Advanced Analysis of Pharmaco-EEG Data in Humans.

Pharmaco-electroencephalography (EEG) is a non-invasive method used to assess the effects of pharmacological compounds on the central nervous system by processing the EEG signals which directly reveal the spontaneous synchronised postsynaptic neuronal activity of the cortex with high temporal resolution. The International Pharmaco-Encephalography Society (IPEG) has recently published guidelines, which were produced by a global panel of EEG experts, with the goal to increase the standardisation of pharmaco-EEG studies in human subjects and facilitate the comparability of data across laboratories, thus enabling data-pooling and meta-analyses. The recommended standard experimental procedure is to measure EEG activity under vigilance-controlled and resting conditions. The IPEG guidelines thoroughly present the technical details and therefore constitute a robust reference. The complementary aim of the present paper is to focus on practical aspects, pitfalls and precautions to be considered when processing pharmaco-EEG data by covering the following topics: (1) investigate the stability and reliability of 5-min EEG recordings under both vigilance-controlled and resting conditions; (2) assess the spontaneous time-dependent changes in spectral activity over time, and (3) apply the data-processing strategies suggested in the pharmaco-EEG guidelines and designed to optimally capture drug effects. For this purpose, the EEG data from a randomised, double-blind, crossover trial aimed at comparing the effect of diazepam (10 mg) and placebo in 16 healthy male volunteers is used to illustrate the discussion of the processing techniques and difficulties commonly faced when analysing pharmaco-EEG data.

Guidelines for the recording and evaluation of pharmaco-sleep studies in man: the International Pharmaco-EEG Society (IPEG).

The International Pharmaco-EEG Society (IPEG) presents guidelines summarising the requirements for the recording and computerised evaluation of pharmaco-sleep data in man. Over the past years, technical and data-processing methods have advanced steadily, thus enhancing data quality and expanding the palette of sleep assessment tools that can be used to investigate the activity of drugs on the central nervous system (CNS), determine the time course of effects and pharmacodynamic properties of novel therapeutics, hence enabling the study of the pharmacokinetic/pharmacodynamic relationship, and evaluate the CNS penetration or toxicity of compounds. However, despite the presence of robust guidelines on the scoring of polysomnography -recordings, a review of the literature reveals inconsistent -aspects in the operating procedures from one study to another. While this fact does not invalidate results, the lack of standardisation constitutes a regrettable shortcoming, especially in the context of drug development programmes. The present guidelines are intended to assist investigators, who are using pharmaco-sleep measures in clinical research, in an effort to provide clear and concise recommendations and thereby to standardise methodology and facilitate comparability of data across laboratories.

Guidelines for the recording and evaluation of pharmaco-EEG data in man: the International Pharmaco-EEG Society (IPEG).

The International Pharmaco-EEG Society (IPEG) presents updated guidelines summarising the requirements for the recording and computerised evaluation of pharmaco-EEG data in man. Since the publication of the first pharmaco-EEG guidelines in 1982, technical and data processing methods have advanced steadily, thus enhancing data quality and expanding the palette of tools available to investigate the action of drugs on the central nervous system (CNS), determine the pharmacokinetic and pharmacodynamic properties of novel therapeutics and evaluate the CNS penetration or toxicity of compounds. However, a review of the literature reveals inconsistent operating procedures from one study to another. While this fact does not invalidate results per se, the lack of standardisation constitutes a regrettable shortcoming, especially in the context of drug development programmes. Moreover, this shortcoming hampers reliable comparisons between outcomes of studies from different laboratories and hence also prevents pooling of data which is a requirement for sufficiently powering the validation of novel analytical algorithms and EEG-based biomarkers. The present updated guidelines reflect the consensus of a global panel of EEG experts and are intended to assist investigators using pharmaco-EEG in clinical research, by providing clear and concise recommendations and thereby enabling standardisation of methodology and facilitating comparability of data across laboratories.

Modeling napping, post-lunch dip, and other variations in human sleep propensity.

STUDY OBJECTIVES: To model sleep propensity (SP) as a continuous variable across 24 hours and to model the post-noon nap zone, or post-lunch dip in performance, and the early evening trough in SP. METHODS: The present model is a variant of the 2-process model with 2 major modifications. (1) The circadian threshold process was replaced by sleep drive R, derived from REM sleep propensity, which shows a strong circadian modulation. (2) The model is based on a multiplicative interaction between the 2 input variables S and R. The model parameters S and R were estimated from experimental data. Thus, SP is modeled by multiplicative interaction of 2 sleep drives, S and R, the former of homeostatic, the latter of circadian nature. In short: SP = S x R. RESULTS: Under the condition of normal phase and duration of nighttime sleep, SP across 24 hours displays 4 characteristics, (a) a major peak at nighttime, (b) a secondary increase, which peaks post-noon, (c) a first local minimum at sleep offset in the morning, and (d) a second local minimum in the early evening hours. Model simulations with either delayed or advanced sleep times suggest that the magnitude of the post-noon nap zone depends on the phase of the major sleep period within 24 hours. While the nap zone is attenuated or disappears when night sleep is delayed, SP increases during daytime when night sleep is advanced. In all conditions, the evening local minimum of SP remained stable. CONCLUSIONS: SP can be modeled as a continuous variable, based on the multiplicative interaction of 2 basic sleep drives. The model predictions are in agreement with known variations of SP across 24 hours.