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On the analysis of the cat's pattern recognition system

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Abstract

The objective of the paper is to determine in abstract terms the algorithms used by the cat detecting simple patterns and to quantify the contributions of the visual areas 17, 18, 19 for this task. The data incorporated in the algorithm are collected from behavioral experiments where the animals had to distinguish between two patterns. The patterns were superimposed with gaussian noise and the detection probability was measured. The resulting model describes pattern recognition in two steps: first extraction of features and second classification. The test of the validity of the model system was to predict the outcome of similar experiments but with different patterns. With the help of the model it is possible to deccribe the effect of a lesion in parametric form. This in turn gives some hints about the functions of the visual areas 17, 18, 19 for the specific fask, tested in the experiments.

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Authors and Affiliations

  1. Arbeitsgruppe III (Biophysik), Institut für Zoologie, Johannes-Gutenberg-Universität, Mainz, Federal Republic of Germany

    G. Krone, D. Kunz & W. v. Seelen

Authors
  1. G. Krone
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  2. D. Kunz
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  3. W. v. Seelen
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Additional information

The project was supported by DFG Se 251/18

The lesions were made by Prof. Berlucchi, Pisa

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Krone, G., Kunz, D. & Seelen, W.v. On the analysis of the cat's pattern recognition system. Biol. Cybern. 48, 115–124 (1983). https://doi.org/10.1007/BF00344395

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  • DOI: https://doi.org/10.1007/BF00344395

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