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• W2020118400 abstract "Abstract 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, occur. The spiking activity becomes stronger in intensity and higher in frequency as the randomness is further increased. These phenomena imply that random long-range connections can induce and enhance the activity of neural networks. Furthermore, the possible mechanism behind the action of random long-range connections is also addressed. Our results may provide a useful hint for understanding the properties of collective dynamics in coupled real neurons." @default.
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• W2020118400 date "2008-03-01" @default.
• W2020118400 modified "2023-10-16" @default.
• W2020118400 title "Random long-range connections induce activity of complex Hindmarsh–Rose neural networks" @default.
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• W2020118400 doi "https://doi.org/10.1016/j.physa.2007.11.042" @default.
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