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Brightness perception, illusory contours, and corticogeniculate feedback

Published online by Cambridge University Press:  02 June 2009

Alan Gove ,
Stephen Grossberg  and
Ennio Mingolla
Alan Gove
Affiliation:
MIT Lincoln Laboratory, 244 Wood Street, Lexington
Stephen Grossberg
Affiliation:
Department of Cognitive and Neural Systems and Center for Adaptive Systems, Boston University, Boston
Ennio Mingolla
Affiliation:
Department of Cognitive and Neural Systems and Center for Adaptive Systems, Boston University, Boston
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Abstract

A neural network model is developed to explain how visual thalamocortical interactions give rise to boundary percepts such as illusory contours and surface percepts such as filled-in brightnesses. Top-down feedback interactions are needed in addition to bottom-up feed-forward interactions to simulate these data. One feedback loop is modeled between lateral geniculate nucleus (LGN) and cortical area V1, and another within cortical areas V1 and V2. The first feedback loop realizes a matching process which enhances LGN cell activities that are consistent with those of active cortical cells, and suppresses LGN activities that are not. This corticogeniculate feedback, being endstopped and oriented, also enhances LGN ON cell activations at the ends of thin dark lines, thereby leading to enhanced cortical brightness percepts when the lines group into closed illusory contours. The second feedback loop generates boundary representations, including illusory contours, that coherently bind distributed cortical features together. Brightness percepts form within the surface representations through a diffusive filling-in process that is contained by resistive gating signals from the boundary representations. The model is used to simulate illusory contours and surface brightnesses induced by Ehrenstein disks, Kanizsa squares, Glass patterns, and cafe wall patterns in single contrast, reverse contrast, and mixed contrast configurations. These examples illustrate how boundary and surface mechanisms can generate percepts that are highly context-sensitive, including how illusory contours can be amodally recognized without being seen, how model simple cells in V1 respond preferentially to luminance discontinuities using inputs from both LGN ON and OFF cells, how model bipole cells in V2 with two colinear receptive fields can help to complete curved illusory contours, how short-range simple cell groupings and long-range bipole cell groupings can sometimes generate different outcomes, and how model double-opponent, filling-in and boundary segmentation mechanisms in V4 interact to generate surface brightness percepts in which filling-in of enhanced brightness and darkness can occur before the net brightness distribution is computed by double-opponent interactions.

Keywords

BrightnessIllusory contoursLateral geniculate nucleusVisual cortexNeural networksAdaptive resonance theory
Type
Research Articles
Information
Visual Neuroscience , Volume 12 , Issue 6 , November 1995 , pp. 1027 - 1052
Copyright
Copyright © Cambridge University Press 1995

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References

REFERENCES

Andreou, A.G. & Boahen, K.A. (1991). Modeling inner and outer plexiform retinal processing using nonlinear, coupled resistive networks. In Human Vision, Visual Processing, and Digital Display II, SPIE, 1453, pp. 270–281. Bellington, Washington: Society of Photo-Optical Instrumentation Engineers.CrossRefGoogle Scholar
Arrington, K. (1994). The temporal dynamics of brightness filling-in. Vision Research 34, 3371–3387.CrossRefGoogle ScholarPubMed
Carpenter, G.A. & Grossberg, S. (1991). Pattern Recognition by Self-Organizing Neural Networks. Cambridge, Massachusetts: MIT Press.CrossRefGoogle Scholar
