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Order symmetry breaking and broad distribution of events in spiking neural networks with continuous membrane potential

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  • Stucchi, Marco
  • Pittorino, Fabrizio
  • Volo, Matteo di
  • Vezzani, Alessandro
  • Burioni, Raffaella

Abstract

We introduce an exactly integrable version of the well-known leaky integrate-and-fire (LIF) model, with continuous membrane potential at the spiking event, the c-LIF. We investigate the dynamical regimes of a fully connected network of excitatory c-LIF neurons in the presence of short-term synaptic plasticity. By varying the coupling strength among neurons, we show that a complex chaotic dynamics arises, characterized by scale free avalanches. The origin of this phenomenon in the c-LIF can be related to the order symmetry breaking in neurons spike-times, which corresponds to the onset of a broad activity distribution. Our analysis uncovers a general mechanism through which networks of simple neurons can be attracted to a complex basin in the phase space.

Suggested Citation

  • Stucchi, Marco & Pittorino, Fabrizio & Volo, Matteo di & Vezzani, Alessandro & Burioni, Raffaella, 2021. "Order symmetry breaking and broad distribution of events in spiking neural networks with continuous membrane potential," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    • Handle: RePEc:eee:chsofr:v:147:y:2021:i:c:s0960077921003003
    DOI: 10.1016/j.chaos.2021.110946
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    Cited by:

    1. Guo, Lei & Guo, Minxin & Wu, Youxi & Xu, Guizhi, 2023. "Specific neural coding of fMRI spiking neural network based on time coding," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    2. Guo, Lei & Liu, Chengjun & Wu, Youxi & Xu, Guizhi, 2023. "fMRI-based spiking neural network verified by anti-damage capabilities under random attacks," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).

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