Neural Mechanisms for the Robust Representation of Junctions

Neural Computation

Volumn 16, Issue 5, 2004, Pages 1013-1037

  Hansen, Thorsten ^a   Neumann, Heiko ^b  

^a JUSTUS LIEBIG UNIVERSITY   (Germany)

^b UNIVERSITY OF ULM   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BIOLOGICAL MODEL; METHODOLOGY; ORIENTATION; PHOTOSTIMULATION; PHYSIOLOGY;

MODELS, NEUROLOGICAL; ORIENTATION; PHOTIC STIMULATION;

EID: 1842632414     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976604773135087     Document Type: Article

References (94)

1. Adelson, E. H. (1993). Perceptual organization and the judgment of brightness. Science, 262(5142), 2042-2044.
2. Adelson, E. H. (2000). Lightness perception and lightness illusions. In M. S. Gazzaniga (Ed.), The new cognitive neurosciences (2nd ed., pp. 339-351). Cam bridge, MA: MIT Press.
3. Amir, Y., Harel, M., & Malach, R. (1993). Cortical hierarchy reflected in the organization of intrinsic connections in the macaque monkey visual cortex. J. Comp. Neurol., 334, 19-46.
4. Attneave, F. (1954). Some informational aspects of visual perception. Psychol. Rev., 61(3), 183-193.
5. Biederman, I. (1985). Human image understanding: Recent research and a the ory. Computer Vision, Graphics, Image Proc., 32(1), 29-73.
6. Biederman, I. (1987). Recognition-by-components: A theory of human image understanding. Psychol. Rev., 94(2), 115-147.
7. Bolz, J., & Gilbert, C. D. (1986). Generation of end-inhibition in the visual cortex via interlaminar connections. Nature, 320(6060), 362-365.
8. Bolz, J., Gilbert, C. D., & Wiesel, T. N. (1989). Pharmacological analysis of cortical circuitry. Trends Neurosci, 12(8), 292-296.
9. Borg-Graham, L. J., Monier, C., & Frégnac, Y. (1998). Visual input evokes tran sient and strong shunting inhibition in visual cortical neurons. Nature, 393, 369-373.
10. Bosking, W. H., Zhang, Y., Schofield, B., & Fitzpatrick, D. (1997). Orientation selectivity and the arrangement of horizontal connections in tree shrew striate cortex. J. Neurosci, 17(6), 2112-2127.
11. Carandini, M., & Heeger, D. J. (1994). Summation and division by neurons in primate visual cortex. Science, 264(5163), 1333-1336.
12. Carpenter, G. A., & Grossberg, S. (1988). The ART of adaptive pattern recognition by a self-organizing neural network. Computer, 21, 77-88.
13. Coelho, C., Heller, A., Mundy, J. L., Forsyth, D., & Zisserman, A. (1991). An experimental evaluation of projective invariants. In Proc. DARPA-ESPRIT Workshop on Applications of Invariants in Computer Vision, Reykjavik, Iceland (pp. 273-293).
14. Das, A., & Gilbert, C. D. (1999). Topography of contextual modulations mediated by short-range interactions in primary visual cortex. Nature, 399, 655-661.
15. David, C., & Zucker, S. W. (1990). Potentials, valleys, and dynamic global cov erings. Int. J. Comput. Vision, 5, 219-238.
16. Dayan, P., & Abbott, L. F. (2001). Theoretical neuroscience. Cambridge, MA: MIT Press.
17. DeAngelis, G. C., Freeman, R. D., & Ohzawa, I. (1994). Length and width tuning of neurons in the cat's primary visual cortex. J. Neurophysiol, 71 (1), 347-374.
18. Deriche, R., & Giraudon, G. (1990). Accurate corner detection: An analytical study. In Proc. 3rd Int. Conf. Computer Vision (pp. 66-70). Los Alamitos, CA: IEEE Computer Society Press.
19. Douglas, R. J., & Martin, K. A. C. (1990). Control of neuronal output by inhibition at the axon initial segment. Neural Comput., 2(3), 283-292.
20. Fechner, G. T. (1889). Elemente der psychophysik. Leipzig: Breitkopf & Härtel.
21. Field, D. J., Hayes, A., & Hess, R. F. (1993). Contour integration by the human visual system: Evidence for a local "association field." Vision Res., 33(2), 173-193.
22. Furman, G. (1965). Comparison of models for subtractive and shunting lateral-inhibition in receptor-neuron fields. Kybernetik, 2, 257-274.
