Balance between noise and adaptation in competition models of perceptual bistability
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Abbott, L. F., Varela, J. A., Sen, K., & Nelson, S. B. (1997). Synaptic depression and cortical gain control. Science, 275(5297), 220–224
Amit, D. J., & Brunel, N. (1997). Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex. Cerebral Cortex, 7, 237–252.
Brunel, N., & Sergi, S. (1998). Firing frequency of leaky integrate-and-fire neurons with synaptic current dynamics. Journal of Theoretical Biology, 195(1), 87–95.
Buice, M. A., & Chow, C. C. (2007). Correlations, fluctuations, and stability of a finite-size network of coupled oscillators. Physical Review E, 76, 031118.
Curtu, R., Shpiro, A., Rubin, N., & Rinzel, J. (2008). Mechanisms for frequency control in neuronal competition models. SIAM Journal on Applied Dynamical Systems, 7(2), 609–649.
Descalzo, V. F., Nowak, L. G., Brumberg, J. C., McCormick, D. A., & Sanchez-Vives, M. V. (2005). Slow adaptation in fast-spiking neurons of visual cortex. Journal of Neurophysiology, 93(2), 1111–8.
Fox, R., & Herrmann, J. (1967). Stochastic properties of binocular rivalry alterations. Perception and Psychophysics, 2, 432–436.
Freeman, A. W. (2005). Multistage model for binocular rivalry. Journal of Neurophysiology, 94, 4412–4420.
Grossberg, S. (1973). Contour enhancement, short-term memory, and constancies in reverberating neural networks. Studies in Applied Mathematics, 52, 217–257.
Guckenheimer, J., & Holmes, P. (2002). Nonlinear oscillations, dynamical systems, and bifurcations of vector field. New York: Springer.
Gutkin, B. S., & Ermentrout, G. B. (1998). Dynamics of membrane excitability determine interspike interval variability: A link between spike generation mechanisms and cortical spike train statistics. Neural Computation, 10, 1047–1065.
Haken, H. (1994). A brain model for vision in terms of synergetics. Journal of Theoretical Biology, 171, 75–85.
Haynes, J. D., Deichmann, R., & Rees, G. (2005). Eye-specific effects of binocular rivalry in the human lateral geniculate nucleus. Nature, 438, 496–499.
Hertz, J., Krogh, A., & Palmer, R. G. (1991). Introduction to the theory of neural computation. Redwood City: Addison-Wesley.
Hupe, J. M., & Rubin, N. (2003). The dynamics of bistable alternation in ambiguous motion displays: A fresh look at plaids. Vision Research, 43, 531–548.
Julesz, B. (1971). Foundations of cyclopean perception. Chicago: University of Chicago Press.
Kalarickal, G. J., & Marshall, J. A. (2000). Neural model of temporal and stochastic properties of binocular rivalry. Neurocomputing, 32–33, 843–853.
Kim, Y. J., Grabowecky, M., & Suzuki, S. (2006). Stochastic resonance in binocular rivalry. Vision Research, 46, 392–406.
Kramers, H. A. (1940) Brownian motion in a field of force and the diffusion model of chemical reactions. Physica, 7, 284–304.
Lago-Fernandez, L. F., & Deco, G. (2002). A model of binocular rivalry based on competition in IT. Neurocomputing, 44, 503–507.
Laing, C. R., & Chow, C. C. (2002). A spiking neuron model for binocular rivalry. Journal of Computational Neuroscience, 12, 39–53.
Lehky, S. R. (1995). Binocular rivalry is not chaotic. Proceedings: Biological Sciences, 259(1354), 71–76.
Leopold, D. A., & Logothetis, N. K. (1996). Activity changes in early visual cortex reflect monkeys’ percepts during binocular rivalry. Nature, 379, 549-554.
Levelt, W. J. M. (1968). On binocular rivalry. The Hague: Mouton.
Logothetis, N. K. (1998). A primer on binocular rivalry, including current controversies. Philosophical Transactions of the Royal Society of London, B, 353, 1801–1818.
Logothetis, N. K., Leopold, D. A., & Sheinberg, D. L. (1996). What is rivaling during binocular rivalry? Nature, 380, 621–624.
Mattia, M., & Del Giudice, P. (2002). Population dynamics of interacting spiking neurons. Physical Review E, 66, 051917.
McClave, J., & Sincich, T. (2006). Statistics, 10th ed., section 8.3. Englewood Cliffs: Pearson Prentice Hall.
