiring numerical calculation) is very time consuming. Here we describe briefly an event-driven simulation scheme that uses pre-calculated table-based neuron characterizations to avoid numerical calculations during a network simulation, allowing the simulation of large-scale neural systems. More concretely we explain how electrical coupling can be simulated efficiently within this computation scheme, reproducing synchronization processes observed in detailed simulations of neural populations.
大多数神经通信和处理任务由尖峰驱动。这使得事件驱动模拟方案得以应用。然而，基于无法简化为解析表达式（需要数值计算）的复杂模型对脉冲神经网络进行模拟非常耗时。在此，我们简要描述一种事件驱动模拟方案，该方案使用预先计算的基于表格的神经元特征描述，以避免在网络模拟期间进行数值计算，从而能够模拟大规模神经系统。更具体地说，我们解释了如何在这种计算方案中高效模拟电耦合，再现神经群体详细模拟中观察到的同步过程。
