Open Access
Lecture Notes in Computer Science, pages 305-312
Test-Retest Reliability of Graph Theory Measures of Structural Brain Connectivity
Emily L. Dennis
1
,
Neda Jahanshad
1
,
Arthur W. Toga
2
,
Katie L. McMahon
3
,
Greig I. de Zubicaray
4
,
Nicholas G. Martin
5
,
Margaret J. Wright
4, 5
,
Paul M. Thompson
1
3
Center for Advanced Imaging, Univ. of Queensland, Brisbane, Australia
|
Publication type: Book Chapter
Publication date: 2012-09-21
Journal:
Lecture Notes in Computer Science
Q2
SJR: 0.606
CiteScore: 2.6
Impact factor: —
ISSN: 03029743, 16113349, 18612075, 18612083
Abstract
The human connectome has recently become a popular research topic in neuroscience, and many new algorithms have been applied to analyze brain networks. In particular, network topology measures from graph theory have been adapted to analyze network efficiency and ‘small-world’ properties. While there has been a surge in the number of papers examining connectivity through graph theory, questions remain about its test-retest reliability (TRT). In particular, the reproducibility of structural connectivity measures has not been assessed. We examined the TRT of global connectivity measures generated from graph theory analyses of 17 young adults who underwent two high-angular resolution diffusion (HARDI) scans approximately 3 months apart. Of the measures assessed, modularity had the highest TRT, and it was stable across a range of sparsities (a thresholding parameter used to define which network edges are retained). These reliability measures underline the need to develop network descriptors that are robust to acquisition parameters.
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Dennis E. L. et al. Test-Retest Reliability of Graph Theory Measures of Structural Brain Connectivity // Lecture Notes in Computer Science. 2012. pp. 305-312.
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Dennis E. L., Jahanshad N., Toga A. W., McMahon K. L., de Zubicaray G. I., Martin N. G., Wright M. J., Thompson P. M. Test-Retest Reliability of Graph Theory Measures of Structural Brain Connectivity // Lecture Notes in Computer Science. 2012. pp. 305-312.
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RIS
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TY - GENERIC
DO - 10.1007/978-3-642-33454-2_38
UR - https://doi.org/10.1007/978-3-642-33454-2_38
TI - Test-Retest Reliability of Graph Theory Measures of Structural Brain Connectivity
T2 - Lecture Notes in Computer Science
AU - Dennis, Emily L.
AU - Jahanshad, Neda
AU - Toga, Arthur W.
AU - McMahon, Katie L.
AU - de Zubicaray, Greig I.
AU - Martin, Nicholas G.
AU - Wright, Margaret J.
AU - Thompson, Paul M.
PY - 2012
DA - 2012/09/21
PB - Springer Nature
SP - 305-312
SN - 0302-9743
SN - 1611-3349
SN - 1861-2075
SN - 1861-2083
ER -
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BibTex (up to 50 authors)
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@incollection{2012_Dennis,
author = {Emily L. Dennis and Neda Jahanshad and Arthur W. Toga and Katie L. McMahon and Greig I. de Zubicaray and Nicholas G. Martin and Margaret J. Wright and Paul M. Thompson},
title = {Test-Retest Reliability of Graph Theory Measures of Structural Brain Connectivity},
publisher = {Springer Nature},
year = {2012},
pages = {305--312},
month = {sep}
}