DMCA
An evaluation of the use of Multidimensional Scaling for understanding brain connectivity (1994)
| Venue: | Philosophical Transactions of the Royal Society, Series B |
| Citations: | 12 - 2 self |
BibTeX
@ARTICLE{Goodhill94anevaluation,
author = {Geoffrey J. Goodhill and Martin W. Simmen and David J. Willshaw and Buccleuch Place},
title = {An evaluation of the use of Multidimensional Scaling for understanding brain connectivity},
journal = {Philosophical Transactions of the Royal Society, Series B},
year = {1994},
volume = {348},
pages = {265--280}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
A large amount of data is now available about the pattern of connections between brain regions. Computational methods are increasingly relevant for uncovering structure in such datasets. There has been recent interest in the use of Nonmetric Multidimensional Scaling (NMDS) for such analysis (Young, 1992, 1993; Scannell & Young, 1993). NMDS produces a spatial representation of the "dissimilarities" between a number of entities. Normally, it is applied to data matrices containing a large number of levels of dissimilarity, whereas for connectivity data there is a very small number. We address the suitability of NMDS for this case. Systematic numerical studies are presented to evaluate the ability of this method to reconstruct known geometrical configurations from dissimilarity data possessing few levels. In this case there is a strong bias for NMDS to produce annular configurations, whether or not such structure exists in the original data. Using a connectivity dataset derived from the pr...
Keyphrases
multidimensional scaling brain connectivity dissimilarity data annular configuration large amount brain region connectivity data strong bias nonmetric multidimensional scaling systematic numerical study recent interest known geometrical configuration spatial representation original data large number structure exists data matrix small number computational method scannell young connectivity dataset
