title: Type of self-organized criticality model based on neural networks.
abstract: Based on the standard self-organizing map neural network model, we introduce a kind of coupled map lattice system to investigate self-organized criticality (SOC) in the activity of model neural populations. Our system is simulated by a more detailed integrate-and-fire mechanism and a kind of local perturbation driving rule; it can display SOC behavior in a certain range of system parameters, even with period boundary condition. More importantly, when the influence of synaptic plasticity is adequately considered, we can find that our system's learning process plays a promotive role in the emergence of SOC behavior.
authors.affiliation: Department of Physics, Nankai University, Tianjin 300071, People's Republic of China. xiaoweizhao@eyou.com
authors.forename: XiaoWei
authors.initials: X
authors.lastname: Zhao
authors.forename: TianLun
authors.initials: T
authors.lastname: Chen