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Spike code and information flow in cultured neuronal networks and its simulation on 2D mesh network

机译:培养的神经元网络中的秒杀代码和信息流及其在2D网格网络上的仿真

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It's important to investigate natural intelligence how the signal/ information is flown in neuronal network. We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multi-electrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We then constructed code flow maps as movies of the electrode array to observe the code flow especially of “1101” and “1011.” To quantify the flow, we calculated the cross-correlations of the maximum direction of the codes with lengths less than 8. Normalized cross-correlations in the maximum direction were almost constant irrespective of code. Thus, the analysis suggested that the local codes for electrode flow maintained the code shape to some extent and conveyed information in the neural network. Then we made simulation of such code flow.
机译:重要的是调查自然情报如何在神经元网络中传递信号/信息。我们在培养的神经元网络中观察到由8×8多电极一键式电刺激产生的尖峰序列。每个电极接受来自几个神经元的尖峰。然后,我们将代码流图构造为电极阵列的影片,以观察代码流,尤其是“ 1101”和“ 1011”的代码流。为了量化流量,我们计算了长度小于8的代码最大方向的互相关。无论代码如何,在最大方向上的标准化互相关几乎都是恒定的。因此,分析表明,电极流的局部代码在某种程度上保持了代码形状,并在神经网络中传达了信息。然后,我们对这种代码流进行了仿真。

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