A review of the continuum of drug-induced states of excitation and depression

G-force induced alterations in rat EEG activity: a quantitative analysis

A major physical limitation affecting pilots is G-force (+Gz, head-to-foot inertial load) induced loss of consciousness. Previous studies have shown that +Gz produces qualitatively similar effects on human and rat EEG activity. The present study sought to quantitatively correlate changes in rat EEG activity with increasing +Gz levels. A frontal-parietal differential electrode recorded rat EEG data during +Gz exposures (30 s) ranging from +0.5 to +25.0 Gz. Acceleration levels < or = +10 Gz had little effect on EEG activity. Acceleration levels of +15 to +20 Gz were associated with increased EEG slowing, depression and sharp waves. Acceleration levels > or = +17.5 Gz evoked burst suppression followed by isoelectric activity. Times to first onset of delta, depressed, and isoelectric EEG activity were approximately 12, 14 and 18 s, respectively. Acceleration effects on delta (1-4 Hz), theta (5-8 Hz), alpha (9-12 Hz), beta (13-30 Hz) and total (1-30 Hz) EEG powers were examined using Fourier transform analysis. EEG measures with the most predictive value at the following post-acceleration onset times (PAOT) were as follows (in s); increasing theta power: PAOT 0-2, decreasing delta power: PAOT 3-9, and decreasing beta power: PAOT > or = 12. This study provides a quantitative description of +Gz-induced alterations in EEG magnitude, time course and spectral content. Additionally, several EEG measures were identified which correlated with acceleration level at specific post-acceleration onset times.

Electroencephalogram effect measures and relationships between pharmacokinetics and pharmacodynamics of centrally acting drugs

Electroencephalogram (EEG) effect parameters may be useful in pharmacokinetic-pharmacodynamic modelling studies of drug effects on the central nervous system (CNS). Effect parameters derived from a quantitative analysis of the EEG appear to be perfectly suited to characterise the relationships between pharmacokinetics and pharmacodynamics of benzodiazepines and intravenous anaesthetics. EEG parameters represent many of the characteristics of ideal pharmacodynamic measures, being continuous, objective, sensitive and reproducible. These features provide the opportunity to derive concentration-effect relationships for these drugs in individuals, which yield important quantitative information on the potency and intrinsic efficacy of these drugs. The EEG techniques presented can be used to study the influences of factors such as age, disease, chronic drug use and drug interactions on the concentration-effect relationships of psychotropic drugs. An important issue is the choice of the EEG parameter to characterise the CNS effects of the compounds. More attention must be paid to evaluating the relevance of EEG parameters to the pharmacological effects of the drugs. Knowledge of the relationship between EEG effect parameters and clinical effects of drugs under different physiological and pathophysiological conditions is crucial to determining the value of EEG parameters in drug effect monitoring. Pharmacodynamic parameters derived from the concentration-EEG effect relationship may be correlated to pharmacodynamic parameters obtained from other in vitro and in vivo effect measurements. These comparisons revealed that changes in the amplitudes in the beta frequency band of EEG signals is a relevant measure of pharmacological effect intensity of benzodiazepines, which reflects their affinity and intrinsic efficacy at the central gamma-aminobutyric acid (GABA) benzodiazepine receptor complex. The exact EEG correlates of the anxiolytic, anticonvulsant, sedative and hypnotic actions of benzodiazepines have not yet clearly been elucidated. For intravenous anaesthetics, close correlations between the potency determined with EEG measurements and clinical measures of anaesthetic depth have been established, suggesting that, in principle, EEG parameters can adequately reflect depth of anaesthesia. However, more study is required to further substantiate these findings.

Pharmacodynamic characterization of the electroencephalographic effects of thiopental in rats

We have developed a chronically instrumented rat model that uses changes in electroencephalographic wave forms to estimate continuously the degree of central nervous system (CNS) depression induced by thiopental. Such changes were subject to aperiodic signal analysis, a technique that breaks down the complex EEG into a series of discreet neurologic "events" which are then quantitated as waves/sec. We thus obtained a continuous measure of CNS drug effect. In addition we continuously recorded central arterial blood pressure and heart rate and monitored ventilatory status using arterial blood gas determinations. We also determined, with frequent arterial blood sampling, the distribution and elimination of thiopental in individual animals. The time lag occurring in the curve representing arterial concentration of thiopental vs. EEG effect suggests that arterial plasma is not kinetically equivalent to the EEG effect site. Application of semiparametric pharmacodynamic modeling techniques enabled us to estimate equilibration rate constant (Keo) for concentrations of thiopental between arterial plasma and the effect site. The half-life for equilibration of thiopental with the EEG (CNS) effect was less than 80 sec. Knowledge of the rate of equilibration permitted characterization of the relationship between the steady state plasma concentrations and CNS effect of thiopental, as measured by activation and slowing of the EEG. At concentrations of thiopental below 5 micrograms/ml, EEG activity was 180% higher than during the baseline awake state. Thiopental produced an activated EEG over more than 20% of the concentration-effect relationship. Further increases in the concentration of thiopental at the site of effect depressed EEG activity progressively until complete suppression of the EEG signal occurred (at which time, the concentration was approximately 80 micrograms/ml). This report describes our model and its application to the assessment of the pharmacodynamics of thiopental as manifested by changes on the EEG.

Pharmacokinetic-pharmacodynamic modeling of the central nervous system effects of heptabarbital using aperiodic EEG analysis

The concentration EEG effect relationship of heptabarbital was modeled using effect parameters derived from aperiodic EEG analysis. Male Wistar rats (n = 10) received an intravenous infusion of heptabarbital at a rate of 6-9 mg/kg per min until burst suppression with isoelectric periods of 5 sec or longer. Arterial blood samples were obtained and EEG was measured continuously until recovery of baseline EEG and subjected to aperiodic analysis for quantification. Two EEG parameters, the amplitudes per second (AMP) and the total number of waves per second (TNW), in five discrete frequency ranges and for two EEG leads were used as descriptors of the drug effect on the brain. The EEG parameters responded both qualitatively and quantitatively different to increasing concentrations of heptabarbital. Monophasic concentration effect curves (decrease) were found for the frequency ranges greater than 2.5 Hz and successfully quantified with a sigmoidal Emax model after collapsing the hysteresis by a nonparametric modeling approach. For the parameter TNW in the 2.5-30 Hz frequency range the value of the pharmacodynamic parameters EC50, Emax, and n (means +/- SD) were 78 +/- 7 mg/L, 11.4 +/- 1.7 waves/sec and 5.0 +/- 1.5, respectively. For other discrete frequency ranges, differences in EC50 were observed, indicating differences in sensitivity to the effect of heptabarbital. In the 0.5 +/- 2.5 Hz frequency range biphasic concentration effect relationships (increase followed by decrease) were observed. To fully account for the hysteresis in these concentration effect relationships, postulation of two effect compartments was necessary. To characterize these biphasic effect curves two different pharmacodynamic models were evaluated. Model 1 characterized the biphasic concentration effect relationship as the summation of two sigmoidal Emax models, whereas Model 2 assumed the biphasic effect to be the result of only one inhibitory mechanism of action. With Model 1 however realistic parameter estimation was difficult because the maximal increase could not be measured, resulting in high correlations between parameter estimates. This seriously limits the value of Model 1. Model 2 involves besides estimation of the classical pharmacodynamic parameters Emax, EC50, and n also estimation of the maximal disinhibition Amax. This model is a new approach to characterize biphasic drug effects and allows, in principle, reliable estimation of all relevant pharmacodynamic parameters.