Journal
PLOS ONE
Volume 9, Issue 10, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0108648
Keywords
-
Categories
Funding
- Swiss National Science Foundation [33CM30_124115, 326030_128775, 33CM30_140338]
- Novartis Research Foundation [09B35]
- Swiss Multiple Sclerosis Society
- Swiss National Science Foundation (SNF) [33CM30_140338, 326030_128775] Funding Source: Swiss National Science Foundation (SNF)
Ask authors/readers for more resources
Functional connectivity (FC) and graph measures provide powerful means to analyze complex networks. The current study determines the inter-subject-variability using the coefficient of variation (CoV) and long-term test-retest-reliability (TRT) using the intra-class correlation coefficient (ICC) in 44 healthy subjects with 35 having a follow-up at years 1 and 2. FC was estimated from 256-channel-EEG by the phase-lag-index (PLI) and weighted PLI (wPLI) during an eyes-closed resting state condition. PLI quantifies the asymmetry of the distribution of instantaneous phase differences of two time-series and signifies, whether a consistent non-zero phase lag exists. WPLI extends the PLI by additionally accounting for the magnitude of the phase difference. Signal-space global and regional PLI/wPLI and weighted first-order graph measures, i.e. normalized clustering coefficient (gamma), normalized average path length (lambda), and the small-world-index (SWI) were calculated for theta-, alpha1-, alpha2- and beta-frequency bands. Inter-subject variability of global PLI was low to moderate over frequency bands (0.12<0.28), higher for wPLI (0.25<0.55) and very low for gamma, lambda and SWI (CoV<0.048). TRT was good to excellent for global PLI/wPLI (0.68<0.80), regional PLI/wPLI (0.58<0.77), and fair to good for graph measures (0.32<0.73) except wPLI-based lambda in alpha1 (ICC = 0.12). Inter-electrode distance correlated very weakly with inter-electrode PLI (-0.06<0) and weakly with inter-electrode wPLI (-0.22<-0.18). Global PLI/wPLI and topographic connectivity patterns differed between frequency bands, and all individual networks showed a small-world-configuration. PLI/wPLI based network characterization derived from high-resolution EEG has apparently good reliability, which is one important requirement for longitudinal studies exploring the effects of chronic brain diseases over several years.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available