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Statistical Decision Tree: A Tool for Studying Pharmaco-EEG Effects of CNS-Active Drugs

Abstract : 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.
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https://hal-utt.archives-ouvertes.fr/hal-02861433
Contributor : Jean-Baptiste Vu Van <>
Submitted on : Tuesday, June 9, 2020 - 7:13:41 AM
Last modification on : Wednesday, June 10, 2020 - 3:01:43 AM

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Koudou Toussaint Dago, Rémy Luthringer, Régis Lengellé, Gérard Rinaudo, Jean-Paul Macher. Statistical Decision Tree: A Tool for Studying Pharmaco-EEG Effects of CNS-Active Drugs. Neuropsychobiology, Karger, 1994, 29 (2), pp.91-96. ⟨10.1159/000119068⟩. ⟨hal-02861433⟩

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