Multivariate multiscale entropy (mMSE) as a tool for understanding the resting-state EEG signal dynamics: the spatial distribution and sex/gender-related differences

Table 2 Descriptive statistics for the AUC (area under curve), MaxSlope, AvgEnt and the DiffEnt features of the multivariate Multiscale Entropy (mMSE) vector determined for the channel sets corresponding to the seven resting-state networks (Yeo et al. 2011).

Network	M	SD	Skewness	Kurtosis
AUC
DMN	23.448	2.790	−0.688	0.697
DAN	23.617	3.349	−0.624	0.593
FPN	21.964	3.007	−0.700	0.616
LN	21.879	3.081	−0.835	0.510
SMN	24.200	2.677	−0.941	1.752
VAN	23.066	3.033	−0.893	1.009
VN	21.381	3.554	−0.554	−0.186
MaxSlope
DMN	0.519	0.148	0.406	−1.072
DAN	0.466	0.117	0.843	0.849
FPN	0.491	0.147	0.388	−1.097
LN	0.514	0.150	0.170	−1.132
SMN	0.517	0.131	0.567	−0.707
VAN	0.520	0.147	0.246	−1.048
VN	0.426	0.127	0.729	0.053
AvgEnt
DMN	1.944	0.331	−0.297	−0.461
DAN	2.078	0.365	−0.368	−0.348
FPN	1.831	0.334	−0.208	−0.070
LN	1.760	0.323	−0.190	−0.298
SMN	2.032	0.324	−0.469	0.057
VAN	1.924	0.317	−0.254	−0.229
VN	1.846	0.341	−0.289	−0.522
DiffEnt
DMN	−0.438	0.409	−0.168	−0.421
DAN	−0.195	0.303	−0.590	0.580
FPN	−0.391	0.404	−0.751	0.886
LN	−0.502	0.414	−0.312	−0.356
SMN	−0.395	0.352	−0.189	−0.093
VAN	−0.424	0.381	−0.476	0.218
VN	−0.223	0.307	−1.272	2.244

DMN default mode network, DAN dorsal attention network, FPN frontoparietal network, LN limbic network, SMN somatomotor network, VAN ventral attention network, VN visual network

ISSN: 1744-9081