A dynamic neural network model of self-organized criticality in neuronal avalanches

Self-organized criticality is one of the key mechanisms to explain the emergence of complexity in natural systems, which has been demonstrated in many physical systems. Recently, physiological experiments reported the convincing evidence that the spontaneous activity in brain cortex exhibited neuronal avalanches, which provided that self-organized criticality also play a crucial role in brain. The scientific problem for theoretical works is to analyze the dynamic mechanism of self-organized criticality in the neurosystem. A neural network model, based on the dynamic neurons and synaptic transmissions properties, was developed in this paper. Through the discussion of the balance between the excitatory and inhibitory neurons, the dynamic synaptic transmission process, synaptic plasticity and the temporal connecting structure due to the synaptic delay, we discussed the probable dynamic mechanisms in neuronal avalanches and the difference of the mechanisms of self-organized criticality between the neurosystem and other systems.