The University of Queensland, Centre for Advanced Imaging, St Lucia, QLD, 4072, Australia.
Sci Rep. 2019 Jan 31;9(1):1097. doi: 10.1038/s41598-018-37646-9.
Epilepsy is a neurological disorder characterised by spontaneous recurrent seizures. The mechanisms by which multiple molecular and cellular changes lead to seizures is not well understood. Here, we study cortical seizure generation by simulating the activity of neuron groups in a network using the laminar cortex model. We identified a clear boundary between low-amplitude, asynchronous activity and high-amplitude, rhythmic activity, around which small changes in excitatory synaptic gain led to strong oscillatory activity. Neuron groups only responded significantly to stimulation around the boundary. The consequences of biophysical changes induced by epilepsy-related SCN1A mutations were also examined. Marked reduction in neuronal inhibition, as caused by mutations underlying Dravet syndrome, invariably led to strong neuronal firing, whereas small reductions in inhibition could cause significant changes when the network was poised close to the boundary. The study highlights the critical role of network dynamics in seizure genesis.
癫痫是一种以自发性反复发作性癫痫发作为特征的神经障碍。导致癫痫发作的多种分子和细胞变化的机制尚不清楚。在这里,我们通过使用层状皮质模型模拟神经元群体在网络中的活动来研究皮质癫痫发作的产生。我们在低幅度、异步活动和高幅度、节律性活动之间确定了一个明显的边界,在这个边界周围,兴奋性突触增益的微小变化会导致强烈的振荡活动。神经元群体仅在边界附近对刺激有明显反应。我们还检查了与癫痫相关 SCN1A 突变引起的生物物理变化的后果。由 Dravet 综合征相关突变引起的神经元抑制明显减少,总是导致强烈的神经元放电,而当网络接近边界时,抑制的微小减少也会导致显著的变化。该研究强调了网络动力学在癫痫发作中的关键作用。