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Title: Topographic and laminar models for the development and organisation of spatial frequency and orientation in V1
Authors: Palmer, Chris M.
Supervisor(s): Bednar, Jim
Issue Date: 2009
Publisher: The University of Edinburgh
Abstract: Over the past several decades, experimental studies of the organisation of spatial frequency (SF) preference in mammalian visual cortex (V1) have reported a wide variety of conflicting results. A consensus now appears to be emerging that in the superficial layers SF is mapped continuously across the cortical surface. However, other evidence suggests that SF may differ systematically with cortical depth, at least in layer 4, where the magnocellular (M) and parvocellular (P) pathway afferents terminate in different sublaminae. It is not yet clear whether the topographic organisation for SF observed in the superficial layers is maintained throughout the input layers as well, or whether there is a switch from a laminar to a topographic organisation along the vertical dimension in V1. I present results from two alternative self-organising computational models of V1 that receive natural image inputs through multiple SF channels in the LGN, differing in whether they develop laminar or topographic organisation in layer 4. Both models lead to topographic organisation for orientation (OR) and SF preference in upper layers, consistent with current experimental evidence. The results suggest that in either case separate sub-populations of neurons are required to obtain a wide range of SF preference from Hebbian learning of natural images. These models show that a laminar organisation for SF preference can coexist with a topographic, columnar organisation for orientation, and that the columnar organisation for orientation is dependent upon inter-laminar feedback. These results help clarify and explain the wide range of SF results reported in previous studies.
Sponsor(s): Engineering and Physical Sciences Research Council (EPSRC)
Edinburgh Compute and Data Facility (ECDF)
Keywords: spatial frequency
visual cortex
topographic organisation
Appears in Collections:Informatics thesis and dissertation collection

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