Pharmakopsychiatrie, Neuro-Psychopharmakologie最新文献

Among the newer psychoactive compounds, clozapine is classified by some authors as an antipsychotic compound, but it exhibits differences in pharmacology and clinical effects that clearly distinguish it from established antipsychotic compounds. It represents an anomaly in the EEG classification scheme as well. In normal volunteers and in psychotic patients, it elicits EEG effects that are more like those of sedative thymoleptic antidepressants than the established antipsychotic compounds. It is probable that the antipsychotic activity reported by some observers reflected the sedative qualities of the compound and not a prototypic antipsychotic activity. Further testing in other psychiatric populations, particularly patients with depressive illnesses, is warranted.

One of the first routine applications of quantitative EEG analysis was in the field of human psychopharmacology. As early as the 1960's, quantitative techniques, mainly period and amplitude integration analyses or analogue filtering, were successfully applied to EEG data with the aim of quantifying and objectifying changes induced by psychoactive medidation. Thus, step by step, a new research field, pharmacoelectroencephalography, was developed. Many other sophisticated new techniques have been described in great detail from the engineering viewpoint. However, due to the language barriers common between representatives of the various disciplines involved, it is still difficult to view them in context with the experimental design as a whole. Therefore, based on examples taken from our routine work, an attempt is made to give a balanced judgement on the value of such techniques in pharmaco-electroencephalography, and their contribution to the CNS pharmacology.

This contribution focusses on the treatment of EEG data as time series. More emphasis is placed on spontaneous activity than on event-related potentials. Smoothing techniques are discussed, both for the nonparametric estimation of regression functions and of densities. Some new promising methods are presented. The fundamentals of time series analysis, and in particular of spectrum analysis, are reviewed. For the difficult area of parameterization of EEG time series, we compare desirable characteristica of parameters with the methods already in use.

The relatively clear and compact picture of an electroencephalographic classification of psychotropic substances becomes extremely more complex if the influence of personality traits and topographic differentiations in the EEG are taken into account. Using the example of EEG alterations under diazepam, amitriptyline, pyritinol, EMD 21-657 and caffeine, the complex structure of substance effects, personality factors, topographical differentiations, placebo reactivity and spontaneous circadian variability of the EEG is demonstrated.

A critical analysis of quantitative pharmaco-electroencephalography begins with parametrization into variables. The determination of frequency bands according to clinical criteria should be reconsidered. Alternatives may be the determination of factor scores or the definition of frequency bands based on factor analysis. If the latter procedure is used, the clinical alpha-band is subdivided into a lower (alpha 1F = 8,5-10.5 HZ) and an upper (alpha 2F = 10.5-12.5 HZ) part. Furthermore parts of the clinical theta-band (and the delta-band are combined into the delta F-band (1.5-6.0 HZ), for awake healthy volunteers with an occipital alpha-rhythm. Existing concepts of vigilance for the awake stages are not contradictory to the following observations: the factor structure of EEG relative power spectrum variables shows a negative correlation of slow alpha-frequencies with those in the delta F- and beta 3F-band. There is also a negative correlation between slow and fast alpha-wave relative power values.

The main object of the study was to separate the specific EEG effects of psychopharmaca from changes caused by drowsiness. The study was based on quantitative evaluation of the vigilance level during five minutes of EEG recording under standardized conditions. The equation for computing the vigilance level from EEG spectra was obtained by using a training material. The segments were classified visually either as alert EEG, or as EEG marked by drowsiness. As confirmed by independent test material, the coefficients derived by means of multiple linear regression were applicable to other EEGs for estimating the vigilance level. The procedure was used in the evaluation of the psychopharmacological treatment. It was concluded that the specific EEG drug profiles were certainly influenced by the accompanying drowsiness, but the main information was still preserved. In contrast to the specific drug effect, the drug-induced sleep activity could be isolated from other events and studied separately. It was also found that after a standard stimulation, both the general trend and periodicity of the vigilance fluctuations were closely related to the psychic state of the patient.