A Hierarchical Model of Binocular Rivalry

Neural Computation

Volumn 10, Issue 5, 1998, Pages 1119-1135

  Dayan, Peter ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BINOCULAR VISION; BIOLOGICAL MODEL; HEMISPHERIC DOMINANCE; NERVE CELL; PHOTOSTIMULATION; PHYSIOLOGY; VISUAL CORTEX;

ALGORITHMS; FUNCTIONAL LATERALITY; MODELS, NEUROLOGICAL; NEURONS; PHOTIC STIMULATION; VISION, BINOCULAR; VISUAL CORTEX;

EID: 0032111193     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976698300017377     Document Type: Article

References (43)

1. Bialek, W., & DeWeese, M. (1995). Random switching and optimal processing in the perception of ambiguous signals. Physical Review Letters, 74, 3077-3080.
2. Blake, R. (1977). Threshold conditions for binocular rivalry. Journal of Experimental Psychology: Human Perception and Performance, 3, 251-257.
3. Blake, R. (1989). A neural theory of binocular rivalry. Psychological Review, 96, 145-167.
4. Blake, R., & Fox, R. (1974). Binocular rivalry suppression: Insensitive to spatial frequency and orientation change. Vision Research, 14, 687-692.
5. Blake, R., Westendorf, D. H., & Overton, R. (1980). What is suppressed during binocular rivalry? Perception, 9, 223-231.
6. Carandini, M., & Heeger, D. J. (1994). Summation and division by neurons in primate visual cortex. Science, 264, 1333-1336.
7. Carpenter, G., & Grossberg, S. (1987). A massively parallel architecture for a self-organizing neural pattern recognition machine. Computer Vision, Graphics and Image Processing, 37, 54-115.
8. Dayan, P., & Hinton, G. E. (1996). Varieties of Helmholtz machine. Neural Networks, 9, 1385-1403.
9. Dayan, P., Hinton, G. E., Neal, R. M., & Zemel, R. S. (1995). The Helmholtz machine. Neural Computation, 7, 889-904.
10. Fox, R., & Check, R. (1972). Independence between binocular rivalry suppression duration and magnitude of suppression. Journal of Experimental Psychology, 93, 283-289.
11. Fox, R., & Herrmann, J. (1967). Stochastic properties of binocular rivalry alternations. Perception and Psychophysics, 2, 432-436.
12. Fox, R., & Rasche, F. (1969). Binocular rivalry and reciprocal inhibition. Perception and Psychophysics, 5, 215-217.
13. Grenander, U. (1976-1981). Lectures in pattern theory I, II and III: Pattern analysis, pattern synthesis and regular structures. Berlin: Springer-Verlag.
14. Grossberg, S. (1987). Cortical dynamics of three-dimensional form, color and brightness perception: 2. Binocular theory. Perception and Psychophysics, 41, 117-158.
15. Hinton, G. E., Dayan, P., Frey, B. J., & Neal, R. M. (1995). The wake-sleep algorithm for unsupervised neural networks. Science, 268, 1158-1160.
16. Jaakkola, T., Saul, L. K., & Jordan, M. I. (1996). Fast learning by bounding likelihoods in sigmoid type belief networks. In D. S. Touretzky, M. C. Mozer, & M. E. Hasselmo (Eds.), Advances in neural information processing systems 8. Cambridge, MA: MIT Press.
17. Kovacs, I., Papathomas, T. V., Yang, M., & Feher, A. (1996). When the brain changes its mind: Interocular grouping during binocular rivalry. Proceedings of the National Academy of Sciences of the United States of America, 93, 15508-15511.
18. Lehky, S. R. (1988). An astable multivibrator model of binocular rivalry. Perception, 17, 215-228.
19. Lehky, S. R. (1995). Binocular rivalry is not chaotic. Proceedings of the Royal Society of London, Series B: Biological Sciences, 259, 71-76.
20. Lehky, S. R., & Blake, R. (1991). Organization of binocular pathways: Modeling and data related to rivalry. Neural Computation, 3, 44-53.
