Skip to main content
Springer Nature Link
Log in

A Computational Model of Bistable Perception- Attention Dynamics with Long Range Correlations

  • Conference paper
KI 2007: Advances in Artificial Intelligence (KI 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4667))

Included in the following conference series:

  • 1667 Accesses

Abstract

Simulation results of bistable perception due to ambiguous visual stimuli are presented which are obtained with a nonlinear dynamics model using perception–attention–memory coupling. Percept reversals are induced by attention fatigue and noise, with an attention bias which balances the relative percept duration. The dynamics of the attention parameter exhibits qualitative agreement with the eye blink rate variation [4]. Coupling of an attention bias to the perception state introduces memory effects leading to significant long range correlations of perceptual duration times as quantified by the Hurst parameter (H > 0.5). This prediction is in agreement with recent experimental results [1]. Deviations of the reversal time statistics from the Γ-distribution increase with decreasing memory time constant and attention noise. Mean perceptual duration times of 2 – 5 s are predicted in agreement with experimental results [7] if a feedback delay of ca. 40 ms is assumed which is typical for cortical reentrant loops.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Gao, J.B., Merk, I., Tung, W.W., Billok, V., White, K.D., Harris, J.G., Roychowdhury, V.P.: Inertia and memory in visual perception. Cogn. Process 7, 105–112 (2006)

    Article  Google Scholar 

  2. Mandelbrot, B.B.: The fractal Geometry of Nature. German translation: Birkhäuser, pp. 265–270 (1991)

    Google Scholar 

  3. Fürstenau, N.: Modelling and Simulation of spontaneous perception switching with ambiguous visual stimuli in augmented vision systems. In: André, E., Dybkjær, L., Minker, W., Neumann, H., Weber, M. (eds.) PIT 2006. LNCS (LNAI), vol. 4021, pp. 20–31. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  4. Ito, J., Nikolaev, A.R., Luman, M., Aukes, M.F., Nakatani, C., van Leeuwen, C.: Perceptual switching, eye movements, and the bus paradox. Perception 32, 681–698 (2003)

    Article  Google Scholar 

  5. Blake, R., Logothetis, N.K.: Visual competition. Nature Reviews / Neuroscience 3, 1–11 (2002)

    Google Scholar 

  6. Orbach, J., Ehrlich, D., Heath, H.A.: Reversibility of the Necker Cube: An examination of the concept of satiation of orientation. Perceptual and Motor Skills 17, 439–458 (1963)

    Google Scholar 

  7. Borsellino, A., de Marco, A., Allazetta, A., Rinesi, S., Bartolini, B.: Reversal time distribution in the perception of visual ambiguous stimuli. Kybernetik 10, 139–144 (1972)

    Article  Google Scholar 

  8. Hupe, J.-M., Rubin, N.: The dynamics of bistable alternation in ambiguous motion displays: a fresh look at plaids. Vision Research 43, 531–548 (2003)

    Article  Google Scholar 

  9. Koch, C.: The Quest for Consciousness – A Neurobiological Approach, German Translation, Elsevier, München (2004)

    Google Scholar 

  10. Engel, A.K., Fries, P., Singer, W.: Dynamic Predictions: Oscillations and Synchrony in Top-Down Processing. Nature Reviews Neuroscience 2, 704–718 (2001)

    Article  Google Scholar 

  11. Engel, A.K., Fries, P., König, P., Brecht, M., Singer, W.: Temporal binding, binocular rivalry, and consciousness. Consciousness and Cognition 8, 128–151 (1999)

    Article  Google Scholar 

  12. Srinavasan, R., Russel, D.S., Edelman, G.M., Tononi, G.: Increased synchronization of magnetic responses during conscious perception. J. Neuroscience 19, 5435–5448 (1999)

    Google Scholar 

  13. Edelman, G.: Wider than the Sky. Penguin Books, pp. 87–96 (2004)

    Google Scholar 

  14. Kettani, H., Gubner, J.A.: A Novel Approach to the Estimation of the Long-Range Dependence Parameter. IEEE Trans. Circuits and Systems-II: Express Briefs 53, 463–467 (2006)

    Article  Google Scholar 

  15. De Marco, A., Penengo, P., Trabucco, A., Borsellino, A., Carlini, F., Riani, M., Tuccio, M.T.: Stochastic Models and Fluctuations in Reversal Time of Ambiguous Figures. Perception 6, 645–656 (1977)

    Article  Google Scholar 

  16. Merk, I.L.K., Schnakenberg, J.: A stochastic model of multistable perception. Biol. Cybern. 86, 111–116 (2002)

    Article  MATH  Google Scholar 

  17. Poston, T., Stewart, I.: Nonlinear Modeling of Multistable Perception. Behavioral Science 23, 318–334 (1978)

    Article  MathSciNet  Google Scholar 

  18. Ditzinger, T., Haken, H.: A Synergetic Model of Multistability in Perception. In: Kruse, P., Stadler, M. (eds.) Ambiguity in Mind and Nature, pp. 255–273. Springer, Berlin (1995)

    Google Scholar 

  19. Levelt, W.J.M.: Note on the distribution of dominance times in binocular rivalry. Br. J. Psychol. 58, 143–145 (1967)

    Google Scholar 

  20. Lamme, V.A.F.: Why visual attention and awareness are different. Trends in cognitive Sciences 7, 12–18 (2003)

    Article  Google Scholar 

  21. Tononi, G., Edelman, G.M.: Consciousness and Complexity. Science 282, 1846–1851 (1998)

    Article  Google Scholar 

  22. Schuster, H.G., Wagner, P.A.: A Model for Neural Oscillations in the Visual Cortex: 1. Mean field theory and the derivation of the phase equations. Biol. Cybern. 64, 77–82 (1990)

