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. Author manuscript; available in PMC: 2017 Jan 15.
Published in final edited form as: Neuroimage. 2015 Oct 27;125:601–615. doi: 10.1016/j.neuroimage.2015.10.070

Table E.1.

Posterior probabilities of relative temporal stationarity for graph metrics. (a) Posterior probability of greater temporal stationarity in global efficiency than in path length; (b) posterior probability of greater temporal stationarity in betweenness centrality than in eigenvector centrality; (c) posterior probability of greater temporal stationarity in global efficiency than in local efficiency; (d) posterior probability of greater temporal stationarity in small-world index than in the other graph measures. λ, characteristic path length; GE, global efficiency; γ, clustering coefficient; LE, local efficiency; σ, small-world index; BC, betweenness centrality; EC, eigenvector centrality.

HC TLE
(a) Global integration measures (GE vs. λ)
NGE > Nλ SGE > Sλ NGE > Nλ SGE > Sλ
0.81 0.78 0.54 0.52
(b) Centrality measures (BC vs. EC)
NBC > NEC SBC > SEC NBC >NEC SBC > SEC
0.90 0.87 0.994 0.993
(c) Efficiency measures (GE vs. LE)
NGE >NLE SGE > SLE NGE > NLE SGE > SLE
0.98 0.97 0.97 0.96
(d) Small-world index
Nσ > NZ Sσ > SZ Nσ > NZ Sσ > SZ
Z = γ 0.76 0.75 0.00 0.00
Z = GE 0.89 0.87 0.999 0.999
Z = LE 0.998 0.997 0.999 0.999
Z = λ 0.98 0.97 0.999 0.999
Z = BC 0.97 0.96 0.999 0.997
Z = EC 0.998 0.997 0.999 0.999