The study of the entropic structure and organization of the brain allows us to visualize brain functioning as a network of hyper-complex processes that exist on the verge of chaos, thanks to the permanent supply of energy that sustains it in this quasi-stable condition. However, this energy supply does not ensure its optimal administration, and it is possible that much of the chronic, acute, severe or mild neuro-psychopathology that we experience in society may have to do with the inappropriate distribution in the brain of the entropic order/chaos balance that every complex organic system must pay. In the present report, we replicated and extended the set of results from using brain entropic profiles to characterize the structure and organization of the order/chaos balance in the brain on the basis of the EEG electrodes array. Through inter-group comparison of two similar samples, we corroborated the nonlinear behavior of the Hurst exponent estimator, as well as confirmed the behavior of the two Hurst derivatives that estimate the order/chaos balance at different time scales. The two samples compared correspond to a random sample (N=7) and a non-random sample (N=13) of subjects from which EEG recordings were obtained in basal resting conditions with eyes closed, using the Emotiv Epoc brain-computer interface (Research Edition), with a sampling rate of 128Hz. The study also compared the behavior of the nonlinear estimators in 4 sub-second time processing windows (125ms, 250ms, 500ms, and 1s). The overall results of all the comparisons made were consistent in the inter-group comparison, but at the same time some differences between the two samples were revealed. The study also revealed some differences at the intra-group level, as well as at the intra- and inter-individual scales. The use of entropic brain profiles proved to be a powerful tool to conduct an investigation of the non-linear phenomenology of EEG and its implications on the order/chaos balance of the brain.
