PT  - JOURNAL ARTICLE
AU  - Moo K. Chung
AU  - Jamie L. Hanson
AU  - Nagesh Adluru
AU  - Andrew L. Alexander
AU  - Richard J. Davison
AU  - Seth D. Pollak
TI  - Integrative Structural Brain Network Analysis in Diffusion Tensor Imaging
AID  - 10.1101/129015
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 129015
4099  - http://biorxiv.org/content/early/2017/04/20/129015.1.short
4100  - http://biorxiv.org/content/early/2017/04/20/129015.1.full
AB  - In diffusion tensor imaging, structural connectivity between brain regions is of-ten measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.