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A unified neural network model of spatiotemporal processing in X and Y retinal ganglion cells

II. Temporal adaptation and simulation of experimental data

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Abstract

This article makes use of a push-pull shunting network, which was introduced in the companion article, to model certain properties of X and Y retinal ganglion cells. Input to the push-pull network is preprocessed by a nonlinear mechanism for temporal adaptation, which is ascribed here to photoreceptor dynamics. The complete circuit is used to show that a simple change in receptive field morphology within a single model equation can change the network's response characteristics to closely resemble those of either X or Y cells. Specifically, an increase in width of the receptive field center mechanism is sufficient to account for generation of on-off (Y-like) instead of null (X-like) responses to modulated gratings. In agreement with experimental data, the Y cell on-off response is independent of spatial phase. Also, the model accurately predicts that on-off responses can be observed in X cells for particular stimulus configurations. Taken together, the results show how the retina combines individually inadequate modules to efficiently handle the tasks required for accurate spatial and temporal visual information processing. The model is also able to clarify a number of controversial experimental findings on the nature of spatiotemporal visual processing in the retina.

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References

  • Barlow HB (1953) Summation and inhibition in the frog retina. J Physiol (London) 119:69–88

    Google Scholar 

  • Baylor DA, Hodgkin AL, Lamb TD (1974) Reconstruction of the electrical responses of turtle cones to flashes and steps of light. J Physiol (London) 242:759–791

    Google Scholar 

  • Boycott BB, Wässle H (1974) The morphological types of ganglion cells of the domestic cat's retina. J Physiol (London) 240:397–419

    Google Scholar 

  • Carpenter GA, Grossberg S (1981) Adaptation and transmitter gating in vertebrate photoreceptors. J Theor Neurobiol 1:1–42

    Google Scholar 

  • Cleland BG, Levick WR (1974) Brisk and sluggish concentrically organized ganglion cells in the cat's retina. J Physiol (London) 240:421–456

    Google Scholar 

  • Dowling JE (1987) The retina: an approachable part of the brain. Belknap, Cambridge

    Google Scholar 

  • Emerson RC, Korenberg MJ, Citron MC (1989) Identification of intensive nonlinearities in cascade models of visual cortex and its relation to cell classification. In: Marmarelis VZ (ed) Advanced methods of physiological system modeling. Plenum Press, New York

    Google Scholar 

  • Enroth-Cugell C, Robson JC (1966) The contrast sensitivity of retinal ganglion cells of the cat. J Physiol (London) 197:517–552

    Google Scholar 

  • Freed MA, Smith RG, Sterling P (1992) Computational model of the On-alpha ganglion cell receptive field based on bipolar cell circuits. Proc Natl Acad Sci USA 89:236–240

    Google Scholar 

  • Fukuda Y, Hsiao C-F, Watanabe M, Ito H (1984) Morphological correlates of physiologically identified Y, X and W cells in the cat retina. J Neurophysiol 52:999–1013

    Google Scholar 

  • Gaudiano P (1991) Neural network models for spatio-temporal visual processing and adaptive sensor-motor control. Unpublished Doctoral Dissertation, Boston University

  • Gaudiano P (1992a) A unified neural network model of spatiotemporal processing in X and Y retinal ganglion cells. I: Analytical results. Biol Cybern (this issue)

  • Gaudiano P (1992b) Toward a unified theory of spatiotemporal processing in the retina. In: Carpenter G, Grossberg S (eds) Neural networks for vision and image processing. MIT Press, Cambridge (in press)

    Google Scholar 

  • Grossberg S (1968) Some physiological and biochemical consequences of psychological postulates. Proc Natl Acad Sci USA 60:758–765

    Google Scholar 

  • Grossberg S (1969) On the production and release of chemical transmitters and related topics in cellular control. J Theor Biol 22:325–364

    Google Scholar 

  • Grossberg S (1970) Neural pattern discrimination. J Theor Biol 27:291–337

    Google Scholar 

  • Grossberg S (1980a) Intracellular mechanisms of adaptation and self-regulation in self-organizing networks: the role of chemical transducers. Bull Math Biol 42:365–396

    Google Scholar 

  • Grossberg S (1980b) How does a brain build a cognitive code? Psych Rev 1:1–51

    Google Scholar 

  • Hochstein S, Shapley RM (1976a) Quantitative analysis of retinal ganglion cell classification. J Physiol (London) 262:237–264

    Google Scholar 

  • Hochstein S, Shapley RM (1976b) Linear and nonlinear spatial subunits in Y cat retinal ganglion cells. J Physiol (London) 262:265–284

    Google Scholar 

  • Koch C, Poggio T, Torre V (1987) Computation in the vertebrate retina: gain enhancement, differentiation and motion discrimination. TINS 9:204–211

    Google Scholar 

  • Kuffler SW (1953) Discharge patterns and functional organization of the mammalian retina. J Physiol (London) 16:37–68

    Google Scholar 

  • Melkonian DS (1990) Mathematical theory of chemical synaptic transmission. Biol Cybern 62:539–548

    Google Scholar 

  • McGuire BA, Stevens JK, Sterling P (1986) Microcircuitry of beta ganglion cells in cat retina. J Neurosci 6:907–918

    Google Scholar 

  • Öğmen H (1991) On the mechanisms underlying directional selectivity. Neural Comput 3:333–349

    Google Scholar 

  • Öğmen H (1992) Sensorial nonassociative learning and its implications for visual perception. In: Omidvar (ed) Progress in Neural Networks. Ablex, NJ (in press)

    Google Scholar 

  • Öğmen H, Gagné S (1990a) Neural models for sustained and ONOFF units of insect lamina. Biol Cybern 63:51–60

    Google Scholar 

  • Öğmen H, Gagné S (1990b) Neural network architectures for motion perception and elementary motion detection in the fly visual system. Neural Networks 3:487–505

    Google Scholar 

  • Pugh EN Jr, Cobbs WH (1988) Visual transduction in vertebrate rods and cones: a tale of two transmitters, calcium and cyclic GMP. Vision Res 26:1613–1643

    Google Scholar 

  • Pugh EN Jr, Lamb TD (1990) Cyclic GMP and calcium: the internal messengers of excitation and adaptation in vertebrate photoreceptors. Vision Res 30:1923–1948

    Google Scholar 

  • Richter J, Ullman S (1983) A model for the temporal organization of X- and Y-type receptive fields in the primate retina. Biol Cybern 43:127–145

    Google Scholar 

  • Rodieck RW (1965) Quantitative analysis of cat retinal ganglion cell response to visual stimuli. Vision Res 5:583–601

    Google Scholar 

  • Rushton WAH (1958) Kinetics of cone pigments measured objectively on the living human fovea. Ann NY Acad Sci 74:291–304

    Google Scholar 

  • Satio H (1983) Morphology of physiologically identified X-, Y- and W-type retinal ganglion cells of the cat. J Comp Neurol 221:279–288

    Google Scholar 

  • Siminoff R (1991) Simulated bipolar cells in fovea of human retina. Part I. Computer simulation. Biol Cybern 64:497–504

    Google Scholar 

  • Sperling G (1970) Model of visual adaptation and contrast detection. Percept Psychophys 8:143–157

    Google Scholar 

  • Sterling P (1990) Retina. In: Shepherd GM (ed) The synaptic organization of the brain, 3rd edn, chap 6. Oxford University Press, New York, pp 170–213

    Google Scholar 

  • Sterling P, Freed M, Smith RG (1987) Microcircuitry and functional architecture of the cat retina. TINS 9:186–192

    Google Scholar 

  • Werblin F (1991) Synaptic connections, receptive fields, and patterns of activity in the tiger slamander retina. Invest Ophthalmol Vis Sci 32:459–483

    Google Scholar 

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Gaudiano, P. A unified neural network model of spatiotemporal processing in X and Y retinal ganglion cells. Biol. Cybern. 67, 23–34 (1992). https://doi.org/10.1007/BF00201799

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  • DOI: https://doi.org/10.1007/BF00201799

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