Biological Cybernetics

, Volume 100, Issue 6, pp 491–504 | Cite as

Visual perception of ambiguous figures: synchronization based neural models

  • Roman Borisyuk
  • David Chik
  • Yakov Kazanovich
Original Paper


We develop and study two neural network models of perceptual alternations. Both models have a star-like architecture of connections with a central element connected to a set of peripheral elements. A particular perception is simulated in terms of partial synchronization between the central element and some sub-group of peripheral elements. The first model is constructed from phase oscillators and the mechanism of perceptual alternations is based on chaotic intermittency under fixed parameter values. Similar to experimental evidence, the distribution of times between perceptual alternations is represented by the gamma distribution. The second model is built of spiking neurons of the Hodgkin–Huxley type. The mechanism of perceptual alternations is based on plasticity of inhibitory synapses which increases the inhibition from the central unit to the neural assembly representing the current percept. As a result another perception is formed. Simulations show that the second model is in good agreement with behavioural data on switching times between percepts of ambiguous figures and with experimental results on binocular rivalry of two and four percepts.


Perceptual multi-stability Synchronization Phase oscillators Hodgkin–Huxley neurons 


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  1. Adrian E (1926) The impulses produced by sensory nerve endings. Part 2: The response of a single end-organ. J Physiol 61: 151–171PubMedGoogle Scholar
  2. Beck O, Chistiakova M, Obermayer K, Volgushev M (2005) Adaptation at synaptic connections to layer 2/3 pyramidal cells in rat visual cortex. J Neurophysiol 94: 363–376PubMedCrossRefGoogle Scholar
  3. Bialek W, DeWeese M (1995) Random switching and optimal processing in the perception of ambiguous signals. Phys Rev Lett 74: 3077–3080PubMedCrossRefGoogle Scholar
  4. Blake R (1989) A neural theory of binocular rivalry. Psychol Rev 96(1): 145–167PubMedCrossRefGoogle Scholar
  5. Borisyuk RM, Hoppensteadt F (2004) A theory of epineuronal memory. Neural Netw 17: 1427–1436PubMedCrossRefGoogle Scholar
  6. Borisyuk RM, Kazanovich YB (2003) Oscillatory neural network model of attention focus formation and control. Biosystems 71: 29–38PubMedCrossRefGoogle Scholar
  7. Borisyuk RM, Kazanovich YB (2006) Oscillations and waves in the models of interactive neural populations. Biosystems 86: 53–62PubMedCrossRefGoogle Scholar
  8. Borsellino A, de Marco A, Allazetta A, Rinesi S, Bartolini B (1972) Reversal time distribution in the perception of visual ambiguous stimuli. Biol Cybern 10: 139–144Google Scholar
  9. Borisyuk GN, Borisyuk RM, Kirillov AB, Kovalenko EI, Kryukov VI (1985) A new statistical method for identifying interconnections between neuronal network elements. Biol Cybern 52(5): 301–306PubMedCrossRefGoogle Scholar
  10. Bossink CJH, Stalmeier PFM, de Weert CMM (1993) A test of Levelt’s second proposition for binocular rivalry. Vision Res 33: 1413–1419PubMedCrossRefGoogle Scholar
  11. Brager DH, Capogna M, Thompson SM (2002) Short-term synaptic plasticity, simulation of nerve terminal dynamics, and the effects of protein kinase C activation in rat hippocampus. J Physiol 541: 545–559PubMedCrossRefGoogle Scholar
