Protachevicz Paulo R, Borges Fernando S, Lameu Ewandson L, Ji Peng, Iarosz Kelly C, Kihara Alexandre H, Caldas Ibere L, Szezech Jose D, Baptista Murilo S, Macau Elbert E N, Antonopoulos Chris G, Batista Antonio M, Kurths Jürgen
Graduate in Science Program-Physics, State University of Ponta Grossa, Ponta Grossa, Brazil.
Center for Mathematics, Computation, and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil.
Front Comput Neurosci. 2019 Apr 5;13:19. doi: 10.3389/fncom.2019.00019. eCollection 2019.
Excessively high, neural synchronization has been associated with epileptic seizures, one of the most common brain diseases worldwide. A better understanding of neural synchronization mechanisms can thus help control or even treat epilepsy. In this paper, we study neural synchronization in a random network where nodes are neurons with excitatory and inhibitory synapses, and neural activity for each node is provided by the adaptive exponential integrate-and-fire model. In this framework, we verify that the decrease in the influence of inhibition can generate synchronization originating from a pattern of desynchronized spikes. The transition from desynchronous spikes to synchronous bursts of activity, induced by varying the synaptic coupling, emerges in a hysteresis loop due to bistability where abnormal (excessively high synchronous) regimes exist. We verify that, for parameters in the bistability regime, a square current pulse can trigger excessively high (abnormal) synchronization, a process that can reproduce features of epileptic seizures. Then, we show that it is possible to suppress such abnormal synchronization by applying a small-amplitude external current on > 10% of the neurons in the network. Our results demonstrate that external electrical stimulation not only can trigger synchronous behavior, but more importantly, it can be used as a means to reduce abnormal synchronization and thus, control or treat effectively epileptic seizures.
过高的神经同步与癫痫发作有关，癫痫是全球最常见的脑部疾病之一。因此，更好地理解神经同步机制有助于控制甚至治疗癫痫。在本文中，我们研究了一个随机网络中的神经同步，其中节点是具有兴奋性和抑制性突触的神经元，每个节点的神经活动由自适应指数积分发放模型提供。在此框架下，我们验证了抑制作用影响的降低会产生源自去同步尖峰模式的同步。通过改变突触耦合诱导的从去同步尖峰到同步活动爆发的转变，由于存在双稳态（异常（过高同步）状态）而出现在一个滞后环中。我们验证了，对于双稳态区域中的参数，一个方波电流脉冲可以触发过高（异常）同步，这一过程可以重现癫痫发作的特征。然后，我们表明通过在网络中超过10%的神经元上施加小幅度外部电流，可以抑制这种异常同步。我们的结果表明，外部电刺激不仅可以触发同步行为，更重要的是，它可以作为一种减少异常同步的手段，从而有效控制或治疗癫痫发作。
