Geoffrey Goodhill, Steven Finch, Terrence J. Sejnowski
"Topographic" mappings occur frequently in the brain. A pop(cid:173) ular approach to understanding the structure of such mappings is to map points representing input features in a space of a few dimensions to points in a 2 dimensional space using some self(cid:173) organizing algorithm. We argue that a more general approach may be useful, where similarities between features are not con(cid:173) strained to be geometric distances, and the objective function for topographic matching is chosen explicitly rather than being spec(cid:173) ified implicitly by the self-organizing algorithm. We investigate analytically an example of this more general approach applied to the structure of interdigitated mappings, such as the pattern of ocular dominance columns in primary visual cortex.