A network model for the emergence of orientation maps and local lateral circuits

  • Thomas Burger
  • Elmar W. Lang
Plasticity Phenomena (Maturing, Learning & Memory)
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1606)


We present a nonlinear, recurrent neural network model of the primary visual cortex with separate ON/OFF-pathways and modifiable afferent as well as intracortical synaptic couplings. Orientation maps emerge driven by random input stimuli. Lateral coupling structures self-organize into DOG profiles under the influence of pronounced emerging cortical activity blobs. The model’s architecture and features are, compared with former models, well justified neurobiologically.


Cortical Neuron Receptive Field Primary Visual Cortex Ocular Dominance Lateral Coupling 
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  1. 1.
    Blasdel, G. G.: Differential imaging of ocular dominance and orientation selectivity in monkey striate cortex. J. Neurosci. 12 (1992) 3115–38Google Scholar
  2. 2.
    Bonhoeffer, T., Grinvald, A.: Iso-orientation domains in cat visual cortex are arranged in pinwheel-like patterns. Nature 353 (1991) 429–31CrossRefGoogle Scholar
  3. 3.
    Braitenberg V, Schütz, A.: Anatomy of the cortex: statistics and geometry. (New York, Berlin, Heidelberg: Springer) (1991)CrossRefGoogle Scholar
  4. 4.
    Burger, T., Kussinger, M., Ziegaus, C., Lang, E. W.: Emergence of orientation maps in area 17 of the cerebral cortex: A correlation-based model with afferent and lateral plasticity of synaptical weights and real input patterns. Proceedings of the 25th Göttingen Neurobiology Conference 1997, Ed. Elsner, N., Wässle, H. (Stuttgart, Germany: Georg Thieme Verlag) (1997)Google Scholar
  5. 5.
    Burger, T., Lang, E. W.: A CBL network model with intracortical plasticity and natural image stimuli. Lecture Notes in Computer Science 1327 (1997) 225–30CrossRefGoogle Scholar
  6. 6.
    Burger, T., Lang, E. W.: An incremental Hebbian learning model of the primary visual cortex with lateral plasticity and real input patterns. Z. Naturforsch. C (1998) (in press)Google Scholar
  7. 7.
    Burger, T., Lang, E. W.: A new model of the visual cortex with lateral plasticity for the emergence of orientation maps. Biol. Cybern. (submitted)Google Scholar
  8. 8.
    Callaway, E. M., Katz, L. C.: Emergence and refinement of clustered horizontal connections in cat striate cortex. J. Neurosci. 10 (1990) 1134–53.Google Scholar
  9. 9.
    Crair, M. C., Deda, C. G., Stryker, M. P.: The role of visual experience in the development of columns in cat visual cortex. Science 279 (1998) 566–70CrossRefGoogle Scholar
  10. 10.
    Field, D. J., Tolhurst, D. J.: The structure and symmetry of simple-cell receptivefield profiles in the cat’s visual cortex. Proc. R. Soc. Lond. B 228 (1986) 379–400CrossRefGoogle Scholar
  11. 11.
    Gilbert, C. D., Hirsch, J. A., Wiesel T. N.: Lateral interactions in visual cortex. Cold Spring Harbor Symposia on Quantitative Biology 55 (1990) 663–77CrossRefGoogle Scholar
  12. 12.
    Gilbert, C. D., Wiesel, T. N.: Columnar specificity of intrinsic horizontal and corticocortical connections in cat visual cortex. J. Neurosci. 9 (1989) 2432–42Google Scholar
  13. 13.
    Grinvald, A., Frostig, R. D., Lieke, E., Hildesheim, R.: Optical imaging of neuronal activity. Physiol. Rev. 68 (1988) 1285–366Google Scholar
  14. 14.
    Hubel, D. H., Wiesel, T. N.: Functional architecture of macaque monkey visual cortex. Proc. R. Soc. Lond. B 198 (1977) 1–59CrossRefGoogle Scholar
  15. 15.
    Kandel, E. R., Schwartz, J. H., Jessell, T. M. (eds.): Essentials of neural science and behavior. (Norwalk: Appleton & Lange) (1995)Google Scholar
  16. 16.
    Katz, L. C., Callaway, E. M.: Development of local circuits in mammalian visual cortex. Ann. Rev. Neurosci. 15 (1992) 31–56CrossRefGoogle Scholar
