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In this paper, we investigate how activity of complex neural networks depends on random long-range connections. Network elements are described by Hindmarsh–Rose (HR) neurons assumed to be inactive. It is found that for a given coupling strength, when the number of random connections (or randomness) is greater than a threshold, the spiking neurons, which are absent in the nearest-neighbor neural network,...
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