  12. Choi IS, Cho JH, Jeong SG, Hong JS, Kim SJ, Kim J, Lee MG, Choi BJ, Jang IS (2008) GABAB receptor-mediated presynaptic inhibition of glycinergic transmission onto substantia gelatinosa neurons in the rat spinal cord. Pain. doi: 10.1016/j.pain.2008.01.005
  13. Damasio A (1989) The brain binds entities and events by multiregional activation from convergent zones. Neural Comput 1: 123–132CrossRefGoogle Scholar
  14. Dayan P (1998) A hierarchical model of binocular rivalry. Neural Comput 10: 1119–1135PubMedCrossRefGoogle Scholar
  15. De Marco A, Penengo P, Trabucco A (1977) Stochastic models and fluctuations in reversal time of ambiguous figures. Perception 6(6): 645–656PubMedCrossRefGoogle Scholar
  16. Einhauser W, Martin KAC, Konig P (2004) Are switches in perception of the Necker cube related to eye position?. Eur J Neurosci 20(10): 2811–2818PubMedCrossRefGoogle Scholar
  17. Engel A, Singer W (2001) Temporal binding and the neural correlates of sensory awareness. Trends Cogn Sci 5: 16–25PubMedCrossRefGoogle Scholar
  18. Fitzpatrick JS, Akopian G, Walsh JP (2001) Short term plasticity at inhibitory synapses in rat striatum and its effect on striatal output. J Neurophysiol 85: 2088–2099PubMedGoogle Scholar
  19. Fox R, Herrmann J (1967) Stochastic properties of binocular rivalry alternations. Percept Psychophys 2: 432–436Google Scholar
  20. Freeman AW (2005) Multistage model for binocular rivalry. J Neurophysiol 94: 4412–4420PubMedCrossRefGoogle Scholar
  21. Friston KJ (1997) Another neural code?. Neuroimage 5: 213–220PubMedCrossRefGoogle Scholar
  22. Gertsner W, Kistler WM (2002) Hebbian models. In: Spiking neuron models: single neurons, populations, plasticity, chap 10. Cambridge University Press, LondonGoogle Scholar
  23. Gray CM (1999) The temporal correlation hypothesis is still alive and well. Neuron 24: 31–47PubMedCrossRefGoogle Scholar
  24. Grossberg S, Swaminathan G (2004) A laminar cortical model for 3D perception of slanted and curved surfaces and of 2D images: development, attention and bistability. Vision Res 44: 1147–1187PubMedCrossRefGoogle Scholar
  25. Hancock S, Andrews TJ (2007) The role of voluntary attention in selecting perceptual dominance during binocular rivalry. Perception 36: 288–298PubMedCrossRefGoogle Scholar
  26. Hodgkin AL, Huxley AF (1952) A quantitative description of membrane current and its applications to conduction and excitation in nerve. J Physiol 117: 500–544PubMedGoogle Scholar
  27. Hubel DH, Wiesel TN (1959) Receptive fields of single neurons in the cat’s striate cortex. J Physiol (Lond) 148: 574–591Google Scholar
  28. Hubel DH, Wiesel TN (1962) Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J Physiol (Lond) 160: 106–154Google Scholar
  29. Izhikevich EM (1998) Multiple cusp bifurcations. Neural Netw 11: 495–508PubMedCrossRefGoogle Scholar
  30. Kazanovich YB, Borisyuk RM (1999) Dynamics of neural networks with a central element. Neural Netw 12(3): 441–454PubMedCrossRefGoogle Scholar
  31. Keil A, Muller MM, Ray WJ, Gruber T, Elbert T (1999) Human gamma band activity and perception of a Gestalt. J Neurosci 19(16): 7152–7161PubMedGoogle Scholar
  32. Klemm WR, Li TH, Hernandez JL (2000) Coherent EEG indicators of cognitive binding during ambiguous figure tasks. Conscious. Cogn 9: 66–85PubMedCrossRefGoogle Scholar
  33. Klink PC, van Ee R, Nijs MM, Bruwer GJ, Noest AJ, van Wezel RJA (2008) Early interactions between neuronal adaptation and voluntary control perceptual choices in bistable vision. J Vis 8(5):16, 1–18Google Scholar
