In this work WC explered the use of linear and nonlinear, statistical appmaches to studying basal EEG brain activity. To do this, We used the Moving Correlation Coefficient (MCC), and the Hurst exponent estimator to visualize short. and long term EEG behavior during 2 minutes of EEG recording in closed eyes basal conditions. The EEG of 8 subjects served as data source for exploring the time series organtzation of the EEG in resting state. We found inter-subjects shared network patterns of high synchronic functional connectivity in frontal and right temporo-occipital regions. We also found a diversity of individual different networks of variable degree of synchronicity, in the range of -0.50.5 for all channels. The short-term approximation to the chaos oscillation (M-Hurst)revealed several individual differences and a potential tool for subject's characterization. (C) 2018 The Authors. Published by Elsevier B.V.