Convergence and divergence across construction methods for human brain white matter networks: An assessment based on individual differences
Using diffusion MRI, a number of studies have investigated the properties of whole‐brain white matter (WM) networks with differing network construction methods (node/edge definition). However, how the construction methods affect individual differences of WM networks and, particularly, if distinct me...
Saved in:
Published in | Human brain mapping Vol. 36; no. 5; pp. 1995 - 2013 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
Blackwell Publishing Ltd
01.05.2015
John Wiley & Sons, Inc John Wiley and Sons Inc |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Using diffusion MRI, a number of studies have investigated the properties of whole‐brain white matter (WM) networks with differing network construction methods (node/edge definition). However, how the construction methods affect individual differences of WM networks and, particularly, if distinct methods can provide convergent or divergent patterns of individual differences remain largely unknown. Here, we applied 10 frequently used methods to construct whole‐brain WM networks in a healthy young adult population (57 subjects), which involves two node definitions (low‐resolution and high‐resolution) and five edge definitions (binary, FA weighted, fiber‐density weighted, length‐corrected fiber‐density weighted, and connectivity‐probability weighted). For these WM networks, individual differences were systematically analyzed in three network aspects: (1) a spatial pattern of WM connections, (2) a spatial pattern of nodal efficiency, and (3) network global and local efficiencies. Intriguingly, we found that some of the network construction methods converged in terms of individual difference patterns, but diverged with other methods. Furthermore, the convergence/divergence between methods differed among network properties that were adopted to assess individual differences. Particularly, high‐resolution WM networks with differing edge definitions showed convergent individual differences in the spatial pattern of both WM connections and nodal efficiency. For the network global and local efficiencies, low‐resolution and high‐resolution WM networks for most edge definitions consistently exhibited a highly convergent pattern in individual differences. Finally, the test–retest analysis revealed a decent temporal reproducibility for the patterns of between‐method convergence/divergence. Together, the results of the present study demonstrated a measure‐dependent effect of network construction methods on the individual difference of WM network properties. Hum Brain Mapp 36:1995–2013, 2015. © 2015 Wiley Periodicals, Inc. |
---|---|
Bibliography: | National Science Foundation of China - No. 81271649; No. 81322021; No. 81030028; No. 31221003 Scientific Research Foundation for the Returned Overseas Chinese Scholars National Science Fund for Distinguished Young Scholars of China - No. 81225012 Major Project of National Social Science Foundation - No. 12 No. 11 istex:D3342EB1016A31C7FE2C0CFDE11745729B359E76 ArticleID:HBM22751 Beijing Nova Program - No. Z121110002512032 Specialized Research Fund for the Doctoral Program of Higher Education, China - No. 20130003110002 973 program - No. 2013CB837300 ark:/67375/WNG-F61CBWVR-D 863 program - No. 2015AA020912 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23 |
ISSN: | 1065-9471 1097-0193 1097-0193 |
DOI: | 10.1002/hbm.22751 |