首页> 美国卫生研究院文献>Computational Intelligence and Neuroscience >Rhythmic Oscillations of Excitatory Bursting Hodkin-Huxley Neuronal Network with Synaptic Learning
【2h】

Rhythmic Oscillations of Excitatory Bursting Hodkin-Huxley Neuronal Network with Synaptic Learning

机译:突触学习的霍奇金-赫克斯利神经网络的节律性振荡

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Rhythmic oscillations of neuronal network are actually kind of synchronous behaviors, which play an important role in neural systems. In this paper, the properties of excitement degree and oscillation frequency of excitatory bursting Hodkin-Huxley neuronal network which incorporates a synaptic learning rule are studied. The effects of coupling strength, synaptic learning rate, and other parameters of chemical synapses, such as synaptic delay and decay time constant, are explored, respectively. It is found that the increase of the coupling strength can weaken the extent of excitement, whereas increasing the synaptic learning rate makes the network more excited in a certain range; along with the increasing of the delay time and the decay time constant, the excitement degree increases at the beginning, then decreases, and keeps stable. It is also found that, along with the increase of the synaptic learning rate, the coupling strength, the delay time, and the decay time constant, the oscillation frequency of the network decreases monotonically.
机译:神经网络的节律振荡实际上是一种同步行为,在神经系统中起着重要的作用。本文研究了结合突触学习规则的兴奋性爆发霍奇金-赫克斯利神经元网络的兴奋度和振荡频率的性质。分别探讨了耦合强度,突触学习率和化学突触的其他参数(如突触延迟和衰减时间常数)的影响。发现耦合强度的增加可以减弱兴奋的程度,而突触学习速率的增加会使网络在一定范围内更加兴奋。随着延迟时间和衰减时间常数的增加,兴奋度在开始时先增大,然后减小,并保持稳定。还发现,随着突触学习速率,耦合强度,延迟时间和衰减时间常数的增加,网络的振荡频率单调降低。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号