College of Information and Control Engineering, Xi'an University of Architecture and Technology, Shaanxi, Xi'an 710055, China.
State Key Laboratory for Strength and Vibration of Mechanical Structures, National Demonstration Center for Experimental Mechanics Education, School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Chaos. 2022 Nov;32(11):113121. doi: 10.1063/5.0124123.
Epilepsy is a neurological disorder with recurrent seizures, which convey complex dynamical characteristics including chaos and randomness. Until now, the underlying mechanism has not been fully elucidated, especially the bistable property beneath the epileptic random induction phenomena in certain conditions. Inspired by the recent finding that astrocyte GTPase-activating protein (G-protein)-coupled receptors could be involved in stochastic epileptic seizures, we proposed a neuron-astrocyte network model, incorporating the noise of the astrocytic second messenger, inositol triphosphate (IP3) that is modulated by G-protein-coupled receptor activation. Based on this model, we have statistically analyzed the transitions of epileptic seizures by performing repeatable simulation trials. Our simulation results show that the increase in the IP3 noise intensity induces depolarization-block epileptic seizures together with an increase in neuronal firing frequency, consistent with corresponding experiments. Meanwhile, the bistable states of the seizure dynamics were present under certain noise intensities, during which the neuronal firing pattern switches between regular sparse spiking and epileptic seizure states. This random presence of epileptic seizures is absent when the noise intensity continues to increase, accompanying with an increase in the epileptic depolarization block duration. The simulation results also shed light on the fact that calcium signals in astrocytes play significant roles in the pattern formations of the epileptic seizure. Our results provide a potential pathway for understanding the epileptic randomness in certain conditions.
癫痫是一种具有反复发作性的神经系统疾病，其传达的复杂动力学特征包括混沌和随机性。到目前为止，其潜在机制尚未完全阐明，特别是在某些条件下癫痫随机诱导现象下的双稳态特性。受星形胶质细胞鸟嘌呤核苷酸交换因子（G 蛋白）偶联受体可能参与随机癫痫发作这一最新发现的启发，我们提出了一个神经元-星形胶质细胞网络模型，其中纳入了星形胶质细胞第二信使肌醇三磷酸（IP3）的噪声，该噪声由 G 蛋白偶联受体激活调制。基于该模型，我们通过重复模拟试验对癫痫发作的转变进行了统计分析。我们的模拟结果表明，随着 IP3 噪声强度的增加，会引发去极化阻断性癫痫发作，并伴随着神经元放电频率的增加，与相应的实验结果一致。同时，在一定的噪声强度下，癫痫动力学存在双稳态状态，在此期间神经元放电模式在规则稀疏放电和癫痫发作状态之间切换。当噪声强度继续增加时，这种癫痫发作的随机性就会消失，同时癫痫去极化阻断持续时间增加。模拟结果还表明，星形胶质细胞中的钙信号在癫痫发作的模式形成中起着重要作用。我们的结果为理解某些条件下癫痫的随机性提供了一条潜在的途径。
