Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Self-organizing maps for internal representations

  • 92 Accesses

  • 14 Citations


One of the biological mechanisms that has so far been poorly understood is the ability of the brain to form representations of primary sensory experiences at increasingly higher levels of abstraction. At many lower perceptual levels, sensory information first becomes represented in topographically ordered sensory maps. In these maps neurons become tuned in a regular manner to simple stimulus features, such as amplitude, frequency, or direction of sound. In this paper it is shown that a model, originally devised by Kohonen for the understanding of the self-organized formation of such “lower-level maps,” can also explain the formation of more abstract maps, such as adaptive maps for use in motor control, or maps in which, during a learning stage, the neurons become tuned in an orderly fashion to aspects of the semantic meaning of words. The actual presence of such maps in the brain is speculative at present, but many maps of simpler type have been found. It is argued that the process of the adaptive formation of maps may offer a way to a more unified understanding of many aspects of information processing in the brain.

This is a preview of subscription content, log in to check access.


  1. Anderson, J. A., & Rosenfeld, E. (Eds.) (1989).Neurocomputing — foundations of research. Cambridge, MA: MIT Press.

  2. Caramazza, A. (1988). Some aspects of language processing revealed through the analysis of acquired aphasia: The lexical system.Annual Review of Neuroscience, 11, 395–421.

  3. Cottrell, M., & Fort, J. C. (1986). A stochastic model of retinotopy: A self-organizing process.Biological Cybernetics, 53, 405–411.

  4. Essen, D. van, (1985). Functional organization of primate visual cortex. In A. Peters & E. G. Jones (Eds.),Cerebral cortex (Vol. 3, pp. 259–329). New York: Plenum Press.

  5. Harris, W. A. (1986). Learned topography: The eye instructs the ear.Trends in Neuroscience e,g, 97 – 99.

  6. Hasselmo, M. E., Rolls, E. T., & Baylis, G. C. (1989). The role of expression and identity in the face selective neurons in the temporal visual cortex of the monkey.Behavioral and Brain Research, 32, 203–218.

  7. Hart, J., Berndt, R. S., & Caramazza, A. (1985). Category-specific naming deficit following cerebral infarction.Nature, 316, 439–440.

  8. Hubel, D. H., & Wiesel, T. N. (1959). Receptive fields of single neurons in the cat's striate cortex.Journal of Physiology, 148, 574–591.

  9. Kaas, J. H., Nelson, R. J., Sur, M., Lin, C. S., & Merzenich, M. M. (1979). Multiple representations of the body within the primary somatosensory cortex of primates.Science, 204, 521–523.

  10. King, A. J., Hutchings, M. E., Moore, D. R., & Blakemore, C. (1988). Developmental plasticity in the visual and auditory representations in the mammalian superior colliculus.Nature, 332, 73–76.

  11. Knudsen, E. I., du Lac, S., & Esterly, S. D. (1987). Computational maps in the brain.Annual Review of Neuroscience, 10, 41–65.

  12. Kohonen, T. (1982a). Self-organized formation of topologically correct feature maps.Biological Cybernetics, 43, 59–69.

  13. Kohonen, T. (1982b). Analysis of a simple self-organizing process.Biological Cybernetics, 44, 135–140.

  14. Kohonen, T. (1982c). Clustering, taxonomy and topological maps of patterns.Proceedings of the 6th International Conference of Pattern Recognition, Munich, pp. 114 – 128.

  15. Kohonen, T. (1984). Self-organization and associative memory. Springer Series in Information Sciences, 8. Heidelberg: Springer.

  16. Kohonen, T., Mäkisara, K., & Saramäki, T. (1984). Phonotopic maps —insightful representation of phonological features for speech recognition.Proceedings of the 7th International Conference of Pattern Recognition, Montreal, pp. 182 – 185.

  17. Lemon, R. (1988). The output map of the primate motor cortex.Trends in Neuroscience, 11, 501–506.

  18. Malsburg, C. von der, & Willshaw, D. J. (1977). How to label nerve cells so that they can interconnect in an ordered fashion.Proceedings of the National Academy of Sciences, USA, 74, 5176–5178.

