Gritsun T A, Le Feber J, Stegenga J, Rutten W L C
Institute for Biomedical Technology and Technical Medicine (MIRA), University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands.
Biol Cybern. 2010 Apr;102(4):293-310. doi: 10.1007/s00422-010-0366-x. Epub 2010 Feb 16.
One of the most specific and exhibited features in the electrical activity of dissociated cultured neural networks (NNs) is the phenomenon of synchronized bursts, whose profiles vary widely in shape, width and firing rate. On the way to understanding the organization and behavior of biological NNs, we reproduced those features with random connectivity network models with 5,000 neurons. While the common approach to induce bursting behavior in neuronal network models is noise injection, there is experimental evidence suggesting the existence of pacemaker-like neurons. In our simulations noise did evoke bursts, but with an unrealistically gentle rising slope. We show that a small subset of 'pacemaker' neurons can trigger bursts with a more realistic profile. We found that adding pacemaker-like neurons as well as adaptive synapses yield burst features (shape, width, and height of the main phase) in the same ranges as obtained experimentally. Finally, we demonstrate how changes in network connectivity, transmission delays, and excitatory fraction influence network burst features quantitatively.
解离培养神经网络（NNs）电活动中最具特异性且表现出的特征之一是同步爆发现象，其爆发轮廓在形状、宽度和发放率方面差异很大。在理解生物神经网络的组织和行为的过程中，我们用具有5000个神经元的随机连接网络模型重现了这些特征。虽然在神经网络模型中诱导爆发行为的常见方法是噪声注入，但有实验证据表明存在类似起搏器的神经元。在我们的模拟中，噪声确实引发了爆发，但上升斜率不切实际地平缓。我们表明，一小部分“起搏器”神经元可以触发具有更现实轮廓的爆发。我们发现，添加类似起搏器的神经元以及适应性突触会产生与实验获得的相同范围内的爆发特征（主相的形状、宽度和高度）。最后，我们展示了网络连接性、传输延迟和兴奋性比例的变化如何定量地影响网络爆发特征。