23. Gilbert, C. D., & Wiesel, T. N. (1983). Clustered intrinsic connections in cat visual cortex. J. Neurosci., 3, 1116-1133.
24. Gilbert, C. D., & Wiesel, T. N. (1989). Columnar specificity of intrinsic horizontal and corticocortical connections in cat visual cortex. J. Neurosci., 9(7), 2432-2442.
25. Green, D. M., & Swets, J. A. (1974). Signal detection theory and psychophysics. Huntington, NY: Krieger.
26. Grossberg, S. (1970). Neural pattern discrimination. J. Theoret. Biol., 27, 291-337.
27. Grossberg, S., & Mingolla, E. (1985a). Neural dynamics of form perception: Boundary completion, illusory figures, and neon color spreading. Psychol. Rev., 92, 173-211.
28. Grossberg, S., & Mingolla, E. (1985b). Neural dynamics of perceptual group ing: Textures, boundaries, and emergent segmentation. Percept. Psychophys., 38:141-171.
29. Grossberg, S., & Raizada, R. D. S. (2000). Contrast-sensitive perceptual grouping and object-based attention in the laminar circuits of primary visual cortex. Vision Res., 40(10), 1413-1432.
30. Hansen, T. (2003). A neural model of early vision: Contrast, contours, cor ners and surfaces. Doctoral dissertation, Ulm University. Available on-line: http://vts.uni-ulm.de/query/longview.meta.asp?document.id=3022.
31. Hansen, T., & Neumann, H. (1999). A model of V1 visual contrast processing utilizing long-range connections and recurrent interactions. In Proc. 9 Int. Conf. on Artificial Neural Networks (ICANN99) (pp. 61-66). London: Institution of Electrical Engineers.
32. Hansen, T., & Neumann, H. (2001). Neural mechanisms for representing surface and contour features. In S. Wermter, J. Austin, & D. Willshaw (Eds.), Emergent neural computational architectures based on neuroscience (pp. 139-153). Berlin: Springer-Verlag.
33. Hansen, T., & Neumann, H. (2002). A biologically motivated scheme for ro bust junction detection. In H. H. Bülthoff, S.-W. Lee, T. A. Poggio, & C. Wallraven (Eds.), Biologically motivated computer vision (pp. 16-26). Berlin: Springer-Verlag.
34. Hansen, T., Sepp, W., & Neumann, H. (2001). Recurrent long-range interactions in early vision. In S. Wermter, J. Austin, & D. Willshaw (Eds.), Emerging neural architectures based on neuroscience (pp. 127-138). Berlin: Springer-Verlag.
35. Harris, C. J. (1987). Determination of ego-motion from matched points. In Proc. Third Alvey Vision Conference (pp. 189-192). Cambridge, UK.
36. Heitger, F., Rosenthaler, L., von der Heydt, R., Peterhans, E., & Kübler, O. (1992). Simulation of neural contour mechanisms: From simple to end-stopped cells. Vision Res., 32(5), 963-981.
37. Heitger, F., von der Heydt, R., Peterhans, E., Rosenthaler, L., & Kübler, O. (1998). Simulation of neural contour mechanisms: Representing anomalous con tours. Image Vision Comput., 16, 407-421.
38. Heyden, A., & Rohr, K. (1996). Evaluation of corner extraction schemes using invariance methods. In Proc. 13th Int. Conf. Pattern Recognition, Vienna, Austria (Vol. 1, pp. 895-899). Los Alamitos, CA: IEEE Computer Society Press.
39. Hinton, G. E. (1992). How neural networks learn from experience. Sci. Am., 267(3), 144-151.
40. Hirsch, J. A., & Gilbert, C. D. (1991). Synaptic physiology of horizontal connec tions in the cat's visual cortex. J. Neurosci., 11(6), 1800-1809.
41. Hodgkin, A. L. (1964). The conduction of nervous impulses. Liverpool: Liverpool University Press.
42. Holt, G. R., & Koch, C. (1997). Shunting inhibition does not have a divisive effect on firing rates. Neural Comput., 9(5), 1001-1013.
43. Hubel, D. H., & Wiesel, T. N. (1968). Receptive fields and functional architecture of monkey striate cortex. J. Physiol., 195, 215-243.
44. Huffman, D. A. (1971). Impossible objects as nonsense sentences. In B. Meltzer & D. Michic (Eds.), Machine intelligence 6 (pp. 295-323). Edinburgh: Edinburgh University Press.
