Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks.
Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks.
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DOI：
10.1155/2016/7186092
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发表时间：
2016
影响因子：
--
通讯作者：
Sawai H
中科院分区：
文献类型：
--
作者：
Tamura S;Nishitani Y;Hosokawa C;Miyoshi T;Sawai H
已经表明，在多电极上培养的神经元网络中，检测到伪随机样序列（代码），并且它们以一定的空间衰减常数流动。每个培养的神经元网络的特征在于一个特定的频谱曲线。也就是说，我们可以将频谱曲线视为其相关神经元网络的“签名”，其取决于神经元和网络配置的特性，包括权重分布。在本研究中，我们使用了一个集成和消防模型的神经元的内在和瞬时波动的特性进行模拟的代码频谱从多电极上的二维网状神经网络。我们发现，它是可能的，以估计神经元的特性，如分布的神经元的数量在每个电极和他们的不应期。虽然这个过程是一个逆问题，理论上的解决方案是没有足够的保证，参数似乎是一致的神经元。也就是说，所提出的神经网络模型可以充分反映培养的神经网络的行为。此外，这样的前景进行了讨论，代码分析将提供一个神经网络，也将创建一个自然智能的基础内的通信基础。
It has been shown that, in cultured neuronal networks on a multielectrode, pseudorandom-like sequences (codes) are detected, and they flow with some spatial decay constant. Each cultured neuronal network is characterized by a specific spectrum curve. That is, we may consider the spectrum curve as a “signature” of its associated neuronal network that is dependent on the characteristics of neurons and network configuration, including the weight distribution. In the present study, we used an integrate-and-fire model of neurons with intrinsic and instantaneous fluctuations of characteristics for performing a simulation of a code spectrum from multielectrodes on a 2D mesh neural network. We showed that it is possible to estimate the characteristics of neurons such as the distribution of number of neurons around each electrode and their refractory periods. Although this process is a reverse problem and theoretically the solutions are not sufficiently guaranteed, the parameters seem to be consistent with those of neurons. That is, the proposed neural network model may adequately reflect the behavior of a cultured neuronal network. Furthermore, such prospect is discussed that code analysis will provide a base of communication within a neural network that will also create a base of natural intelligence.