6 February 2008 Bifurcation and chaos in the spontaneously firing spike train of cultured neuronal network
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Abstract
Both neuroscience and nonlinear science have focused attention on the dynamics of the neural network. However, litter is known concerning the electrical activity of the cultured neuronal network because of the high complexity and moment change. Instead of traditional methods, we use chaotic time series analysis and temporal coding to analyze the spontaneous firing spike train recorded from hippocampal neuronal network cultured on multi-electrode array. When analyzing interspike interval series of different firing patterns, we found when single spike and burst alternate, the largest Lyapunov exponent of interspike interval (ISI) series is positive. It suggests that chaos should exist. Furthermore, a nonlinear phenomenon of bifurcation is found in the ISI vs. number histogram. It determined that this complex firing pattern of neuron and the irregular ISI series were resulted from deterministic factors and chaos should exist in cultured term.These results suggest that chaotic time series analysis and temporal coding provide us effective methods to investigate the role played by deterministic and stochastic component in neuron information coding, but further research should be carried out because of the high complexity and remarkable noise of the electric activity.
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Wenjuan Chen, Wenjuan Chen, Xiangning Li, Xiangning Li, Geng Zhu, Geng Zhu, Wei Zhou, Wei Zhou, Shaoqun Zeng, Shaoqun Zeng, Qingming Luo, Qingming Luo, } "Bifurcation and chaos in the spontaneously firing spike train of cultured neuronal network", Proc. SPIE 6855, Complex Dynamics and Fluctuations in Biomedical Photonics V, 68550E (6 February 2008); doi: 10.1117/12.763403; https://doi.org/10.1117/12.763403
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