45. Hupé, J. M., James, A. C., Payne, B. R., Lomber, S. G., Girard, P., & Bullier, J. (1998). Cortical feedback improves discrimination between figure and background by V1, V2 and V3 neurons. Nature, 394, 784-787.
46. Kapadia, M. K., Ito, M., Gilbert, C. D., & Westheimer, G. (1995). Improvement in visual sensitivity by changes in local context: Parallel studies in human observers and in V1 of alert monkeys. Neuron, 15(4), 843-856.
47. Kapadia, M. K., Westheimer, G., & Gilbert, C. D. (2000). Spatial distribution of contextual interactions in primary visual cortex and in visual perception. J. Neurophysiol., 84(4), 2048-2062.
48. Kisvarday, Z. F., Kim, D. S., Eysel, U. T., & Bonhoeffer, T. (1994). Relationship between lateral inhibitory connections and the topography of the orientation map in cat visual cortex. Europ. J. Neurosci., 6(10), 1619-1632.
49. Lamme, V. A. F. (1995). The neurophysiology of figure-ground segregation in primary visual cortex. J. Neurosci., 15(2), 1605-1615.
50. Levine, D. S. (2000). Introduction to neural and cognitive modeling (2nd ed.). Mahwah, NJ: Erlbaum.
51. Li, Z. (1998). A neural model of contour integration in the primary visual cortex. Neural Comput., 10(4), 903-940.
52. Li, Z. (1999). Pre-attentive segmentation in the primary visual cortex. Spat. Vis., 13, 25-50.
53. Li, Z. (2001). Computational design and nonlinear dynamics of a recurrent network model of the primary visual cortex. Neural Comput., 13(8), 1749-1780.
54. Lindeberg, T. (1998). Feature detection with automatic scale selection. Int. J. Comput. Vision, 30(2), 77-116.
55. McDermott, J. H. (2001). Some experiments on junctions in real images. Unpub lished master's thesis, University College London. Available on-line: http:// persci.mti.edu/~jmcderm.
56. McDermott, J. H. (2002). Psychophysics with junctions in real images. J. Vis., 2(7), 131a.
57. McLaughlin, D., Shapley, R., Shelley, M. J., & Wielaard, D. J. (2000). A neural network model of macaque primary visual cortex (V1): Orientation selectiv ity and dynamics in the input layer 4Cα. Proc. Natl Acad. Sci. USA, 97(14), 8087-8092.
58. Metelli, F. (1974). The perception of transparency. Sci. Am., 230(4), 90-98.
59. Michaelis, M. (1997). Low level image processing using steerable filters. Unpublished doctoral dissertation, Christian-Albrechts-Universität Kiel.
60. Mitchell, S. J., & Silver, R. A. (2003). Shunting inhibition modulates neuronal gain during synaptic excitation. Neuron, 38(3), 433-445.
61. Mokhtarian, F., & Suomela, R. (1998). Robust image corner detection through curvature scale space. IEEE Trans. Pattern Anal. Mach. Intell., 20(12), 1376-1381.
62. Mumford, D. (1991). On the computational architecture of the neocortex II: The role of cortico-cortical loops. Biol Cybern., 65, 241-251.
63. Neumann, H., & Mingolla, E. (2001). Computational neural models of spatial integration and perceptual grouping. In T. F. Shipley & P. J. Kellman (Eds.), From fragments to objects: Segmentation and grouping in vision (pp. 353-400). Amsterdam: Elsevier Science.
64. Neumann, H., & Sepp, W. (1999). Recurrent V1-V2 interaction in early visual boundary processing. Biol. Cybern., 81, 425-444.
65. Oram, M. W., Földiàk, P., Perret, D. I., & Sengpiel, F. (1998). The "ideal homuncu lus": Decoding neural population signals. Trends Neurosci., 21(6), 259-265.
66. Parent, P., & Zucker, S. W. (1989). Trace inference, curvature consistency, and curve detection. IEEE Trans. Pattern Anal. Mach. Intell., 11(8), 823-839.
67. Parida, L., & Geiger, D. (1998). Junctions: Detection, classification, and recon struction. IEEE Trans. Pattern Anal. Mach. Intell., 20(7), 687-698.
68. Pasupathy, A., & Connor, C. E. (1999). Responses to contour features in macaque area V4. J. Neurophysiol., 82(5), 2490-2502.
