title: [Stochastic nonlinear evolutional model of the large-scaled neuronal population and dynamic neural coding subject to stimulation].
abstract: In this paper, we investigate how the population of neuronal oscillators deals with information, and analyze the dynamic evolution of neural coding when the outer stimulation acts on it on the base of our former work. By numerically computing for the model, we obtain the figure of average number density, which is used to describe the action potential of the neurons within population in three-dimensional space, namely the dynamic evolution of neural coding. The result of numerical analysis indicates that the model in this paper can be used to describe the evolutional process of abundant mutual interactional neurons acted by outer stimulation. The numerical result also proves that only the suitable stimulation can change the coupling structure of neurons. And the evolution model given in this paper incarnates the neural plasticity.
authors.affiliation: Institute for Brain Information Processing and Cognitive Neurodynamics, School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.
authors.forename: Rubin
authors.initials: R
authors.lastname: Wang
authors.forename: Wei
authors.initials: W
authors.lastname: Yu
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D001921:Brain / Q000502:physiology*; D016014:Linear Models; D008959:Models, Neurological; D009434:Neural Pathways / Q000502:physiology; D009473:Neuronal Plasticity / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D013269:Stochastic Processes; D009435:Synaptic Transmission / Q000502:physiology