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Quantifying neighbourhood preservation in topographic mappings

Proceedings of the 3rd Joint Symposium on Neural Computation, 1996.
Authors: G. Goodhill and S. Finch and T. Sejnowski
Tags: brainconnectivity dimensionalityreduction
Abstract: Mappings that preserve neighbourhood relationships are important in many contexts, from neurobiology to multivariate data analysis. It is important to be clear about precisely what is meant by preserving neighbourhoods. At least three issues have to be addressed: how neighbourhoods are defined, how a perfectly neighbourhood preserving mapping is defined, and how an objective function for measuring discrepancies from perfect neighbourhood preservation is defined. We review several standard methods, and using a simple example mapping problem show that the different assumptions of each lead to non-trivially different answers. We also introduce a particular measure for topographic distortion, which has the form of a quadratic assignment problem. Many previous methods are closely related to this measure, which thus serves to unify disparate approaches.
| BibTeX  
@inproceedings{GoodhillSejnowski1996,
title = {{Quantifying neighbourhood preservation in topographic mappings}},
author = {G. Goodhill and S. Finch and T. Sejnowski},
booktitle = {Proceedings of the 3rd Joint Symposium on Neural Computation},
year = {1996},
abstract = {Mappings that preserve neighbourhood relationships are important in many contexts, from neurobiology to multivariate data analysis. It is important to be clear about precisely what is meant by preserving neighbourhoods. At least three issues have to be addressed: how neighbourhoods are defined, how a perfectly neighbourhood preserving mapping is defined, and how an objective function for measuring discrepancies from perfect neighbourhood preservation is defined. We review several standard methods, and using a simple example mapping problem show that the different assumptions of each lead to non-trivially different answers. We also introduce a particular measure for topographic distortion, which has the form of a quadratic assignment problem. Many previous methods are closely related to this measure, which thus serves to unify disparate approaches. },
keywords = {brainconnectivity dimensionalityreduction }
}