Carpenter, G.A. & Grossberg, S. (1993). Normal and amnesic learning, recognition, and memory by a neural model of cortico-hippo-campal interactions. Trends in Neurosciences 16, 131–137.CrossRefGoogle ScholarPubMed
Cohen, M.A. & Grossberg, S. (1984). Neural dynamics of brightness perception: Features, boundaries, diffusion, and resonance. Perception and Psychophysics 36, 428–456.CrossRefGoogle ScholarPubMed
Coren, S. & Harland, R.E. (1993). Subjective contours and visual-geometric illusions: Do they share common mechanisms? Italian Journal of Psychology 20, 709–730.Google Scholar
Cruthirds, D.R., Gove, A., Grossberg, S., Mingolla, E., Nowak, N. & Williamson, J. (1992). Processing of synthetic aperture radar images by the Boundary Contour System and Feature Contour System. Proceedings of the International Joint Conference on Neural Networks, IV, pp. 414–419. Picataway, New Jersey: IEEE Service Center.Google Scholar
Daugman, J.G. (1980). Two-dimensional spectral analysis of cortical receptive field profiles. Vision Research 20, 847–856.CrossRefGoogle ScholarPubMed
Day, R.H. & Jory, M.K. (1978). Subjective contours, visual acuity, and line contrast. In Visual Psychophysics and Physiology, ed. Armington, J.C., Krauskopf, J.E. & Wooten, B., pp. 331–349. New York: Academic Press.CrossRefGoogle Scholar
De Yoe, E.A. & van Essen, D.C. (1988). Concurrent processing streams in monkey visual cortex. Trends in Neuroscience 11, 219–226.CrossRefGoogle ScholarPubMed
Desimone, R., Schein, S.J., Moran, J. & Ungerleider, L.G. (1985). Contour, color, and shape analysis beyond the striate cortex. Vision Research 25, 441–452.CrossRefGoogle ScholarPubMed
Dubin, M.W. & Cleland, B.G. (1977). Organization of visual inputs to interneurons of lateral geniculate nucleus of the cat. Journal of Neurophysiology 40, 410–427.CrossRefGoogle ScholarPubMed
Ehrenstein, W. (1941). Über Abwandlungen der L. Hermannschen Hel-ligkeitserscheinung. Zeitschrift für Psychologie 150, 83–91.Google Scholar
Elder, J. & Zucker, S. (1993). The effect of contour closure on the rapid discrimination of two-dimensional shapes. Vision Research 33, 981–991.CrossRefGoogle ScholarPubMed
Epstein, W. (1993). On seeing that thinking is separate and on thinking that seeing is the same. Italian Journal of Psychology 20, 731–747.Google Scholar
Ferster, D. (1988). Spatially opponent excitation and inhibition in simple cells of the cat visual cortex. Journal of Neuroscience 8, 1172–1180.CrossRefGoogle ScholarPubMed
Field, D.J., Hayes, A. & Hess, R.F. (1993). Contour integration by the human visual system: Evidence for a local “association field.” Vision Research 33, 173–193.CrossRefGoogle ScholarPubMed
Francis, G. & Grossberg, S. (1994). Cortical dynamics of form and motion integration: Persistence, apparent motion, and illusory contours. Technical Report CAS/CNS-TR-94–011, Boston, MA: Boston University. Vision Research (in press).Google Scholar
Francis, G. & Grossberg, S. (1995). Cortical dynamics of boundary segmentation and reset: Persistence, afterimages, and residual traces (Technical Report CAS/CNS-TR-95–002). Perception (in press).Google Scholar
Francis, G., Grossberg, S. & Mingolla, E. (1994). Cortical dynamics of feature binding and reset: Control of visual persistence. Vision Research 34, 1089–1104.CrossRefGoogle ScholarPubMed
Frisby, J.P. & Clatworthy, J.L. (1975). Illusory contours: Curious cases of simultaneous brightness contrast? Perception 4, 349–357.CrossRefGoogle Scholar
Funke, K. & Eysel, U.T. (1992). EEG-dependent modulation of response dynamics of cat dLGN relay cells and the contribution of corticogeniculate feedback. Brain Research 573, 217–227.CrossRefGoogle ScholarPubMed
