GRETNA

[…] elation matrix was thresholded over a wide range of sparsity (6% -40%), and the properties of the resulting graphs at each threshold value were estimated. Subsequent indicators were calculated in the Gretna (http://www.nitrc.org/projects/gretna/) []. […]

[…] f seeds that have correlation coefficient values greater than a given threshold. Figure shows the Pearson's correlation matrix of the 10-20 EEG electrode system seeds. That matrix was analyzed using GRETNA software (Wang et al., ) computing the small-world sigma (Watts and Strogatz, ) using different thresholds (from 0.05 to 0.5 in 0.05 intervals) obtaining small-world sigma greater than 1.0 in a […]

[…] In this study, both the global and regional network measures of functional brain networks of patients with OSA and GSs were investigated using the graph theoretical network analysis toolbox (GRETNA) (http://www.nitrc.org/projects/gretna/). The brain functional networks were modeled based on an unweighted, undirected method. Sparsity (Sp) was def […]

[…] o select a single threshold, individual correlation matrices were thresholded over a consecutive sparsity range of 0.05 < S < 0.40 (interval = 0.025). All the above procedures were performed with the GRETNA () and DPARSF software (). […]

[…] -derived p-values are ≤0.05 for at least two of four centrality measures. The statistical analyses were conducted using in-house Matlab scripts. The code for permutation testing was modified from the GRETNA toolbox (). […]

[…] Graph analyses were conducted using graph theoretical network analysis (GRETNA; Wang et al., ). The present study adopted the 10 predefined networks based on the parcellation of the brain with 264 cortical and subcortical 10-mm diameter […]