Turing instability and pattern formation of neural networks with reaction–diffusion terms

@article{Zhao2014TuringIA,
  title={Turing instability and pattern formation of neural networks with reaction–diffusion terms},
  author={Hongyong Zhao and Xuanxuan Huang and Xuebing Zhang},
  journal={Nonlinear Dynamics},
  year={2014},
  volume={76},
  pages={115-124}
}
In this paper, a model for a network of neurons with reaction–diffusion is investigated. By analyzing the linear stability of the system, Hopf bifurcation and Turing unstable conditions are obtained. Based on this, standard multiple-scale analysis is used for deriving the amplitude equations of the model for the excited modes in the Turing bifurcation. Moreover, the stability of different patterns is also determined. The obtained results enrich the dynamics of neurons’ network system. 
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