Abdullahi Aminu T, Adamu Lawan H
Department of Psychiatry, Aminu Kano Teaching Hospital, Kano, Nigeria.
Neurosciences (Riyadh). 2017 Apr;22(2):85-93. doi: 10.17712/nsj.2017.2.20160455.
Epilepsy is a chronic neurological condition, following some trigger, transforming a normal brain to one that produces recurrent unprovoked seizures. In the search for the mechanisms that best explain the epileptogenic process, there is a growing body of evidence suggesting that the epilepsies are network level disorders. In this review, we briefly describe the concept of neuronal networks and highlight 2 methods used to analyse such networks. The first method, graph theory, is used to describe general characteristics of a network to facilitate comparison between normal and abnormal networks. The second, dynamic causal modelling, is useful in the analysis of the pathways of seizure spread. We concluded that the end results of the epileptogenic process are best understood as abnormalities of neuronal circuitry and not simply as molecular or cellular abnormalities. The network approach promises to generate new understanding and more targeted treatment of epilepsy.
癫痫是一种慢性神经疾病，在受到某些触发因素影响后，会使正常大脑转变为一个反复出现无端癫痫发作的大脑。在探寻最能解释癫痫发生过程的机制时，越来越多的证据表明癫痫是网络层面的疾病。在本综述中，我们简要描述神经元网络的概念，并重点介绍用于分析此类网络的两种方法。第一种方法是图论，用于描述网络的一般特征，以便于比较正常网络和异常网络。第二种方法是动态因果建模，有助于分析癫痫发作传播的途径。我们得出结论，癫痫发生过程的最终结果最好理解为神经元回路的异常，而不仅仅是分子或细胞异常。网络方法有望为癫痫带来新的认识和更有针对性的治疗。
