Statistical complexity and nontrivial collective behavior in electroencephalografic signals

Abstract

We calculate a measure of statistical complexity from the global dynamics of electroencephalographic (EEG) signals from healthy subjects and epileptic patients, are able to stablish a criterion to characterize the behavior in both groups of individuals. It is found the collective dynamics of EEG signals possess relative values of complexity for healthy subjects in comparison that for epileptic patients. To interpret these results, propose a model of a network of coupled chaotic maps we calculate the complexity as a function of a parameter relate this measure with the emergence of nontrivial behavior in the system. Our results show that the presence nontrivial collective behavior is associated to high values complexity; thus suggesting that similar dynamical process may take place in the human brain. Our findings suggest that epilepsy is a degenerative illness related to loss of complexity in the brain