69. Pasupathy, A., & Connor, C. E. (2001). Shape representation in area V4: Position-specific tuning for boundary conformation. J. Neurophysiol., 86(5), 2505-2519.
70. Polat, U., & Sagi, D. (1993). Lateral interactions between spatial channels: Sup pression and facilitation revealed by lateral masking experiments. Vision Res., 33(7), 993-999.
71. Polat, U., & Sagi, D. (1994). The architecture of perceptual spatial interactions. Vision Res., 34(1), 73-78.
72. Pouget, A., Dayan, P., & Zemel, R. (2000). Information processing with popula tion codes. Nat. Rev. Neurosci., 1(2), 125-132.
73. Prescott, S. A., & Koninck, Y. D. (2003). Gain control of firing rate by shunting inhibition: Roles of synaptic noise and dendritic saturation. Proc. Natl Acad. Sci. USA, 100(4), 2076-2081.
74. Pugh, M. C., Ringach, D. L., Shapley, R., & Shelley, M. J. (2000). Computational modeling of orientation tuning dynamics in monkey primary visual cortex. J. Comput. Neurosci., 8(2), 143-159.
75. Ringach, D. L., Hawken, M. J., & Shapley, R. (1997). Dynamics of orientation tuning in macaque primary visual cortex. Nature, 387, 281-284.
76. Rockland, K. S., & Lund, J. S. (1983). Intrinsic laminar lattice connections in primate visual cortex. J. Comp. Neurol., 216, 303-318.
77. Rohr, K. (1994). Localization properties of direct corner detectors. J. Math. Imag. Vision, 4, 139-150.
78. Rubin, N. (2001). The role of junctions in surface completion and contour match ing. Perception, 30(3), 339-366.
79. Salin, P.-A., & Bullier, J. (1995). Corticocortical connections in the visual system: Structure and function. Physiol. Rev., 75(1), 107-154.
80. Sandell, J. H., & Schiller, P. H. (1982). Effect of cooling area 18 on striate cortex cells in the squirrel monkey. J. Neurophysiol., 48(1), 38-48.
81. Schmid, C., Mohr, R., & Bauckhage, C. (2000). Evaluation of interest point detectors. Int. J. Comput. Vision, 37(2), 151-172.
82. Schmidt, K. E., Goebel, R., Löwel, S., & Singer, W. (1997). The perceptual group ing criterion of collinearity is reflected by anisotropies of connections in the primary visual cortex. Europ. J. Neurosci., 9, 1083-1089.
83. Seung, H. S., & Sompolinsky, H. (1993). Simple models for reading neuronal population codes. Proc. Natl Acad. Sci. USA, 90(22), 10749-10753.
84. Sinha, P., & Adelson, E. H. (1993). Recovering reflectance in a world of painted polyhedra. In Proc. Fourth International Conference on Computer Vision (ICCV 93), Berlin, Germany (pp. 156-163). New York: IEEE.
85. Smith, S., & Brady, J. (1997). SUSAN - a new approach to low level image processing. Int. J. Comput. Vision, 23(1), 45-78.
86. Todorović, D. (1997). Lightness and junctions. Perception, 26(4), 379-394.
87. van Hateren, J. H., & van der Schaaf, A. (1998). Independent component filters of natural images compared with simple cells in primary visual cortex. Proc. R. Soc. London (B), 265(1394), 359-366.
88. Vogels, R. (1990). Population coding of stimulus orientation by striate cortical cells. Biol. Cybern., 64, 25-31.
89. Weber, E. H. (1905). Tastsinn und Gemeingefühl. Handwörterbuch der Physiologie. Leipzig: Engelmann.
90. Würtz, R. P., & Lourens, T. (2000). Corner detection in color images through a multiscale combination of end-stopped cortical cells. Image Vision Comput., 18(6-7), 531-541.
91. Yen, S.-C, & Finkel, L. H. (1998). Extraction of perceptually salient contours by striate cortical networks. Vision Res., 38(5), 719-741.
92. Zemel, R. S., Dayan, P., & Pouget, A. (1998). Probabilistic interpretation of population codes. Neural Comput., 10(2), 403-430.
93. Zipser, K., Lamme, V. A. F., & Schiller, P. H. (1996). Contextual modulation in primary visual cortex. J. Neurosci., 16(22), 7376-7389.
94. Zucker, S. W., Dobbins, A., & Iverson, L. A. (1989). Two stages of curve detection suggest two styles of visual computation. Neural Comput., 1, 68-81.