TITLE:
Classification of Herbal Drug Effects by Discriminant Analysis of Quantitative Human EEG Data
AUTHORS:
Wilfried Dimpfel
KEYWORDS:
Quantitative EEG, Discriminant Analysis, Herbal Drugs, Fast Fourier Transformation, Central Nervous System, CATEEM
JOURNAL NAME:
Neuroscience and Medicine,
Vol.10 No.2,
May
27,
2019
ABSTRACT: Clinical indications for herbal drugs very often only rely on traditional knowledge. Single plant-derived preparations are used for many purposes and cannot be classified to belong to a single category like calming or stimulating drugs. With respect to the brain a unique possibility exists to analyze drug effects by recording the EEG. It is common knowledge that many drugs change the frequency content of electric brain activity. Quantitative analysis of the EEG by Fast Fourier Transformation reveals parameters like spectral power, which can be processed further (CATEEM®). Source density was determined from 17 channels of the quantitative EEG from 10 clinical studies recorded in a relaxed state with open eyes. Linear discriminant analysis was used to differentiate the effects of Placebo (circadian rhythm) from CNS-active herbal drugs in comparison to Valium®. Calmvalera®, L-Theanine, Lasea®, Neurapas®, Neuravena®, Neurexan®, Nutrifin Relax®, Pascoflair® (herbal calming drugs) as well as memoLoges®, Zembrin® (herbal stimulating drugs) induced different changes of the frequency content of brain electric activity. Discriminant analysis revealed that Nutrifin Relax®, Pascoflair® and Suntheanine® could not be separated well from each other indicating a similar mechanism of action. The effect of Valium® was projected at a very isolated position far away from the herbal preparations indicating a totally different mechanism of action. Zembrin® and memoLoges® grouped together with respect to the first three discriminant functions, but were different with respect to the 4th to 6th discriminant function. Lasea® as anxiolytic drug and Neurapas® as antidepressive drug were projected at isolated positions indicating their different clinical indications. The results indicate that discriminant analysis of human quantitative EEG data allows for unique pharmacological description of individual effect profiles of herbal drugs.