  34. Kruse P, Carmesin HO, Pahlke L, Strüber D, Stadler M (1996) Continuous phase transitions in the perception of multistable visual patterns. Biol Cybern 75: 321–330PubMedCrossRefGoogle Scholar
  35. Kuramoto Y (1984) Chemical oscillations, waves, and turbulence. Springer, BerlinGoogle Scholar
  36. Laing CR, Chow CC (2002) A spiking neuron model for binocular rivalry. J Comput Neurosci 12: 39–53PubMedCrossRefGoogle Scholar
  37. Lehky SR (1988) An astable multivibrator model of binocular rivalry. Perception 17: 215–228PubMedCrossRefGoogle Scholar
  38. Leopold DA, Wilke M, Maier A, Logothetis NK (2002) Stable perception of visually ambiguous patterns. Nature Neurosci 5: 605–609PubMedCrossRefGoogle Scholar
  39. Levelt WJM (1968) On binocular rivalry. The Hague, MoutonGoogle Scholar
  40. Logothetis NK, Leopold DA, Sheinberg DL (1996) What is rivaling during binocular rivalry?. Nature 380: 621–624PubMedCrossRefGoogle Scholar
  41. Lumer ED (1998) A neural model of binocular integration and rivalry based on the coordination of action-potential timing in primary visual cortex. Cereb Cortex 8: 553–561PubMedCrossRefGoogle Scholar
  42. Mathes B, Struber D, Stadler MA, Basar-Eroglu C (2006) Voluntary control of Neckar cube reversals modulates the EEG delta- and gamma-band response. Neurosci Lett 402: 145–149PubMedCrossRefGoogle Scholar
  43. Mainen ZF, Sejnowski TJ (1995) Reliability of spike timing in neocortical neurons. Science 268: 1503–1506PubMedCrossRefGoogle Scholar
  44. Melloni L, Molina C, Pena M, Torres D, Singer W, Rodriguez E (2007) Synchronization of neural activity across cortical areas correlates with conscious perception. J Neurosci 27(11): 2858–2865PubMedCrossRefGoogle Scholar
  45. Meng M, Tong F (2004) Can attention selectively bias bistable perception? Differences between binocular rivalry and ambiguous figures. J Vis 4: 539–551PubMedCrossRefGoogle Scholar
  46. Montemurro MA, Rasch MJ, Murayama Y, Logothetis NK, Panzeri S (2008) Phase of firing coding of natural visual stimuli in primary visual cortex. Curr Biol 18: 375–380PubMedCrossRefGoogle Scholar
  47. Moore GP, Segundo JP, Perkel DH, Levitan H (1970) Statistical signs of synaptic interaction in neurons. Biophys J 10: 876–900PubMedCrossRefGoogle Scholar
  48. Moreno-Bote R, Rinzel J, Rubin N (2007) Noise-induced alternations in an attractor network model perceptual bistability. J Neurophysiol 98: 1125–1139PubMedCrossRefGoogle Scholar
  49. Nakatani H, van Leeuwen C (2006) Transient synchrony of distant brain areas and perceptual switching in ambiguous figures. Biol Cybern 94: 445–457PubMedCrossRefGoogle Scholar
  50. Necker LA (1832) Observations on some remarkable phenomenon which occurs on viewing a figure of a crystal of geometrical solid. Lond Edinb Philos Mag J Sci 3: 329–337Google Scholar
  51. Ogawa Y, Isokawa T, Matsui N, Murata T (2000) A neural network model for perceptual alternation of ambiguous figures. In: Proc IEEE intl workshop on robot and human interactive communication, pp 264–269Google Scholar
  52. Olshausen BA, Field DJ (2004) Sparse coding of sensory inputs. Curr Opin Neurobiol 14: 481–487PubMedCrossRefGoogle Scholar
  53. Reike F, Warland D, de Ruyter van Steveninck R, Bialek W (1999) Spikes: exploring the neural code. MIT Press, CambridgeGoogle Scholar
  54. Rock I, Gopnik A, Hall S (1994) Do young children reverse ambiguous figures?. Perception 23(6): 635–644PubMedCrossRefGoogle Scholar
