3 research outputs found
Statistical Complexity and Nontrivial Collective Behavior in Electroencephalografic Signals
We calculate a measure of statistical complexity from the global dynamics of
electroencephalographic (EEG) signals from healthy subjects and epileptic
patients, and are able to stablish a criterion to characterize the collective
behavior in both groups of individuals. It is found that the collective
dynamics of EEG signals possess relative higher values of complexity for
healthy subjects in comparison to that for epileptic patients. To interpret
these results, we propose a model of a network of coupled chaotic maps where we
calculate the complexity as a function of a parameter and relate this measure
with the emergence of nontrivial collective behavior in the system. Our results
show that the presence of nontrivial collective behavior is associated to high
values of complexity; thus suggesting that similar dynamical collective process
may take place in the human brain. Our findings also suggest that epilepsy is a
degenerative illness related to the loss of complexity in the brain.Comment: 13 pages, 3 figure