Electronic Theses and Dissertations
Reliability of Graph Measures Derived from Resting-State MEG Data Using Source Space Functional Connectivity Analysis
Date of Award
Master of Science
Amy de Jongh Curry
The reliability of global graph measures derived from neuroimaging data is an important criterion for their use as biomarkers for neurological disorders. This study examined the reliability of the global efficiency (GE), characteristic path length (CPL), transitivity, and synchronizability of functional whole-brain and intra-hemispheric networks based on resting-state magnetoencephalography. Brain sources were reconstructed using atlas-based beamforming, and functional connectivity in six frequency bands was estimated using the debiased weighted phase lag index. An optimal threshold of 100% was chosen based on test-retest reliability of the measures. At this threshold, test-retest reliability of the GE, CPL, and transitivity was mostly fair to excellent except for in the delta band. However, test-retest reliability of the synchronizability was mostly poor to fair. There was no significant effect of gender on any graph measure. Overall, these results indicate that the GE, CPL, and transitivity in most of the frequency bands may be useful biomarkers.
dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.
Pourmotabbed, Haatef, "Reliability of Graph Measures Derived from Resting-State MEG Data Using Source Space Functional Connectivity Analysis" (2020). Electronic Theses and Dissertations. 2126.
Data is provided by the student.