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Precise restoration of cortical orientation maps explained by hebbian dynamics of geniculocortical connections

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1112))

Abstract

It is widely assumed that experience dependence and variability of the individual layout of cortical columns are the hallmarks of activity-dependent self-organization during development. Recent optical imaging studies of visual cortical development seem to indicate a lack of such intinsic variability in visual cortical development. These studies showed that orientation maps which were forced to form independently for the left and right eye exhibited a high degree of similarity in area 18 of cat visual cortex [7, 4]. It has been argued that this result must be viewed are evidence for an innate predetermination of orientation preference if orientation preference is determined by the pattern of geniculocortical connections.

Here we point out that the observed phenomenon can in fact be explained by the activity-dependent development of geniculocortical connections if geometric constraints and retinotopic organization of area 18 are taken into acount. In particular we argue that symmetries, which would lead to a strong variability of the emerging orientation map can be broken by boundary effects and interactions between the orientation preference map and the retinotopic organization. As a consequence independently developing orientation maps should exhibit the same layout in area 18, but not in area 17. Simulations of the formation of orientation columns in narrow areas indeed produce uniquely defined orientation preference maps irrespective of the particular set of stimuli driving the development.

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Christoph von der Malsburg Werner von Seelen Jan C. Vorbrüggen Bernhard Sendhoff

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© 1996 Springer-Verlag Berlin Heidelberg

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Pawelzik, K., Bauer, H.U., Wolf, F., Geisel, T. (1996). Precise restoration of cortical orientation maps explained by hebbian dynamics of geniculocortical connections. In: von der Malsburg, C., von Seelen, W., Vorbrüggen, J.C., Sendhoff, B. (eds) Artificial Neural Networks — ICANN 96. ICANN 1996. Lecture Notes in Computer Science, vol 1112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61510-5_72

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  • DOI: https://doi.org/10.1007/3-540-61510-5_72

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61510-1

  • Online ISBN: 978-3-540-68684-2

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