Department of Mathematics and Informatics, University of Palermo, Palermo, Italy.
Institute of Biophysics, National Research Council, Palermo, Italy.
Sci Rep. 2021 Oct 21;11(1):20792. doi: 10.1038/s41598-021-00283-w.
A number of potentially important mechanisms have been identified as key players to generate epileptiform activity, such as genetic mutations, activity-dependent alteration of synaptic functions, and functional network reorganization at the macroscopic level. Here we study how network connectivity at cellular level can affect the onset of epileptiform activity, using computational model networks with different wiring properties. The model suggests that networks connected as in real brain circuits are more resistant to generate seizure-like activity. The results suggest new experimentally testable predictions on the cellular network connectivity in epileptic individuals, and highlight the importance of using the appropriate network connectivity to investigate epileptiform activity with computational models.
已经确定了一些潜在的重要机制，它们是产生癫痫样活动的关键因素，例如基因突变、突触功能的活动依赖性改变以及宏观水平上的功能网络重组。在这里，我们使用具有不同布线特性的计算模型网络来研究细胞水平的网络连接如何影响癫痫样活动的发生。该模型表明，连接方式与真实大脑电路相似的网络更能抵抗产生类似癫痫发作的活动。研究结果为癫痫患者的细胞网络连接提出了新的可在实验中验证的预测，并强调了使用适当的网络连接来通过计算模型研究癫痫样活动的重要性。
