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The use of maps in the analysis of networks of coupled neuronal oscillators.

机译:映射在耦合神经元振荡器网络分析中的使用。

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摘要

In this thesis we study aspects of periodic activity in model mutually-coupled oscillators inspired by the nervous system. We define and use maps describing the timing of activity on successive cycles. The central theme here is to examine emergent behavior in networks through the properties of the individual oscillators.;In the first chapter, we describe Phase Response Curves (PRCs), which map the changes in the period of an oscillator to perturbations at different phases along the cycle. We consider various networks of oscillators, pulse-coupled through their PRCs: rings, chains, arrays, and global coupling. We study conditions under which stable patterns, such as synchrony and waves, may be found.;In the second and third chapters, we model beta (12--30 Hz) and gamma (30--80 Hz) rhythms in the nervous system in reduced networks of excitatory and inhibitory neurons. We look at the intriguing results of experiments that show increases in beta band activity in human MEGs upon taking the sedative Diapam. We show that the model network is able to mimic the experimental data. The model then clarifies the inhibitory action of the drug in tissue.;We look at another experiment that finds disruption of long-range synchrony of gamma oscillations in transgenic mice with altered excitatory kinetics. We study this behavior in a reduced network that encodes for conduction delays across spatially distal sites. The model provides an explanation of this phenomenon in terms of the properties of the cells involved in generating the rhythm.;In our analyses, we use maps to study stability of the patterns of activity.
机译:在本文中,我们研究了受神经系统启发的模型互耦振荡器中周期性活动的各个方面。我们定义和使用描述连续周期活动时间的地图。这里的中心主题是通过单个振荡器的属性来检查网络中的突发行为。在第一章中,我们描述了相位响应曲线(PRC),该曲线将振荡器的周期变化映射到沿不同相位的扰动周期。我们考虑了各种振荡器网络,它们通过其PRC进行脉冲耦合:环,链,阵列和全局耦合。我们研究了可以找到稳定模式(例如同步和波动)的条件;在第二和第三章中,我们对神经系统中的β(12--30 Hz)和γ(30--80 Hz)节律进行建模在减少的兴奋性和抑制性神经元网络中。我们看了一些有趣的实验结果,这些结果显示服用镇静性Diapam后人MEG中的β带活性增加。我们证明了模型网络能够模仿实验数据。然后,该模型阐明了该药物在组织中的抑制作用。我们研究了另一个实验,该实验发现了兴奋性动力学改变的转基因小鼠中伽马振荡的长期同步破坏。我们在简化的网络中研究此行为,该网络编码跨空间远端站点的传导延迟。该模型根据参与产生节律的细胞的性质对这种现象进行了解释。在我们的分析中,我们使用地图来研究活动模式的稳定性。

著录项

  • 作者

    Goel, Pranay.;

  • 作者单位

    University of Pittsburgh.;

  • 授予单位 University of Pittsburgh.;
  • 学科 Biophysics General.;Physics General.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 118 p.
  • 总页数 118
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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