Gilbert, C.D. & Kelly, J.P. (1975). The projections of cells in different layers of the cat≈s visual cortex. Journal of Comparative Neurology 163, 81–106.CrossRefGoogle Scholar
Gillam, B.J. & Goodenough, B. (1994). Subjective contours at line terminators – The effect of the relationship between terminator arrangement and line arrangement. Investigative Ophthalmology and Visual Science 35, 1627.Google Scholar
Glass, L. (1969). Moiré effect from random dots. Nature 223, 578–580.CrossRefGoogle ScholarPubMed
Gove, A.N., Grossberg, S. & Mingolla, E. (1994). A link between brightness perception, illusory contours, and binocular corticogeniculate feedback. Investigative Ophthalmology and Visual Science 35, 1437.Google Scholar
Gregory, R.L. (1993). Seeing and thinking. Italian Journal of Psychology 20, 749–769.Google Scholar
Grossberg, S. (1976). Adaptive pattern classification and universal recoding, II: Feedback, expectation, olfaction, and illusions. Biological Cybernetics 23, 187–202.CrossRefGoogle ScholarPubMed
Grossberg, S. (1980). How does a brain build a cognitive code? Psychological Review 87, 1–51.CrossRefGoogle ScholarPubMed
Grossberg, S. (1983). The quantized geometry of visual space: The coherent computation of depth, form, and lightness. Behavioral and Brain Sciences 6, 625–657.CrossRefGoogle Scholar
Grossberg, S. (1984). Outline of a theory of brightness, color, and form perception. In Trends in Mathematical Psychology, ed. Degreef, E. & van Buggenhaut, J., pp. 59–86. Amsterdam: Elsevier/North-Holland.CrossRefGoogle Scholar
Grossberg, S. (1987 a). Cortical dynamics of three-dimensional form, color, and brightness perception, I: Monocular theory. Perception and Psychophysics 41, 87–116.CrossRefGoogle ScholarPubMed
Grossberg, S. (1987 b). Cortical dynamics of three-dimensional form, color, and brightness perception, II: Binocular theory. Perception and Psychophysics 41, 117–158.CrossRefGoogle ScholarPubMed
Grossberg, S. (1994). 3–D vision and figure-ground separation by visual cortex. Perception and Psychophysics 55, 48–120.CrossRefGoogle ScholarPubMed
Grossberg, S. & Mingolla, E. (1985 a). Neural dynamics of form perception: Boundary completion, illusory figures, and neon color spreading. Psychological Review 92, 173–211.CrossRefGoogle ScholarPubMed
Grossberg, S. & Mingolla, E. (1985 b). Neural dynamics of perceptual grouping: Textures, boundaries, and emergent segmentations. Perception and Psychophysics 38, 141–171.CrossRefGoogle ScholarPubMed
Grossberg, S. & Mingolla, E. (1987). Neural dynamics of surface perception: Boundary webs, illuminants, and shape-from-shading. Computer Vision, Graphics, and Image Processing 37, 116–165.CrossRefGoogle Scholar
Grossberg, S., Mingolla, E. & Ross, W.D. (1994 a). A neural theory of attentive visual search: Interactions of boundary, surface, spatial, and object representations. Psychological Review 101, 470–489.CrossRefGoogle ScholarPubMed
Grossberg, S., Mingolla, E. & Williamson, J. (1994 b). Synthetic aperture radar processing by a multiple scale neural system for boundary and surface representation. Technical Report CAS/CNS-TR-94–001, Boston, MA: Boston University. Neural Networks (in press).Google Scholar
Grossberg, S., Mingolla, E. & Todorović, D. (1989). A neural network architecture for preattentive vision. IEEE Transactions on Biomedical Engineering 36, 65–83.CrossRefGoogle ScholarPubMed
Grossberg, S. & Todorović, D. (1988). Neural dynamics of 1–D and 2–D brightness perception: A unified model of classical and recent phenomena. Perception and Psychophysics 43, 241–277.CrossRefGoogle ScholarPubMed
Grossberg, S. & Wyse, L. (1991). A neural network architecture for figure-ground separation of connected scenic figures. Neural Networks 4, 723–742.CrossRefGoogle Scholar
