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The Resonance Frequency Shift, Pattern Formation, and Dynamical Network Reorganization via Sub-Threshold Input

机译:通过亚阈值输入的共振频率偏移,模式形成和动态网络重组

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摘要

We describe a novel mechanism that mediates the rapid and selective pattern formation of neuronal network activity in response to changing correlations of sub-threshold level input. The mechanism is based on the classical resonance and experimentally observed phenomena that the resonance frequency of a neuron shifts as a function of membrane depolarization. As the neurons receive varying sub-threshold input, their natural frequency is shifted in and out of its resonance range. In response, the neuron fires a sequence of action potentials, corresponding to the specific values of signal currents, in a highly organized manner. We show that this mechanism provides for the selective activation and phase locking of the cells in the network, underlying input-correlated spatio-temporal pattern formation, and could be the basis for reliable spike-timing dependent plasticity. We compare the selectivity and efficiency of this pattern formation to a supra-threshold network activation and a non-resonating network/neuron model to demonstrate that the resonance mechanism is the most effective. Finally we show that this process might be the basis of the phase precession phenomenon observed during firing of hippocampal place cells, and that it may underlie the active switching of neuronal networks to locking at various frequencies.
机译:我们描述了一种新颖的机制,可调节亚阈值水平输入的变化相关性,从而调节神经网络活动的快速和选择性模式的形成。该机制基于经典共振和实验观察到的现象,即神经元的共振频率随膜去极化而变化。当神经元收到变化的亚阈值输入时,它们的固有频率会移入和移出其共振范围。作为响应,神经元以高度组织的方式激发一系列动作电位,该动作电位对应于信号电流的特定值。我们表明,该机制提供了网络中细胞的选择性激活和锁相,潜在的与输入相关的时空模式的形成,并且可能是依赖于尖峰时序的可塑性的基础。我们将这种模式形成的选择性和效率与超阈值网络激活和非共振网络/神经元模型进行比较,以证明共振机制是最有效的。最后,我们证明了该过程可能是海马位置细胞放电过程中观察到的相位进动现象的基础,并且它可能是神经网络主动切换为锁定各种频率的基础。

著录项

  • 作者

    Lau, Troy; Zochowski, Michal;

  • 作者单位
  • 年度 2011
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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