物理
联轴节(管道)
生物神经网络
同步(交流)
人工神经网络
计算机科学
控制理论(社会学)
生物系统
神经科学
电信
人工智能
生物
材料科学
频道(广播)
冶金
控制(管理)
作者
Yitong Guo,Ying Xie,Jun Ma
标识
DOI:10.1016/j.physa.2023.129120
摘要
Biological neurons are clustered and functional synapses are created to propagate electric signals accompanying with formation of spatial patterns in the neural network. From physical aspect, fast synaptic connections to neurons provide an effective shortcut for energy exchange and keeping energy balance between neurons. In fact, field coupling behaves effective bridge connections to neurons and then neural activities can be controlled by spatial induction currents in the neural network. In this paper, memristive neurons are controlled by magnetic flux by inducing gradient induction current in presence of electromagnetic radiation without synaptic connections. Differed from the previous uniform radiation, spatial radiation is imposed on the neural network and the stability of spatial patterns is explored by imposing a spatiotemporal disturbance on the network. Memristive neurons developed from Hindmarsh–Rose neurons by involving memristive term and magnetic flux variable are used to build a chain network and a lattice network under field coupling rather than using synaptic coupling. Synchronization factors are calculated to discern the synchronization dependence on noise, amplitude and frequency in the spatial electromagnetic radiation. An isolated neuron can present stochastic resonance under noise and radiation with diversity. Field coupling enhances energy exchange and local energy balance, and then synchronous patterns are controlled in absence of synaptic coupling. External noise and spatial disturbance can induce certain diversity in induction current and excitability, therefore, approach of complete synchronization and development of regular patterns are blocked because of local energy balance under field coupling. These results indicate that energy injection and control of energy flow are effective to prevent the occurrence of bursting synchronization and coexistence of multiple firing modes is formed in neural network composed of memristive neurons under spatial radiation.
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