Guillery, R.W. (1967). Patterns of fiber degeneration in the dorsal lateral geniculate nucleus of the cat following lesions in the visual cortex. Journal of Comparative Neurology 130, 197–222.CrossRefGoogle ScholarPubMed
Halpern, D.F. (1981). The determinants of illusory-contour perception. Perception 10, 199–213.CrossRefGoogle ScholarPubMed
Hubel, D.H. & Wiesel, T.N. (1977). Functional architecture of macaque monkey visual cortex. Proceedings of the Royal Society B (London) 198, 1–59.Google ScholarPubMed
Hull, D.H. (1968). Corticofugal influence in the macaque lateral geniculate nucleus of the cat. Vision Research 8, 1285–1298.CrossRefGoogle Scholar
Kalil, R.E. & Chase, R. (1970). Corticofugal influence on activity of lateral geniculate nucleus neurons in the cat. Journal of Neurophysiology 33, 459–474.CrossRefGoogle ScholarPubMed
Kanizsa, G. (1979). Organization in Vision. New York: Praeger Publishing.Google Scholar
Kellman, P.J. & Shipley, T.F. (1991). A theory of interpolation in object perception. Cognitive Psychology 23, 141–221.CrossRefGoogle ScholarPubMed
Kennedy, J.M. (1979). Subjective contours, contrast, and assimilation. In Perception and Pictorial Representation, ed. Nodine, C.F. & Fisher, D.F., New York: Praeger.Google Scholar
Kennedy, J.M. (1988). Line endings and subjective contours. Spatial Vision 3, 151–158.CrossRefGoogle ScholarPubMed
Koch, C. (1987). The action of the corticofugal pathway on sensory thalamic nuclei: A hypothesis. Neuroscience 23, 399–406.CrossRefGoogle ScholarPubMed
Lesher, G.W.Illusory contours: Toward a neurally based perceptual theory. Psychological Bulletin (in press).Google Scholar
Liu, Z., Gaska, J.P., Jacobson, L.D. & Pollen, D.A. (1992). Inter-neuronal interaction between members of quadrature phase and anti-phase pairs in the cat≈s visual cortex. Vision Research 32, 1193–1198.CrossRefGoogle Scholar
Marčelja, S. (1980). Mathematical description of the responses of simple cortical cells. Journal of the Optical Society of America 70, 1297–1300.CrossRefGoogle ScholarPubMed
Marrocco, R.T. & McClurxin, J.W. (1985). Evidence for spatial structure in cortical input to the monkey lateral geniculate nucleus. Experimental Brain Research 59, 50–56.CrossRefGoogle Scholar
Michotte, A., Thines, G. & Crabbe, G. (1964). Les complements amodaux des structures perceptives. Louvain: Publications Universitaires de Louvain.Google Scholar
Mishkin, M. (1982). A memory system in the monkey. Philosophical Transactions Royal Society B (London) 298, 85–95.Google ScholarPubMed
Mishkin, M. & Appenzeller, T. (1987). The anatomy of memory. Scientific American 256, 80–89.CrossRefGoogle ScholarPubMed
Montero, V.M. (1990). Quantitative immunogold analysis reveals high glutamate levels in synaptic terminals of retino-geniculate cortico-geniculate, and geniculo-cortical axons in the cat. Visual Neuroscience 4, 437–443.CrossRefGoogle ScholarPubMed
Montero, V.M. & Zempel, J. (1985). Evidence for two types of GABA-containing interneurons in the A-laminae of the cat lateral geniculate nucleus: A double-label HRP and GABA-immunocytochemcal study. Experimental Brain Research 60, 603–609.Google ScholarPubMed
Morgan, M.J. & Moulden, B. (1986). The Münsterberg figure and twisted cords. Vision Research 26, 1793–1800.CrossRefGoogle ScholarPubMed
Murphy, P.C. & Sillito, A.M. (1987). Corticofugal influences on the generation of length tuning in the visual pathway. Nature 329, 727–729.CrossRefGoogle ScholarPubMed
Paradiso, M. & Nakayama, K. (1991). Brightness perception and filling-in. Vision Research 31, 1221–1236.CrossRefGoogle ScholarPubMed
Pessoa, L., Mingolla, E. & Neumann, H. (1995). A contrast- and luminance-driven multiscale network model of brightness perception. Visual Research 35, 2201–2233.Google ScholarPubMed
Petzold, L.R. (1983). Automatic selection of methods for solving stiff and non-stiff systems of ordinary differential equations. SIAM Journal of Scientific and Statistical Computing 4, 136–148.CrossRefGoogle Scholar
