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Neural Chaos Scheme of Perceptual Conflicts

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2003)

Abstract

Multistable perception is perception in which two (or more) interpretations of the same ambiguous image alternate while an obserber looks at them. Perception undergoes involuntary and random-like change. The question arises whether the apparent randomness of alternation is real (that is, due to a stochastic process) or whether any underlying deterministic structure to it exists. Upon this motivation, we have examined the spatially coherent temporal behaviors of multistable perception model based on the chaotic neural network from the viewpoint of bottom-up high dimensional approach. In this paper, we focus on dynamic processes in a simple (minimal) system which consists of three neurons, aiming at further understanding of the deterministic mechanism.

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References

  1. Attneave, F.: Multistability in perception. Scientific American 225, 62–71 (1971)

    Article  Google Scholar 

  2. Kruse, P., Stadler, M. (eds.): Ambiguity in Mind and Nature. Springer, Heidelberg (1995)

    MATH  Google Scholar 

  3. Borsellino, A., Marco, A.D., Allazatta, A., Rinsei, S., Bartolini, B.: Reversal time distribution in the perception of visual ambiguous stimuli. Kybernetik 10, 139–144 (1972)

    Article  Google Scholar 

  4. Borsellino, A., Carlini, F., Riani, M., Tuccio, M.T., Marco, A.D., Penengo, P., Trabucco, A.: Effects of visual angle on perspective reversal for ambiguous patterns. Perception 11, 263–273 (1982)

    Article  Google Scholar 

  5. Köhler, W.: Dynamics in psychology. Liveright, New York (1940)

    Google Scholar 

  6. Ditzinger, T., Haken, H.: Oscillations in the perception of ambiguous patterns: A model based on synergetics. Biological Cybernetics 61, 279–287 (1989)

    Article  MathSciNet  Google Scholar 

  7. Ditzinger, T., Haken, H.: The impact of fluctuations on the recognition of ambiguous patterns. Biological Cybernetics 63, 453–456 (1990)

    Article  Google Scholar 

  8. Arbib, M.A.: The Handbook of Brain Theory and Neural Networks. MIT Press, Cambridge (1995)

    Google Scholar 

  9. Nishimura, H., Nagao, N., Matsui, N.: A perception model of ambiguous figures based on the neural chaos. In: Kasabov, N., et al. (eds.) Progress in Connectionist- Based Information Systems, vol. 1, pp. 89–92. Springer, Heidelberg (1997)

    Google Scholar 

  10. Nagao, N., Nishimura, H., Matsui, N.: A neural chaos model of multistable perception. Neural Processing Letters 12, 267–276 (2000)

    Article  MATH  Google Scholar 

  11. Aihara, K., Takabe, T., Toyoda, M.: Chaotic neural networks. Phys. Lett. A 144, 333–340 (1990)

    Article  MathSciNet  Google Scholar 

  12. Nishimura, H., Katada, N., Fujita, Y.: Dynamic learning and retrieving scheme based on chaotic neuron model. In: Nakamura, R., et al. (eds.) Complexity and Diversity, pp. 64–66. Springer, Heidelberg (1997)

    Chapter  Google Scholar 

  13. Mumford, D.: On the computational architecture of the neocortex ii. The role of cortico-cortical loops. Biol. Cybern. 66, 241–251 (1992)

    Article  Google Scholar 

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Nishimura, H., Nagao, N., Matsui, N. (2003). Neural Chaos Scheme of Perceptual Conflicts. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_25

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  • DOI: https://doi.org/10.1007/978-3-540-45224-9_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40803-1

  • Online ISBN: 978-3-540-45224-9

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