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Order symmetry breaking and broad distribution of events in spiking neural networks with continuous membrane potential
Chaos, Solitons & Fractals ( IF 7.8 ) Pub Date : 2021-05-02 , DOI: 10.1016/j.chaos.2021.110946
Marco Stucchi , Fabrizio Pittorino , Matteo di Volo , Alessandro Vezzani , Raffaella Burioni

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.



中文翻译:

具有连续膜电位的尖峰神经网络中的顺序对称性破坏和事件的广泛分布

我们介绍了众所周知的泄漏集成和发射(LIF)模型的完全可集成版本,在峰值事件c-LIF上具有连续的膜电位。我们调查短期内突触可塑性存在的兴奋性c-LIF神经元的完全连接的网络的动力学机制。通过改变神经元之间的耦合强度,我们显示出一个复杂的混沌动力学出现,其特征是无鳞雪崩。这种现象在c-LIF中的起源可能与神经元尖峰时间的顺序对称性破坏有关,这与广泛的活动分布开始有关。我们的分析揭示了一种简单的神经元网络可以被吸引到相空间中复杂盆地的一般机制。

更新日期:2021-05-02
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