    MATH  Google Scholar 

  23. Kelso, J.A.S., Case, P., Holroyd, T., Horvath, E., Raczaszek, J., Tuller, B., Ding, M.: Multistability and metastability in perceptual and brain dynamics. In: Kruse, P., Stadler, M. (eds.) Ambiguity in Mind and Nature, pp. 255–273. Springer, Berlin (1995)

    Google Scholar 

  24. Nakatani, H., van Leeuwen, C.: Transient synchrony of distant brain areas and perceptual switching in ambiguous figures. Biol. Cybern. 94, 445–457 (2006)

    Article  MATH  Google Scholar 

  25. Itti, L., Koch, C.: Computational Modelling of Visual Attention. Nature Reviews Neuroscience 2, 194–203 (2001)

    Article  Google Scholar 

  26. Robinson, D. (ed.): Neurobiology. Springer, Berlin (1998)

    Google Scholar 

  27. Fürstenau, N.: A chaotic attractor model of cognitive multistability. In: Proceedings IEEE 2004 Int. Conf. on Systems, Man and Cybernetics, IEEE cat. no. 04CH37583C, pp. 853–859 (2004)

    Google Scholar 

  28. Hillyard, S.A., Vogel, E.K., Luck, S.J.: Sensory gain control (amplification) as a mechanism of selective attention: electrophysiological and neuroimaging evidence. In: Humphreys, G.W., Duncan, J., Treisman, A. (eds.) Attention, Space, and Action, pp. 31–53. Oxford University Press (1999)

    Google Scholar 

  29. Nakatani, H., van Leeuwen, C.: Individual Differences in Perceptual Switching rates: the role of occipital alpha and frontal theta band activity. Biol. Cybern. 93, 343–354 (2005)

    Article  MATH  Google Scholar 

  30. Watts, C., Fürstenau, N.: Multistable fiber-optic Michelson Interferometer exhibiting 95 stable states. IEEE J. Quantum Electron 25, 1–5 (1989)

    Article  Google Scholar 

  31. Zhou, Y.H., Gao, J.B., White, K.D., Merk, I., Yao, K.: Perceptual dominance time distributions in multistable visual perception. Biol. Cybern. 90, 256–263 (2004)

    Article  MATH  Google Scholar 

  32. Pitts, M.A., Nerger, J.L., Davis, T.J.R.: Electrophysiological correlates of perceptual reversals for three different types of multistable images. J. of Vision 7, 1–14 (2007)

    Article  Google Scholar 

  33. Fürstenau, N.: Nonlinear dynamics model of cognitive multistability and binocular rivalry. In: Proceedings IEEE 2003 Int. Conf. on Systems, Man and Cybernetics, IEEE cat. no. 03CH37483C, pp. 1081-1088 (2003)

    Google Scholar 

  34. Lutzenberger, W., Preissl, H., Pulvermüller, F.: Fractal dimension of electroencephalographic time series and underlying brain processes. Biol. Cybern. 73, 477–482 (1995)

    Article  MATH  Google Scholar 

  35. Dafilis, M.P., Liley, D.T.J., Cadusch, P.J.: Robust chaos in a model of the electroencephalogram: Implications for brain dynamics. Chaos 11, 474–478 (2001)

    Article  MATH  Google Scholar 

  36. Burke, D.P., de Paor, A.M.: A stochastic limit cycle oscillator model of the EEG. Biol. Cybern. 91, 221–230 (2004)

    Article  MATH  Google Scholar 

  37. Richards, W., Wilson, H.R., Sommer, M.A.: Chaos in percepts. Biol. Cybern. 70, 345–349 (1994)

    Article  Google Scholar 

  38. Deco, G., Marti, D.: Deterministic Analysis of Stochastic Bifurcations in Multi-Stable Neurodynamical Systems. Biol. Cybern. 96, 487–496 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  39. Wilson, H.R.: Spikes, Decisions, and Actions. Oxford University Press, Oxford (1999)

    MATH  Google Scholar 

  40. von der Malsburg, C.: The Coherence Definition of Consciousness. In: Ho, M., Miyashita, Y., Rolls, E.T. (eds.) Cognition, Computation, and Consciousnesss, pp. 193–204. Oxford University Press, Oxford (1997)

    Google Scholar 

  41. Meng, M., Tong, F.: Can attention selectively bias bistable perception? Differences between binocular rivalry and ambiguous figures. J. of Vision 4, 539–551 (2004)

    Article  Google Scholar 

  42. Hamker, F.H.: A dynamic model of how feature cues guide spatial attention. Vision research 44, 501–521 (2004)

    Article  Google Scholar 

  43. Lehky, S.R.: Binocular rivalry is not chaotic. Proc. R. Soc. Lond. B 259, 71–76 (1995)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. German Aerospace Center, Institute of Flight Guidance, Lilienthalplatz 7, D-38108 Braunschweig, Germany

    Norbert Fürstenau

Authors
  1. Norbert Fürstenau
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Joachim Hertzberg Michael Beetz Roman Englert

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Fürstenau, N. (2007). A Computational Model of Bistable Perception- Attention Dynamics with Long Range Correlations. In: Hertzberg, J., Beetz, M., Englert, R. (eds) KI 2007: Advances in Artificial Intelligence. KI 2007. Lecture Notes in Computer Science(), vol 4667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74565-5_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74565-5_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74564-8

  • Online ISBN: 978-3-540-74565-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics