Abstract

In this report we explore the use of a method to generate dynamic brain images that represent the variation of the entropic organization of the cerebral cortex during a particular state or condition. The work uses the derivation of nonlinear estimators of the order/chaos balance obtained by calculating the Hurst exponent from the EEG signal captured by an electrocephalograph. The procedure generates entropic estimators of the EEG time series oscillation, for each electrode, being able to obtain consecutive images of individual maps, which represent the nonlinear average of the EEG order/chaos balance for each 125ms of recording.