391 research outputs found

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

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    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

    Deep learning-based i-EEG classification with convolutional neural networks for drug-target interaction prediction

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    Drug-target interaction (DTI) prediction has become a foundational task in drug repositioning, polypharmacology, drug discovery, as well as drug resistance and side-effect prediction. DTI identification using machine learning is gaining popularity in these research areas. Through the years, numerous deep learning methods have been proposed for DTI prediction. Nevertheless, prediction accuracy and efficiency remain key challenges. Pharmaco-electroencephalogram (pharmaco-EEG) is considered valuable in the development of central nervous system-active drugs. Quantitative EEG analysis demonstrates high reliability in studying the effects of drugs on the brain. Earlier preclinical pharmaco-EEG studies showed that different types of drugs can be classified according to their mechanism of action on neural activity. Here, we propose a convolutional neural network for EEG-mediated DTI prediction. This new approach can explain the mechanisms underlying complicated drug actions, as it allows the identification of similarities in the mechanisms of action and effects of psychotropic drugs

    Mice Lacking GABA(A) Receptor delta Subunit Have Altered Pharmaco-EEG Responses to Multiple Drugs

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    In the brain, extrasynaptically expressed ionotropic, delta subunit-containing gamma-aminobutyric acid A-type receptors (delta-GABA(A)Rs) have been implicated in drug effects at both neuronal and behavioral levels. These alterations are supposed to be caused via drug-induced modulation of receptor ionophores affecting chloride ion-mediated inhibitory tonic currents. Often, a transgenic mouse model genetically lacking the delta-GABA(A)Rs (delta-KO) has been used to study the roles of delta-GABA(A)Rs in brain functions, because a specific antagonist of the delta-GABA(A)Rs is still lacking. We have previously observed with these delta-KO mice that activation of delta-GABA(A)Rs is needed for morphine-induced conditioning of place preference, and others have suggested that delta-GABA(A)Rs act as targets selectively for low doses of ethanol. Furthermore, activation of these receptors via drug-mediated agonism induces a robust increase in the slow-wave frequency bands of electroencephalography (EEG). Here, we tested delta-KO mice (compared to littermate wild-type controls) for the pharmaco-EEG responses of a broad spectrum of pharmacologically different drug classes, including alcohol, opioids, stimulants, and psychedelics. Gaboxadol (THIP), a known superagonist of delta-GABA(A)Rs, was included as the positive control, and as expected, delta-KO mice produced a blunted pharmaco-EEG response to 6 mg/kg THIP. Pharmaco-EEGs showed notable differences between treatments but also differences between delta-KO mice and their wild-type littermates. Interestingly mephedrone (4-MMC, 5 mg/kg), an amphetamine-like stimulant, had reduced effects in the delta-KO mice. The responses to ethanol (1 g/kg), LSD (0.2 mg/kg), and morphine (20 mg/kg) were similar in delta-KO and wild-type mice. Since stimulants are not known to act on delta-GABA(A)Rs, our findings on pharmaco-EEG effects of 4-MMC suggest that delta-GABA(A)Rs are involved in the secondary indirect regulation of the brain rhythms after 4-MMC.Peer reviewe

    Evaluation efficiency of modern antidepressants by means of quantative pharmaco-EEG

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    An example perspective way to improve the pharmacotherapy of depression is to combine SSIRs with representatives of other groups of drugs. Great interest from this point of view is the hormone of pineal gland - melatonin (MT), which is an important element of the non-specific antistress system of body. Evaluation efficiency of the above regimes of pharmacotherapy of depressive frustration showed, that the application of valdoxan, and also combination fluoxetine+melaxen favorably affects the course of the disease and contributes to a more rapid normalization of bioelectric activity of brain than fluoxetine in isolation, both experimentally and clinicall

    Inhibition of alpha oscillations through serotonin-2A receptor activation underlies the visual effects of ayahuasca in humans