  17. 17.
    Katz, L. C., Gilbert, C. D., Wiesel, T. N.: Local circuits and ocular dominance columns in monkey striate cortex. J. Neurosci. 9 (1989) 1389–99Google Scholar
  18. 18.
    Linsker, R.: From basic networks principles to neural architecture (series). Proc. Natl. Sci. 83 (1986) 7508–12, 8390-4, 8779–83CrossRefGoogle Scholar
  19. 19.
    Linsker, R.: Designing a sensory processing system: what can be learned from principal component analysis? Proc. of the Int. Joint Conf. on Neural Networks (IJCNN, Washington (DC), USA) (1990)Google Scholar
  20. 20.
    Lund, J. S., Yoshioka, T., Levitt, J. B.: Substrates for interlaminar connections in area V1 of macaque monkey cerevral cortex. Cerebral Cortex 10 (1994) 37–60CrossRefGoogle Scholar
  21. 21.
    Malsburg, C. von der: Self-organization of orientation sensitivity cells in the striate cortex. Kybernetik 14 (1973) 85–100CrossRefGoogle Scholar
  22. 22.
    Miller, K. D.: A model for the development of simple cell receptive fields and the ordered arrangement of orientation columns through activity-dependent competition between ON-and OFF-center inputs. J. Neurosci. 14 (1994) 409–41Google Scholar
  23. 23.
    Miller, K. D.: Synaptic economics: competition and cooperation in synaptic plasticity. Neuron 17 (1996) 367–70CrossRefGoogle Scholar
  24. 24.
    Obermayer, K., Blasdel, G. G.: Singularities in primate orientation maps. Neural Comput. 9 (1997) 555–75CrossRefGoogle Scholar
  25. 25.
    Pape, H. C., Eysel, U. T.: Binocular interactions in the lateral geniculate nucleus of the cat: gabaergic inhibition reduced by dominant afferent activity. Exp. Brain Res. 61 (1986) 265–71CrossRefGoogle Scholar
  26. 26.
    Piepenbrock, C., Ritter, H., Obermayer, K.: Cortical map development driven by spontaneous retinal activity waves. Lecture Notes in Computer Science 1112 (1996) 427–32CrossRefGoogle Scholar
  27. 27.
    Sirosh, J., Miikkulainen, R.: Cooperative self-organization of afferent and lateral connections in cortical maps. Biol. Cybern. 71 (1994) 65–78CrossRefzbMATHGoogle Scholar
  28. 28.
    Sirosh, J., Miikkulainen, R.: Topographic receptive fields and patterned lateral interaction in a self-organization model of the primary visual cortex. Neural Computation 9 (1997) 577–94CrossRefGoogle Scholar
  29. 29.
    Somers, D. C., Nelson, S. B., Sur, M.: An emergent model of orientation selectivity in cat visual cortical simple cells. J. Neurosci. 15 (1995) 5448–65zbMATHGoogle Scholar
  30. 30.
    Stetter, M., Lang, E. W., Müller, A.: Emergence of orientation selective simple cells simulated in deterministic and stochastic neural networks. Biol. Cybern. 68 (1993) 465–476CrossRefzbMATHGoogle Scholar
  31. 31.
    Stetter, M., Müller, A., Lang, E. W.: Neural network model for the coordinated formation of orientation preference and orientation selectivity maps. Phys. Rev. E 50 (1994) 4167–81CrossRefGoogle Scholar
  32. 32.
    Stetter, M., Kussinger, M., Schels, A., Seeger E., Lang, E. W.: Self-organization of cortical receptive fields and columnar structures in a Hebb-trained neural network. Lecture Notes in Computer Science 930 (1995) 37–44CrossRefGoogle Scholar
  33. 33.
    Swindale, N. V.: Orientation tuning curves: empirical description and estimation of parameters. Biol. Cybern. 78 (1998) 45–56CrossRefzbMATHGoogle Scholar
  34. 34.
    Weliky, M., Katz, L. C.: Disruption of orientation tuning in visual cortex by artificially correlated neuronal activity. Nature 386 (1997) 680–5CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Thomas Burger
    • 1
  • Elmar W. Lang
    • 1
  1. 1.Institut für Biophysik und physikalische BiochemieUniversität RegensburgRegensburgGermany

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