Pollen, D.A. & Ronner, S.F. (1981). Phase relationships between adjacent simple cells in the visual cortex. Science 212, 1409–1411.CrossRefGoogle ScholarPubMed
Redies, C., Crook, J.M. & Creutzfeldt, O.D. (1986). Neuronal responses to borders with and without luminance gradients in cat visual cortex and dLGN. Experimental Brian Research 61, 469–481.Google Scholar
Robson, J.A. (1983). The morphology of corticofugal axons to the dorsal lateral geniculate nucleus in the cat. Journal of Comparative Neurology 216, 89–103.CrossRefGoogle Scholar
Schiller, P. (1992). The ON and OFF channels of the visual system. Trends in Neuroscience 15, 86–92.CrossRefGoogle ScholarPubMed
Schwartz, E.L., Desimone, R., Albright, T. & Gross, C.G. (1983). Shape recognition and inferior temporal neurons. Proceedings of the National Academy of Sciences of the U.S.A. 80, 5776–5778.CrossRefGoogle ScholarPubMed
Sillito, A.M., Jones, H.E., Gerstein, G.L. & West, D.C. (1994). Feature-linked synchronization of thalamic relay cell firing induced by feedback from the visual cortex. Nature 369, 479–482.CrossRefGoogle ScholarPubMed
Sillito, A.M. & Kemp, J.A. (1983). The influence of GABAergic inhibitory processes on the receptive field structure of X and Y cells in cat dorsal lateral geniculate nucleus (dLGN). Brain Research 277, 63–77.CrossRefGoogle ScholarPubMed
Singer, W. (1977). Control of thalamic transmission by corticofugal and ascending reticular pathways in the visual system. Physiological Review 57, 386–420.CrossRefGoogle ScholarPubMed
Singer, W. (1979). Central-core control of visual-cortex functions. In Neurosciences Fourth Study Program, ed. Schmitt, F.O. et al. , Cambridge, Massachusetts: M.l.T. Press.Google Scholar
Spitzer, H. & Hochstein, S. (1985). A complex-cell receptive field model. Journal of Neurophysiology 33, 1266–1286.CrossRefGoogle Scholar
Stevens, K.A. (1978). Computation of locally parallel structure. Biological Cybernetics 29, 19–28.CrossRefGoogle Scholar
Updyke, B.V. (1975). The patterns of projection of cortical areas 17, 18, and 19 onto the laminae of the dLGN in the cat. Journal of Comparative Neurology 163, 377–396.CrossRefGoogle Scholar
Varela, F.J. & Singer, W. (1987). Neuronal dynamics in the visual corticothalamic pathway revealed through binocular rivalry. Experimental Brain Research 66, 10–20.CrossRefGoogle ScholarPubMed
von der Heydt, R., Peterhans, E. & Baumgartner, G. (1984). Illusory contours and cortical neuron responses. Science 224, 1260–1262.CrossRefGoogle ScholarPubMed
Watanabe, T. & Sato, T. (1989). Effects of luminance contrast on color spreading and illusory contour in the neon color spreading effect. Perception and Psychophysics 45, 427–430.CrossRefGoogle ScholarPubMed
Watanabe, T. & Takeichi, H. (1990). The relation between color spreading and illusory contours. Perception and Psychophysics 47, 457–467.CrossRefGoogle ScholarPubMed
Waxman, A.M., Seibert, M., Bernardon, A.M. & Fay, D.A. (1993). Neural systems for automatic target learning and recognition. The Lincoln Laboratory Journal 6, 77–116.Google Scholar
Weber, A.J., Kalil, R.E. & Behan, M. (1989). Synaptic connections between corticogeniculate axons and interneurons in the dorsal lateral geniculate nucleus of the cat. Journal of Comparative Neurology 289, 156–164.CrossRefGoogle ScholarPubMed
Zeki, . (1983 a). Colour coding in the cerebral cortex: The reaction of cells in monkey visual cortex to wavelengths and colours. Neuroscience 9, 741–765.CrossRefGoogle ScholarPubMed
Zeki, . (1983 b). Colour coding in the cerebral cortex: The responses of wavelength-selective and colour coded cells in monkey visual cortex to changes in wavelength composition. Neuroscience 9, 767–791.CrossRefGoogle ScholarPubMed