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Experimental Brain Research

Erschienen in:

01.10.2018 | Research Article

Small-world indices via network efficiency for brain networks from diffusion MRI

verfasst von: Lan Lin, Zhenrong Fu, Cong Jin, Miao Tian, Shuicai Wu

Erschienen in: Experimental Brain Research | Ausgabe 10/2018

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Abstract

The small-world architecture has gained considerable attention in anatomical brain connectivity studies. However, how to adequately quantify small-worldness in diffusion networks has remained a problem. We addressed the limits of small-world measures and defined new metric indices: the small-world efficiency (SWE) and the small-world angle (SWA), both based on the tradeoff between high global and local efficiency. To confirm the validity of the new indices, we examined the behavior of SWE and SWA of networks based on the Watts–Strogatz model as well as the diffusion tensor imaging (DTI) data from 75 healthy old subjects (aged 50–70). We found that SWE could classify the subjects into different age groups, and was correlated with individual performance on the WAIS-IV test. Moreover, to evaluate the sensitivity of the proposed measures to network, two network attack strategies were applied. Our results indicate that the new indices outperform their predecessors in the analysis of DTI data.

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Titel: Small-world indices via network efficiency for brain networks from diffusion MRI
verfasst von: Lan Lin
Zhenrong Fu
Cong Jin
Miao Tian
Shuicai Wu
Publikationsdatum: 01.10.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Experimental Brain Research / Ausgabe 10/2018
Print ISSN: 0014-4819
Elektronische ISSN: 1432-1106
DOI: https://doi.org/10.1007/s00221-018-5326-z

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