Quantitative analysis of human electroencephalogram (EEG) is a valuable method for
evaluating psychopharmacological agents. Although the effects of different drug classes on EEG
spectra are already known, interactions between brain locations remain unclear. In this work, cross
mutual information function and appropriate surrogate data were applied to assess linear and
nonlinear couplings between EEG signals. The main goal was to evaluate the pharmacological effects
of alprazolam on brain connectivity during wakefulness in healthy volunteers using a cross-over,
placebo-controlled design. Eighty-five pairs of EEG leads were selected for the analysis, and connectivity
was evaluated inside anterior, central, and posterior zones of the scalp. Connectivity between these
zones and interhemispheric connectivity were also measured. Results showed that alprazolam induced
significant changes in EEG connectivity in terms of information transfer in comparison with placebo.
Trends were opposite depending on the statistical characteristics: decreases in linear connectivity and
increases in nonlinear couplings. These effects were generally spread over the entire scalp. Linear
changes were negatively correlated, and nonlinear changes were positively correlated with drug
plasma concentrations; the latter showed higher correlation coefficients. The use of both linear
and nonlinear approaches revealed the importance of assessing changes in EEG connectivity as
this can provide interesting information about psychopharmacological effects.