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Rational Drug Therapy Based on
Quantitative Real Time Electric Brain Mapping with CATEEM
Conventional recording of the Electroencephalogram (EEG) results in a very complicated depiction of potential differences whose interpretation takes a lot of skill and also is very time consuming. But Hans Berger, the discoverer of human brain electric activity already in 1932 suggested together with Dietsch to perform a frequency analysis of the signal in order to receive quantitative parameters for better interpretation. About three weeks of calculation made it impossible for practical use at that time. However, today by aid of computers frequency analysis is performed in real time. Result of the analytical procedure named after French mathematician Fourier as “Fast Fourier Transformation” (FFT) consists in documentation of spectral power within certain specially defined frequency ranges historically known as delta, theta, alpha and beta waves. The lower right picture gives an example of such a power spectrum. Figures below document an example of such a recording from a human scalp followed by schematic view of frequency synthesis (superposition of sinus waves) and frequency analysis (reverse process finding out which sin waves are needed to construct the lower complicated signal.
The power spectrum quantitatively depicts the electric power within delta waves (red), theta waves (orange), alpha1 waves (yellow), alpha2 waves (green), beta 1 waves (light blue) and beta2 waves (dark blue). According to basic research the electric power within particular frequency ranges like delta or alpha2 reflect the activity of classic neurotransmitter activities. Thus, delta activity seems to be under the control of the cholinergic transmitter system, whereas alpha2 waves correspond to the activity of the dopaminergic system. In order to use this information derived from quantitative analysis of the EEG for diagnostic purposes, reference data are needed derived from healthy people. Therefore, EEG`s from more than 500 healthy volunteers have been collected using this methodology. They now serve for determination of the aberration from normality of individual patient data. Using this approach a so-called aberration index (AI) can be determined, which provides evidence for statistic deviation from normality with respect to each brain region and frequency content.
Results of the FFT are also used to construct a brain map of electric activity. Using the technique of additive colour mixture (like used for red, green and blue as “RGB” in TV pictures) 140 frequency ranges are coded into spectral colours and depicted as colour mixture. Nonlinear interpolation from 17 electrode positions according to LaGrange allows visualization of frequency changes throughout the whole scalp. An example of a young epileptic patient is given in the figure.
As one can see, electric activity within the temporal lobe (electrode position T3) deviates from normality with respect to delta and theta activity, whose content is considerably higher than in normal healthy volunteers (marked as solid line throughout all brain electrode positions). Rational drug therapy now consists in finding a medication which more or less is able to change these two particular frequencies in the brain. This can be achieved by two different ways: Firstly, pharmaceutical industry very often provides information on which neurotransmitter systems a particular drug predominantly acts. Having the information on the relationship between special frequencies and neurotransmitter activities mentioned above a suitable drug can be chosen with a higher probability of success. Secondly, if there are data on changes of frequency content of the EEG by particular drugs available (clinically or from animal research) again a particular drug may be chosen which prevalently is able to target the frequencies recognized as deviating from normality. In the case of epilepsy depicted above the drug Valproic Acid was chosen, since the electropharmacogram of Valproic Acid as determined from EEG analysis in freely moving rats provided information on predominant effects on delta and theta activity. The electropharmacogram of the drug valproic acid is given in the right lower figure.
Due to the ability of the drug valproic acid to change delta and theta activity the treatment of the epileptic patient was successful. No seizures were observed anymore and the electric brain map (lower part of Fig. 4) no longer showed a temporal deviation of delta and theta waves! EEG data obviously can allow non-invasive therapy control.
Prof. Dr. Wilfried Dimpfel (Justus-Liebig-University Giessen Germany c/o NeuroCode AG, D-35578 Wetzlar)