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Transition from regular to labyrinth pattern in a neuronal network with fast inhibitory synapses

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  • Feng, Peihua
  • Fan, Qiang
  • Yuan, Zhixuan
  • Wu, Ying

Abstract

Pattern selection among spiral wave or target wave and irregular patterns plays a key role in cortical information processing in mammalian neocortex. In this paper, we study transition between spiral wave and labyrinth pattern in neural network in which neurons are coupled with fast inhibitory synapse. Transition between regular patterns when neurons are connected by fast inhibitory synapse is quite different from that of network with fast excitatory synapse. It is a complex scenario of transition from regular wave to labyrinth pattern. Four types of spatiotemporal patterns are discovered in the network, namely, rectangular spiral wave, chimera state, circular spiral wave and labyrinth pattern. When the labyrinth pattern occupies the whole domain of network, firing of every neuron is periodic motion. But transition from the regular wave to labyrinth pattern is accompanied with onset of intermittency of neuron firing at the corners of network. Occurrence of intermittency of individual neuron perfectly matches the appearance of circular spiral wave, which is explained by nonlinear analysis. Indeed, dynamics of single neuron electrical activities can also be considered as an index of pattern transition.

Suggested Citation

  • Feng, Peihua & Fan, Qiang & Yuan, Zhixuan & Wu, Ying, 2021. "Transition from regular to labyrinth pattern in a neuronal network with fast inhibitory synapses," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
  • Handle: RePEc:eee:chsofr:v:146:y:2021:i:c:s0960077921001119
    DOI: 10.1016/j.chaos.2021.110758
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    References listed on IDEAS

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    1. Gu, Hua-Guang & Jia, Bing & Li, Yu-Ye & Chen, Guan-Rong, 2013. "White noise-induced spiral waves and multiple spatial coherence resonances in a neuronal network with type I excitability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1361-1374.
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    Cited by:

    1. Li, Tianyu & Wu, Yong & Yang, Lijian & Zhan, Xuan & Jia, Ya, 2022. "Spike-timing-dependent plasticity enhances chaotic resonance in small-world network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    2. Ouyang, Zhicheng & Yu, Yangyang & Liu, Zhilong & Feng, PeiHua, 2023. "Transition of spatiotemporal patterns in neuron–astrocyte networks," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).

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