Complexity analysis of dense array EEG signal reveals sex difference.

This article deals with the complexity aspects of the recorded electroencephalogram (EEG) signal from male and female subjects. The analysis follows direct application of time series measures of global linear complexity and characterization of the embedded complexity in the signals using the nonlinear statistic of approximate entropy. The study reveals significant differences in complexity between the two sex groups during passive, no-task conditions, whereas no apparent variation exists during a mental task state. The detection of subtle changes as well as the ease in presenting a global picture of the complexity variation on the human cortical surface makes the nonlinear statistic a better marker of system complexity.