21. Lehky, S. R., & Maunsell, J. H. (1996). No binocular rivalry in the LGN of alert macaque monkeys. Vision Research, 36, 1225-1234.
22. Leopold, D. A., & Logothetis, N. K. (1996). Activity changes in early visual cortex reflect monkeys' percepts during binocular rivalry. Nature, 379, 549-554.
23. Levelt, W. J. M. (1965). On binocular rivalry. Soesterberg, Netherlands: Institute for Perception RVO-TNO.
24. Liu, L., Tyler, C. W., & Schor, C. (1992). Failure of rivalry at low contrast: Evidence of a suprathreshold binocular summation. Vision Research, 32, 1471-1479.
25. Logothetis, N. K., Leopold, D. A., & Sheinberg, D. L. (1996). What is rivalling during binocular rivalry. Nature, 380, 621-624.
26. Logothetis, N. K., & Schall, J. D. (1989). Neuronal correlates of subjective visual perception. Science, 245, 761-763.
27. MacKay, D. M. (1956). The epistemological problem for automata. In C. E. Shannon & J. McCarthy (Eds.), Automata studies (pp. 235-251). Princeton, NJ: Princeton University Press.
28. Matsuoka, K. (1984). The dynamic model of binocular rivalry. Biological Cybernetics, 49, 201-208.
29. Mueller, T. J. (1990). A physiological model of binocular rivalry. Visual Neuroscience, 4, 63-73.
30. Mueller, T. J., & Blake, R. (1989). A fresh look at the temporal dynamics of binocular rivalry. Biological Cybernetics, 61, 223-232.
31. Mumford, D. (1994). Neuronal architectures for pattern-theoretic problems. In C. Koch and J. Davis (Eds.), Large-scale theories of the cortex (pp. 125-152). Cambridge, MA: MIT Press.
32. Neal, R. M. (1993). Probabilistic inference using Markov Chain Monte Carlo methods (Tech. Rep. No. CRG-TR-93-1). Toronto: Department of Computer Science, University of Toronto.
33. Olshausen, B. A., & Field, D. J. (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381, 607-609.
34. Pearl, J. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. San Mateo, CA: Morgan Kaufmann.
35. Pece, A. E. C. (1992). Redundancy reduction of a Gabor representation: A possible computational role for feedback from primary visual cortex to lateral geniculate nucleus. In I. Aleksander & J. Taylor (Eds.), Artificial Neural Networks, 2 (pp. 865-868) Amsterdam: Elsevier.
36. Rao, P. N. R., & Ballard, D. H. (1997). Dynamic model of visual recognition predicts neural response properties in the visual cortex. Neural Computation, 9, 721-764.
37. Saul, L. K., Jaakkola, T., & Jordan, M. I. (1996). Mean field theory for sigmoid belief networks. Journal of Artificial Intelligence Research, 4, 61-76.
38. Sengpiel, F., Blakemore, C., & Harrad, R. (1995). Interocular suppression in the primary visual cortex: A possible neural basis of binocular rivalry. Vision Research, 35, 179-195.
39. Varela, F. J., & Singer, W. (1987). Neuronal dynamics in the visual corticothalamic pathway revealed through binocular rivalry. Experimental Brain Research, 66, 10-20.
40. Wales, R., & Fox, R. (1970). Increment detection thresholds during binocular rivalry suppression. Perception and Psychophysics, 8, 90-94.
41. Wheatstone, C. (1838). Contributions to the theory of vision. I: On some remarkable and hitherto unobserved phenomena of binocular vision. Philosophical Transactions of the Royal Society of London, 128, 371-394.
42. Whittle, P., Bloor, D. C., & Pocock, (1968). Some experiments on figurai effects in binocular rivalry. Perception and Psychophysics, 4, 183-188.
43. Yu, K., & Blake, R. (1992). Do recognizable figures enjoy an advantage in binocular rivalry? Journal of Experimental Psychology: Human Perception and Performance, 18, 1158-1173.