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Computational and Mathematical Methods in Medicine
Volume 2014, Article ID 174274, 10 pages
http://dx.doi.org/10.1155/2014/174274
Research Article

The Effect of Inhibitory Neuron on the Evolution Model of Higher-Order Coupling Neural Oscillator Population

1Institute for Cognitive Neurodynamics, East China University of Science and Technology, Shanghai 200237, China
2School of Mathematics, Hefei University of Technology, Hefei 230009, China

Received 17 September 2013; Accepted 30 October 2013; Published 2 January 2014

Academic Editor: Jinde Cao

Copyright © 2014 Yi Qi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. G. Werner, “From brain states to mental phenomena via phase space transitions and renormalization group transformation: proposal of a theory,” Cognitive Neurodynamics, vol. 6, no. 2, pp. 199–202, 2012. View at Publisher · View at Google Scholar · View at Scopus
  2. J. Feldman, “The neural binding problems,” Cognitive Neurodynamics, vol. 7, no. 1, pp. 1–12, 2013. View at Google Scholar
  3. C. M. Gray and W. Singer, “Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex,” Proceedings of the National Academy of Sciences of the United States of America, vol. 86, no. 5, pp. 1698–1702, 1989. View at Google Scholar · View at Scopus
  4. C. M. Gray and W. Singer, “Stimulus specific neuronal oscillations in the cat visual cortex: a cortical function unit,” Society for Neuroscience, vol. 404, p. 3, 1989. View at Google Scholar · View at Scopus
  5. A. T. Winfree, The Geometry of Biological Time, Springer, Berlin, Germany, 1980.
  6. P. A. Tass, Phase Resetting in Medicine and Biology, Springer, Berlin, Germany, 1999.
  7. J.-P. Pfister and P. A. Tass, “STDP in oscillatory recurrent networks: theoretical conditions for desynchronization and applications to deep-brain stimulation,” Frontiers in Neuroscience, vol. 4, article 22, 2010. View at Google Scholar
  8. P. Tass, D. Smirnov, A. Karavaev et al., “The causal relationship between subcortical local field potential oscillations and Parkinsonian resting tremor,” Journal of Neural Engineering, vol. 7, no. 1, Article ID 016009, 2010. View at Publisher · View at Google Scholar · View at Scopus
  9. X. Jiao and R. Wang, “Synchronization in neuronal population with the variable coupling strength in the presence of external stimulus,” Applied Physics Letters, vol. 88, no. 20, Article ID 203901, 2006. View at Publisher · View at Google Scholar · View at Scopus
  10. R. Wang and H. Chen, “A dynamic evolution model for the set of populations of neurons,” International Journal of Nonlinear Sciences and Numerical Simulation, vol. 4, no. 3, pp. 203–208, 2003. View at Google Scholar · View at Scopus
  11. R. Wang, Z. Zhang, and Y.-B. Duan, “Nonlinear stochastic models of neurons activities,” Neurocomputing, vol. 51, pp. 401–411, 2003. View at Publisher · View at Google Scholar · View at Scopus
  12. R. Wang, Z. Zhang, and J. Yu, “A neural model on cognitive process,” in Advances in Neural Networks—ISNN 2006, vol. 3971 of Lecture Notes in Computer Science, pp. 50–59, Springer, Berlin, Germany, 2006. View at Google Scholar
  13. Y. Liu, R. Wang, Z. Zhang, and X. Jiao, “Analysis of stability of neural network with inhibitory neurons,” Cognitive Neurodynamics, vol. 4, no. 1, pp. 61–68, 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. T. Trappenberg, “Tracking population densities using dynamic neural fields with moderately strong inhibition,” Cognitive Neurodynamics, vol. 2, no. 3, pp. 171–177, 2008. View at Publisher · View at Google Scholar · View at Scopus
  15. A. Weigenand, T. Martinetz, and J. C. Claussen, “The phase response of the cortical slow oscillation,” Cognitive Neurodynamics, vol. 6, no. 4, pp. 367–375, 2012. View at Google Scholar