Statistical Decision Tree: A Tool for Studying Pharmaco-EEG Effects of CNS-Active Drugs
Résumé
Quantitative pharmaco-EEG has become a useful technique for determing pharmacodynamic parameters after CNS-active drug administration. Nevertheless, one of the most important problems faced by practitioners of pharmaco-EEG is the difficulty in evaluating drug-specific effects. In this article, a methodology for comparing two time sequences of pharmacodynamic measurements, the Statistical Decision Tree (SDT), is proposed. This methodology, based on one- and multi-dimensional Wilcoxon signed-rank tests on EEG variables, takes into account vigilance fluctuations and placebo effects in order to pick out effects specifically due to the drug.