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Effect of temperature on synchronization of scale-free neuronal network

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Abstract

The ambient temperature and the time delay of signal transmission are very important influences on the synchronization behavior of neuronal networks. In this paper, a neuronal network with the power-law degree distribution is constructed using a Hodgkin–Huxley model containing a temperature modulation factor and noise, and neurons at each node of the scale-free network are interconnected by electrical and chemical synapses, respectively. In scale-free networks with different ambient temperatures, the absence of time delay causes the synchronization of networks connected by both synaptic types to increase with coupling strength at lower temperatures, while the opposite is shown for networks connected by chemical synapses at higher temperatures. Networks connected by both synaptic types show multiple synchronization transitions when there is the time delay. Surprisingly, there is a temperature threshold for scale-free networks connected by chemical synapses, beyond which synchronization becomes very poor. By introducing the coefficient of variation and the mean inter-spikes intervals, it is found that the emergence of temperature thresholds for networks connected by chemical synapses is caused by a further increase in the difference in firing frequency of neurons due to increasing temperature. Finally, the generality of the results and mechanisms studied in scale-free networks is verified by investigating the effects of different network scales on synchronization.

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Funding

This work is supported by National Natural Science Foundation of China under Grant 12175080, and also supported by the Fundamental Research Funds for the Central Universities under Grants CCNU22JC009 and CCNU22QN004.

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  1. Department of Physics, Central China Normal University, Wuhan, 430079, China

    Yong Wu, Qianming Ding, Tianyu Li, Dong Yu & Ya Jia

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  1. Yong Wu
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Correspondence to Ya Jia.

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Wu, Y., Ding, Q., Li, T. et al. Effect of temperature on synchronization of scale-free neuronal network. Nonlinear Dyn 111, 2693–2710 (2023). https://doi.org/10.1007/s11071-022-07967-6

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