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Comput Intell Neurosci ; 2016: 8939218, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27725829

RESUMO

Let a neuronal population be composed of an excitatory group interconnected to an inhibitory group. In the Wilson-Cowan model, the activity of each group of neurons is described by a first-order nonlinear differential equation. The source of the nonlinearity is the interaction between these two groups, which is represented by a sigmoidal function. Such a nonlinearity makes difficult theoretical works. Here, we analytically investigate the dynamics of a pair of coupled populations described by the Wilson-Cowan model by using a linear approximation. The analytical results are compared to numerical simulations, which show that the trajectories of this fourth-order dynamical system can converge to an equilibrium point, a limit cycle, a two-dimensional torus, or a chaotic attractor. The relevance of this study is discussed from a biological perspective.


Assuntos
Modelos Lineares , Modelos Neurológicos , Rede Nervosa/fisiologia , Neurônios/fisiologia , Animais , Simulação por Computador , Humanos
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