| Literature DB >> 22903354 |
Emily L Dennis1, Neda Jahanshad, Arthur W Toga, Kori Johnson, Katie L McMahon, Greig I de Zubicaray, Nicholas G Martin, Ian B Hickie, Margaret J Wright, Paul M Thompson.
Abstract
Graph theory can be applied to matrices that represent the brain's anatomical connections, to better understand global properties of anatomical networks, such as their clustering, efficiency and "small-world" topology. Network analysis is popular in adult studies of connectivity, but only one study - in just 30 subjects - has examined how network measures change as the brain develops over this period. Here we assessed the developmental trajectory of graph theory metrics of structural brain connectivity in a cross-sectional study of 467 subjects, aged 12 to 30. We computed network measures from 70×70 connectivity matrices of fiber density generated using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). We assessed global efficiency and modularity, and both age and age(2) effects were identified. HARDI-based connectivity maps are sensitive to the remodeling and refinement of structural brain connections as the human brain develops.Entities:
Year: 2012 PMID： 22903354 PMCID： PMC3420974 DOI： 10.1109/ISBI.2012.6235695
Source DB: PubMed Journal: Proc IEEE Int Symp Biomed Imaging ISSN： 1945-7928