  55. Royer S, Paré D (2003) Conservation of total synaptic weights via inverse homo- vs. heterosynaptic LTD and LTP. Nature 422: 518–522PubMedCrossRefGoogle Scholar
  56. Rubin E (1921) Visuell wahrgenommene Figuren. Gyldendals, CopenhagenGoogle Scholar
  57. Shadlen MN, Newsome WT (1994) Noise, neural codes and cortical organization. Curr Opin Neurobiol 4: 569–579PubMedCrossRefGoogle Scholar
  58. Shpiro A, Curtu R, Rinzel J, Rubin N (2007) Dynamical characteristics common to neuronal competition models. J Neurophysiol 97: 462–473PubMedCrossRefGoogle Scholar
  59. Singer W, Gray CM (1995) Visual feature integration and the temporal correlation hypothesis. Ann Rev Neurosci 18: 555–586PubMedCrossRefGoogle Scholar
  60. Slotnick SD, Yantis S (2005) Common neural substrates for the control and effects of visual attention and perceptual bistability. Cogn Brain Res 24: 97–108CrossRefGoogle Scholar
  61. Stuart E, Walter M, Borisyuk R (2005) The correlation grid: analysis of synchronous spiking in multi-dimensional spike train data and identification of feasible connection architectures. Biosystems 79: 223–233PubMedCrossRefGoogle Scholar
  62. Sudhof TC (2000) The synaptic vesicle cycle revisited. Neuron 28: 317–320PubMedCrossRefGoogle Scholar
  63. Suzuki S, Grabowecky M (2002) Evidence for perceptual trapping and adaptation in multistable binocular rivalry. Neuron 36: 143–157PubMedCrossRefGoogle Scholar
  64. Tiesinga P, Fellous JM, Sejnowski TJ (2008) Regulation of spike timing in visual cortical circuits. Nat Rev Neurosci 9: 97–109PubMedCrossRefGoogle Scholar
  65. Tsodyks M, Adini Y, Sagi D (2004) Associative learning in early vision. Neural Netw 17: 823–832PubMedCrossRefGoogle Scholar
  66. Turrigiano GG, Nelson SB (2004) Homeostatic plasticity in the developing nervous system. Nat Rev Neurosci 5: 97–107PubMedCrossRefGoogle Scholar
  67. Vaadia E, Haalman I, Abeles M, Bergman H, Prut Y, Slovin H, Aersten A (1995) Dynamics of neural interactions in monkey cortex in relation to behavior events. Nature 373: 703–710CrossRefGoogle Scholar
  68. Van Ee R, Noest AJ, Brascamp JW, van der Berg AV (2006) Attentional control over either of the two competing percepts of ambiguous stimuli revealed by a two-parameter analysis: means do not make the difference. Vision Res 46: 3129–3141PubMedCrossRefGoogle Scholar
  69. Volgushev M, Chistiakova M, Singer W (1997) Modification of discharge patterns of neocortical neurons by induced oscillations of the membrane potential. Neuroscience 83: 15–25CrossRefGoogle Scholar
  70. Von der Malsburg C (2001) Neural basis of binding problem. In: Smelser NJ, Baltes PB (eds) International encyclopedia of social and behavioural sciences. Elsevier, Amsterdam, pp 1178–1180Google Scholar
  71. Wilson HR (2003) Computational evidence for a rivalry hierarchy in vision. PNAS 100(24): 14499–14503PubMedCrossRefGoogle Scholar
  72. Windmann S, Wehrmann M, Calabrese P, Gunturkun O (2006) Role of the prefrontal cortex in attentional control over bistable vision. J Cogn Neuro 18(3): 456–471CrossRefGoogle Scholar
  73. Zucker RS, Regehr WG (2002) Short-term synaptic plasticity. Ann Rev Physiol 64: 355–405CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  1. 1.Centre for Theoretical and Computational NeuroscienceUniversity of PlymouthPlymouthUK
  2. 2.Institute of Mathematical Problems in BiologyRussian Academy of Sciences, PushchinoMoscow RegionRussia

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