  19. Martinetz, T., Ritter, H., & Schulten, K. (1989a). Three-dimensional neural net for learning visuomotor-coordination of a robot arm.IEEE-Transactions on Neural Networks, 1, 131–136.

  20. Martinetz, T., Ritter, H., & Schulten, K. (1989b). Learning of visuomotor-coordination of a robot arm with redundant degrees of freedom. In R. Eckmiller & C. v. d. Malsburg (Eds.),Parallel processing in neural systems and computers (pp. 431–434). Amsterdam: North Holland.

  21. Merzenich, M. M., Nelson, R. J., Stryker, M. P., Cynader, M. S., Schoppmann, A., & Zook, J. M. (1984). Somatosensory cortical map changes following digit amputation in adult monkeys.Journal of Comparative Neurology, 224, 591–605.

  22. Obermayer, K., Ritter, H., & Schulten, K. (1989). Large-scale simulation of a self-organizing neural network: Formation of a somatotopic map. In R. Eckmiller & C. v. d. Malsburg (Eds.). In Parallel processing in neural systems and computers (pp. 71–74). Amsterdam: North-Holland.

  23. Ojemann, G. A. (1983). Brain organization for language from the perspective of electrical stimulation mapping.Behavioural and Brain Sciences, 6, 189–230.

  24. O'Leary, D. D. M. (1989). Do cortical areas emerge from a protocortex?Trends in Neuroscience, 12, 400–406.

  25. Rauschecker, J. P., & Singer, W. (1981). The effects of early visual experience on the cat's visual cortex and their possible explanation by Hebb-synapses.Journal of Physiology, 310, 215–239.

  26. Ritter, H., & Schulten, K. (1987). Extending Kohonen's self-organizing mapping algorithm to learn ballistic movements. In R. Eckmiller & C. von der Malsburg (Eds.),Neural Computers (pp. 393–406). Berlin, Heidelberg, New York: Springer.

  27. Ritter, H., & Schulten, K. (1988). Kohonen's self-organizing maps: Exploring their computational capabilities.IEEE ICNN 88 Conference, San Diego, I, 109–116.

  28. Ritter, H. (1988). Selbstorganisierende Neuronale Karten. Thesis, Technical University, Munich.

  29. Ritter, H., & Kohonen, T. (1989a). Self-organizing semantic maps.Biological Cybernetics, 61, 241–254.

  30. Ritter, H., & Kohonen, T. (1989b). Learning “semantotopic maps” from context.Proceedings of the International Joint Conference on Neural Networks IJCNN-90, Washington D.C., I, 23 – 26.

  31. Ritter, H., Martinetz, T., & Schulten, K. (1989a). Topology conserving maps for learning visuomotor-coordination.Neural Networks, 2, 159–168.

  32. Ritter, H., Martinetz, T., & Schulten, K. (1989b). Topology conserving maps for motor control. In L. Personnaz & G. Dreyfus (Eds.),In Neural Networks. From models to applications, (pp. 579–591). Paris: I,D,S,E,T.

  33. Ritter, H., & Schulten, K. (1989). Convergence properties of Kohonen's topology conserving maps: Fluctuations, stability and dimension selection.Biological Cybernetics, 60, 59–71.

  34. Rumelhart, D. E., & McClelland, D. E. (1986).Parallel distributed processing, Vols. 1 – 2. Cambridge, MA: MIT Press.

  35. Sparks, D. L., & Nelson, J. S. (1987). Sensory and motor maps in the mammalian superior colliculus.Trends in Neuroscience, 10, 312–317.

  36. Suga, N., & O'Neill, W. E. (1979). Neural axis representing target range in the auditory cortex of the Mustache Bat.Science, 206, 351–353.

  37. Willshaw, D. J., & Malsburg, C. von der (1976). How patterned neural connections can be set up by self-organization.Proceedings of the Royal Society, London B, 194, 431–445.

Download references

Author information

Additional information

On leave to the University of Bielefeld, Department of Computer Science, D-4800 Bielefeld, Federal Republic of Germany.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Ritter, H. Self-organizing maps for internal representations. Psychol. Res 52, 128–136 (1990). https://doi.org/10.1007/BF00877520

Download citation


  • Sensory Experience
  • Stimulus Feature
  • Simple Type
  • Semantic Meaning
  • Learning Stage