【作者】 王直杰； 吴志龙； 段飞龙；

【Author】 Zhijie Wang, Zhilong Wu, Feilong Duan College of Information Science and Technology, Shanghai 201620

【机构】 东华大学信息科学与技术学院；

【摘要】 大量的研究表明抑制性神经网络有利于产生鲁棒的高频段同步振荡如Gamma振荡。虽然在某些条件下,兴奋性的神经网络也能产生Gamma同步振荡,但其振荡的鲁棒性还需进一步的研究证实。本文发现兴奋性神经网络在某些参数条件下能够产生具有强鲁棒性的Gamma同步振荡。这个参数条件是比较弱的外部输入激励,比较强的兴奋性突触连接,以及不太短的突触延时。本文采用突触连接影响同步振荡的三个途径的思想解释了兴奋性神经网络形成鲁棒同步振荡的原因。更多还原

【Abstract】 Inhibitory neural networks are widely believed to confer advantages to the genesis of robust synchronized oscillation of high frequency such as Gamma oscillation. The Gamma oscillation can also be generated in excitatory neural networks under some certain conditions, but the robustness of the oscillation has not been studied sufficiently. It was found in this paper that the robust Gamma oscillation can be generated in excitatory networks under some certain conditions. These conditions include weak external drives, strong excitatory synapses, and not too short synaptic delay. The genesis of the robust synchronized oscillation in the excitatory was explained by the idea of three synaptic components contributing to the robust synchronization.更多还原