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    Ayahuasca is an Amazonian psychotropic plant tea typically obtained from two plants, Banisteriopsis caapi and Psychotria viridis. It contains the psychedelic 5-HT2A and sigma-1 agonist N,N-dimethyltryptamine (DMT) plus ß-carboline alkaloids with monoamine-oxidase (MAO)-inhibiting properties. Although the psychoactive effects of ayahuasca have commonly been attributed solely to agonism at the 5-HT2A receptor, the molecular target of classical psychedelics, this has not been tested experimentally. Here we wished to study the contribution of the 5-HT2A receptor to the neurophysiological and psychological effects of ayahuasca in humans. We measured drug-induced changes in spontaneous brain oscillations and subjective effects in a double-blind randomized placebo-controlled study involving the oral administration of ayahuasca (0.75 mg DMT/kg body weight) and the 5-HT2A antagonist ketanserin (40 mg). Twelve healthy, experienced psychedelic users (5 females) participated in four experimental sessions in which they received the following drug combinations: placebo+placebo, placebo+ayahuasca, ketanserin+placebo and ketanserin+ayahuasca. Ayahuasca induced EEG power decreases in the delta, theta and alpha frequency bands. Current density in alpha-band oscillations in parietal and occipital cortex was inversely correlated with the intensity of visual imagery induced by ayahuasca. Pretreatment with ketanserin inhibited neurophysiological modifications, reduced the correlation between alpha and visual effects, and attenuated the intensity of the subjective experience. These findings suggest that despite the chemical complexity of ayahuasca, 5-HT2A activation plays a key role in the neurophysiological and visual effects of ayahuasca in humans.Postprint (published version

    Post-movement Beta synchronization studied with linear estimation

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    Event-related desynchronization (ERS) describes a short-lasting and localized amplitude enhancement of specific frequency components. The spatial distribution of a post-movement beta ERS can be visualized by computing the local average reference (LAR). The Linear estimation (LE) method can also be applied to study the spatiotemporal ERS patterns. As source space an hemisphere was used with equally distributed radially oriented current dipoles. The lead field matrix is normalized to make sure that all dipoles have the same average impact on the sensors. A distributed source solution is found for each timestep and for each trial. Event-related Desynchronization calculations are carried out for every dipole (squaring of amplitude, averaging over all trials and time averaging over 16 time points). Both methods were conducted for the study of voluntary hand movement. The results are similar but in contrast to the LAR maps, the LE maps show a better spatial resolution. This is not surprising since the LAR method is limited to the electrode sites whereas with LE the EEG activity is projected onto the source space. Furthermore, the LE method counteracts the deblurring caused by the poorly conducting skull. Linear Estimation depends on several assumptions about the source space, volume conductor and the regularization parameter. Further investigation is needed to evaluate the application of LE for the study of Event-Related EEG phenomena

    A pharmaco-EEG study on antipsychotic drugs in healthy volunteers

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    Rationale: Both psychotropic drugs and mental disorders have typical signatures in quantitative electroencephalography (EEG). Previous studies found that some psychotropic drugs had EEG effects opposite to the EEG effects of the mental disorders treated with these drugs (key-lock principle). Objectives: We performed a placebo-controlled pharmaco-EEG study on two conventional antipsychotics (chlorpromazine and haloperidol) and four atypical antipsychotics (olanzapine, perospirone, quetiapine, and risperidone) in healthy volunteers. We investigated differences between conventional and atypical drug effects and whether the drug effects were compatible with the key-lock principle. Methods: Fourteen subjects underwent seven EEG recording sessions, one for each drug (dosage equivalent of 1mg haloperidol). In a time-domain analysis, we quantified the EEG by identifying clusters of transiently stable EEG topographies (microstates). Frequency-domain analysis used absolute power across electrodes and the location of the center of gravity (centroid) of the spatial distribution of power in different frequency bands. Results: Perospirone increased duration of a microstate class typically shortened in schizophrenics. Haloperidol increased mean microstate duration of all classes, increased alpha 1 and beta 1 power, and tended to shift the beta 1 centroid posterior. Quetiapine decreased alpha 1 power and shifted the centroid anterior in both alpha bands. Olanzapine shifted the centroid anterior in alpha 2 and beta 1. Conclusions: The increased microstate duration under perospirone and haloperidol was opposite to effects previously reported in schizophrenic patients, suggesting a key-lock mechanism. The opposite centroid changes induced by olanzapine and quetiapine compared to haloperidol might characterize the difference between conventional and atypical antipsychotic

    Coarse-grained entropy rates for characterization of complex time series

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    A method for classification of complex time series using coarse-grained entropy rates (CER's) is presented. The CER's, which are computed from information-theoretic functionals -- redundancies, are relative measures of regularity and predictability, and for data generated by dynamical systems they are related to Kolmogorov-Sinai entropy. A deterministic dynamical origin of the data under study, however, is not a necessary condition for the use of the CER's, since the entropy rates can be defined for stochastic processes as well. Sensitivity of the CER's to changes in data dynamics and their robustness with respect to noise are tested by using numerically generated time series resulted from both deterministic -- chaotic and stochastic processes. Potential application of the CER's in analysis of physiological signals or other complex time series is demonstrated by using examples from pharmaco-EEG and tremor classification.Comment: 15 pages, uuencoded compressed postscript file, figures embedded in the text, , <[email protected]

    Classification of electroencephalography for pain and pharmaco-EEG studies

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