Effect of correlating adjacent neurons for identifying communications: Feasibility experiment in a cultured neuronal network
Effect of correlating adjacent neurons for identifying communications: Feasibility experiment in a cultured neuronal network
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DOI：
10.3934/neuroscience.2018.1.18
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发表时间：
2017-12
影响因子：
2.7
通讯作者：
Y. Nishitani;C. Hosokawa;Y. Mizuno-Matsumoto;T. Miyoshi;S. Tamura
中科院分区：
文献类型：
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作者：
Y. Nishitani;C. Hosokawa;Y. Mizuno-Matsumoto;T. Miyoshi;S. Tamura
神经元网络具有波动的特征，不像计算机中看到的稳定特征。驱动神经元网络之间可靠通信的潜在机制以及它们执行可理解的任务的能力仍然未知。最近，为了试图解决这个问题，我们展示了受刺激的神经元通过以棘波序列的形式在时间上传播的棘波进行交流。我们将这种现象称为“尖峰波传播”。在这些先前的研究中，我们使用从大鼠海马神经元培养的神经网络，我们发现多个神经元，例如3个神经元，在培养的神经元网络中识别不同的棘波传播。具体地说，神经元网络中的可分类神经元的数量通过当前神经元和相邻神经元之间的棘波序列的关联而增加。虽然我们之前通过刺激获得了类似的发现，但在这里，我们从生理水平上报道这些观察结果。考虑到单个棘波的传播对应于单个的通信，提出了一种相邻神经元之间的相关性来提高神经元网络的通信分类质量，类似于分集天线，用于提高人工数据通信系统的通信质量。
Neuronal networks have fluctuating characteristics, unlike the stable characteristics seen in computers. The underlying mechanisms that drive reliable communication among neuronal networks and their ability to perform intelligible tasks remain unknown. Recently, in an attempt to resolve this issue, we showed that stimulated neurons communicate via spikes that propagate temporally, in the form of spike trains. We named this phenomenon “spike wave propagation”. In these previous studies, using neural networks cultured from rat hippocampal neurons, we found that multiple neurons, e.g., 3 neurons, correlate to identify various spike wave propagations in a cultured neuronal network. Specifically, the number of classifiable neurons in the neuronal network increased through correlation of spike trains between current and adjacent neurons. Although we previously obtained similar findings through stimulation, here we report these observations on a physiological level. Considering that individual spike wave propagation corresponds to individual communication, a correlation between some adjacent neurons to improve the quality of communication classification in a neuronal network, similar to a diversity antenna, which is used to improve the quality of communication in artificial data communication systems, is suggested.