  The brain is a complex system whose understanding enables potentially deeper
approaches to mental phenomena. Dynamics of wide classes of complex systems
have been satisfactorily described within $q$-statistics, a current
generalization of Boltzmann-Gibbs (BG) statistics. Here, we study human
electroencephalograms of typical human adults (EEG), very specifically their
inter-occurrence times across an arbitrarily chosen threshold of the signal
(observed, for instance, at the midparietal location in scalp). The
distributions of these inter-occurrence times differ from those usually
emerging within BG statistical mechanics. They are instead well approached
within the $q$-statistical theory, based on non-additive entropies
characterized by the index $q$. The present method points towards a suitable
tool for quantitatively accessing brain complexity, thus potentially opening
useful studies of the properties of both typical and altered brain physiology.