Meng, M., & Tong, F. (2004). Can attention selectively bias bistable perception? Differences between binocular rivalry and ambiguous figures. Journal of Vision, 4, 539–551.
Moldakarimov, S., Rollenhagen, J. E., Olson, C. R., & Chow, C. C. (2005). Competitive dynamics in cortical responses to visual stimuli. Journal of Neurophysiology, 94, 3388–3396.
Moreno-Bote, R., & Parga, N. (2004). Role of synaptic filtering on the firing response of simple model neurons. Physical Reviews Letters, 92, 0281021–0281024.
Moreno-Bote, R., Rinzel, J., & Rubin, N. (2007). Noise-induced alternations in an attractor network model of perceptual bistability. Journal of Neurophysiology, 98, 1125–1139.
Moreno-Bote, R., Shpiro. A., Rinzel, J., & Rubin, N. (2008). Bi-stable depth ordering of superimposed moving grating. Journal of Vision, 8(7), 20, 1–13.
Mueller, T. J., & Blake, R. (1989). A fresh look at the temporal dynamics of binocular rivalry. Biological Cybernetics, 61, 223–232.
Necker, L. A. (1832). Observations on some remarkable phenomenon which occurs on viewing a figure of a crystal of geometrical solid. London and Edinburgh Philosophical Magazine and Journal of Science, 3, 329–337.
Riani, M., & Simonotto, E. (1994). Stochastic resonance in the perceptual interpretation of ambiguous figures: A neural network model. Physical Reviews Letters, 72, 3120–3123.
Rubin, E. (1921). Visuellwahrgenommene Figuren, Gyldendals, Copenhagen. Partial version in English in: Rubin, E. (2001). Figure and ground. In S. Yantis (Ed.), Visual perception: Essential readings. Hove: Psychology Press.
Rubin, N., & Hupe, J. M. (2004). Dynamics of perceptual bistability: Plaids and binocular rivalry compared. In: D. Alais, & R. Blake (Eds.), Binocular rivalry. Cambridge: MIT.
Salinas, E. (2003). Background synaptic activity as a switch between dynamical states in a network. Neural Computation, 15(7), 1439–1475.
Shpiro, A., Curtu, R., Rinzel, J., & Rubin, N. (2007). Dynamical characteristics common to neuronal competition models. Journal of Neurophysiology, 97, 462–473.
Soula, H., & Chow, C. C. (2007). Stochastic dynamics of a finite-size spiking neural network. Neural Computation, 19(12), 3262–3292.
Stollenwerk, L., & Bode, M. (2003). Lateral neural model of binocular rivalry. Neural Computation, 15, 2863–2882.
van Dam, L., Mulder, R., Noest, A., Brascamp, J., van den Berg, B., & van Ee, R. (2007). Sequential dependency in percept durations for binocular rivalry. (Abstract). Journal of Vision, 7(9), 53,53a.
van Kampen, N. G. (2001). Stochastic processes in physics and chemistry. Amsterdam: North Holland.
Varela, J. A., Sen, K., Gibson, J., Fost, J., Abbot, L. F., & Nelson, S. B. (1997). A quantitative description of short-term plasticity at excitatory synapses in layer 2/3 of rat primary visual cortex. Journal of Neuroscience, 17, 7926.
Wallach, H. (1935). Uber visuell wahrgenommene Bewegungsrichtung. Psychologische Forschung, 20, 325–380. [English translation in: Wuerger, S., et al. (1996). ’On the visually perceived direction of motion’ by Hans Wallach: 60 years later. Perception, 25, 1317–1367].
Wang, X.-J., & Rinzel, J. (1992). Alternating and synchronous rhythms in reciprocally inhibitory model neurons. Neural Computation, 4, 84–97.
Wheatstone, C. (1838). Contributions to the physiology of vision. Part I: On some remarkable, and hitherto unobserved, phenomena of binocular vision. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, Series 43, 241–267.
Wilson, H. R. (2003). Computational evidence for a rivalry hierarchy in vision. Proceeding of the National Academy of Sciences USA, 100, 14499–14503.
Wilson, H. R. (2007). Minimal physiological conditions for binocular rivalry and rivalry memory. Vision Research, 47(21), 2741–2750.
Wilson, H. R., & Cowan, J. D. (1972). Excitatory and inhibitory interactions in localized populations of model neurons. Biophysical Journal, 12, 1–24.