Giugliano M, Bove M, Grattarola M
Department of Biophysical and Electronic Engineering, Bioelectronics and Neurobioengineering Group, Universita degli Studi de Genova, Via Opera Pia 11A, Genova I-16145 Italy.
Neural Comput. 1999 Aug 15;11(6):1413-26. doi: 10.1162/089976699300016296.
An efficient implementation of synaptic transmission models in realistic network simulations is an important theme of computational neuroscience. The amount of CPU time required to simulate synaptic interactions can increase as the square of the number of units of such networks, depending on the connectivity convergence. As a consequence, any realistic description of synaptic phenomena, incorporating biophysical details, is computationally highly demanding. We present a consolidating algorithm based on a biophysical extended model of ligand-gated postsynaptic channels, describing short-term plasticity such as synaptic depression. The considerable speed-up of simulation times makes this algorithm suitable for investigating emergent collective effects of short-term depression in large-scale networks of model neurons.
在逼真的网络模拟中高效实现突触传递模型是计算神经科学的一个重要主题。模拟突触相互作用所需的CPU时间量可能会随着此类网络单元数量的平方而增加，这取决于连接汇聚情况。因此，任何包含生物物理细节的突触现象的逼真描述在计算上都要求很高。我们提出了一种基于配体门控突触后通道生物物理扩展模型的整合算法，该模型描述了诸如突触抑制等短期可塑性。模拟时间的显著加速使得该算法适用于研究模型神经元大规模网络中短期抑制的涌现集体效应。
