Title
Self-organizing maps for visual feature representation based on natural binocular stimuli.
Abstract
We model the stimulus-induced development of the topography of the primary visual cortex. The analysis uses a self-organizing Kohonen model based on high-dimensional coding. It allows us to obtain an arbitrary number of feature maps by defining different operators. Using natural binocular stimuli, we concentrate on discussing the orientation, ocular dominance, and disparity maps. We obtain orientation and ocular dominance maps that agree with essential aspects of biological findings. In contrast to orientation and ocular dominance, not much is known about the cortical representation of disparity. As a result of numerical simulations, we predict substructures of orientation and ocular dominance maps that correspond to disparity maps. In regions of constant orientation, we find a wide range of horizontal disparities to be represented. This points to geometrical relations between orientation, ocular dominance, and disparity maps that might be tested in experiments.
Year
DOI
Venue
2000
10.1007/PL00007968
Biological Cybernetics
Keywords
Field
DocType
Visual Cortex,Arbitrary Number,Visual Feature,Primary Visual Cortex,Feature Representation
Computer vision,Visual cortex,Ocular dominance,Coding (social sciences),Self-organizing map,Operator (computer programming),Artificial intelligence,Stimulus (physiology),Mathematics
Journal
Volume
Issue
ISSN
82
2
0340-1200
Citations 
PageRank 
References 
5
0.60
8
Authors
3
Name
Order
Citations
PageRank
J Wiemer1193.15
T Burwick2649.31
W von Seelen3503140.13