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International Conference on Artificial Neural Networks

ICANN 1993: ICANN ’93 pp 111–114Cite as

A Neural Network Model for Spatial Information Representation

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Abstract

In this paper, we propose a neural network model that forms a two-dimensional spatial relation map self-organizingly. Cues for spatial relations between objects are given by efference copy signals of saccadic eye movements. The model is able to code the relative positions of objects existing simultaneously in the visual field in spite of its simple structure. The model was simulated on a computer to be shown to have the desired behavior.

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References

  1. For example, Hartman G. (1992) Motion Induced Transformations of Spatial Representations: Mapping 3D onto 2D. Neural Networks, Vol. 5, pp.823–834

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  2. Hirahara M., Nagano T. (1992) A Neural Network for Fixation Point Selection Based on Spatial Knowledge. Artificial Neural Networks 2, pp. 903–906

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  3. Spoehr K. T., Lehmkule S. W. (1982) Visual Information Processing, pp.263–267, W. H. Freeman.

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  4. Pitts W. H., McCulloch W. S. (1947) How we know universals: The perception of auditory and visual forms. Bull. Math. Biophys. 9, pp. 127–147

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  5. Isabelle Otto, et. al. (1992) Direct and Indirect Cooperation between Temporal and Parietal Networks for Invariant Visual Recognition. J. Cog. Neurosci., Vol.4, No.1, pp.35–57

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Author information

Authors and Affiliations

  1. Department of Industrial and System Engineering College of Engineering, Hosei University, 3-7-2, Kajino-cho, Koganei, Tokyo, 184, Japan

    Ryuta Hosaka & Takashi Nagano

Authors
  1. Ryuta Hosaka
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  2. Takashi Nagano
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Editor information

Editors and Affiliations

  1. Dutch Foundation for Neural Networks, University of Nijmegen, Geert Grooteplein 21, 6525 EZ, Nijmegen, The Netherlands

    Stan Gielen  & Bert Kappen  & 

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© 1993 Springer-Verlag London Limited

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Cite this paper

Hosaka, R., Nagano, T. (1993). A Neural Network Model for Spatial Information Representation. In: Gielen, S., Kappen, B. (eds) ICANN ’93. ICANN 1993. Springer, London. https://doi.org/10.1007/978-1-4471-2063-6_25

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  • DOI: https://doi.org/10.1007/978-1-4471-2063-6_25

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  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-19839-0

  • Online ISBN: 978-1-4471-2063-6

  • eBook Packages: Springer Book Archive

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