Abstract
We propose three high level structural principles of neural networks in the vertebrate visual cortex and discuss some of their computational implications for early vision: a) Lamination, average axonal and dendritic domains, and intrinsic feedback determine the spatio-temporal interactions in cortical processing. Possible applications of the resulting filters include continuous motion perception and the direct measurement of high-level parameters of image flow, b) Retinotopic mapping is an emergent property of massively parallel connections. With a local intrinsic operation in the target area, mapping combines to a space-variant image processing system as would be useful in the analysis of optical flow. c) Further space-variance is brought about by both, discrete (patchy) connections between areas and periodic (columnar) arrangement of specialized neurons within the areas. We present preliminary results on the significance of these principles for neural computation.
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Mallot, H.A. (1989). Why Cortices ? Neural Computation in the Vertebrate Visual System. In: Eckmiller, R., v.d. Malsburg, C. (eds) Neural Computers. Springer Study Edition, vol 41. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83740-1_15
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DOI: https://doi.org/10.1007/978-3-642-83740-1_15
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