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Cerebral Cortex Advance Access originally published online on June 13, 2008
Cerebral Cortex 2009 19(3):554-562; doi:10.1093/cercor/bhn105
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© The Author 2008. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org

The Relation between Connection Length and Degree of Connectivity in Young Adults: A DTI Analysis

John D. Lewis1,2, Rebecca J. Theilmann3, Martin I. Sereno4 and Jeanne Townsend2,5

1 Department of Cognitive Science, 2 Research on Aging and Development Laboratory, and, 3 Department of Radiology, University of California-San Diego, La Jolla, CA, 4 Centre for NeuroImaging, Birkbeck-University College London, London, UK, 5 Department of Neurosciences, University of California-San Diego, La Jolla, CA

Address correspondence to John D. Lewis, Department of Cognitive Science, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0515. Email: jdlewis{at}ucsd.edu.

Using diffusion tensor imaging and tractography to detail the patterns of interhemispheric connectivity and to determine the length of the connections, and formulae based on histological results to estimate degree of connectivity, we show that connection length is negatively correlated with degree of connectivity in the normal adult brain. The degree of interhemispheric connectivity—the ratio of interhemispheric connections to total corticocortical projection neurons—was estimated for each of 5 subregions of the corpus callosum in 22 normal males between 20 and 45 years of age (mean 31.68; standard deviation 8.75), and the average length of the longest tracts passing through each point of each subregion was calculated. Regression analyses were used to assess the relation between connection length and the degree of connectivity. Connection length was negatively correlated with degree of connectivity in all 5 subregions, and the regression was significant in 4 of the 5, with an average r2 of 0.255. This is contrasted with previous analyses of the relation between brain size and connectivity, and connection length is shown to be a superior predictor. The results support the hypothesis that cortical networks are optimized to reduce conduction delays and cellular costs.

Key Words: brain scaling • connection length • degree of connectivity • optimal wiring • relative size


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