Guidelines for the Recording and Evaluation of Pharmaco-EEG Data in Man: The International Pharmaco-EEG Society (IPEG)

Jobert, Marc; Wilson, Frederick J. F.; Ruigt, G.S.F.; Brunovský, Martin; Prichep, Leslie S.; Drinkenburg, Wilhelmus

doi:10.1159/000343478

Cited by 148 publications

(143 citation statements)

References 499 publications

(97 reference statements)

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“…This is important because the designation of canonical frequency bands (e.g., delta, theta, alpha, beta, gamma) has been subject to considerable variability (e.g., compare Kane 2017, to Jobert, 2012. We recommend the IFCN guidelines ( Kane 2017 ) for the delineation of frequency bands, as these remain close to the original frequency bands proposed by Berger in the late 1920s, Walter, and Jasper and Andrews in the 1930s ( Hari & Puce, 2017 ), and are consistent with those recommended in the main clinical textbook in the field ( Krishnan et al, 2018 ).…”

Section: Figuresmentioning

confidence: 99%

Best Practices in Data Analysis and Sharing in Neuroimaging using MEEG

Pernet¹,

Garrido²,

Gramfort³

et al. 2018

Preprint

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Neuroimaging methods, including magnetoencephalography and electroencephalography (MEEG), allow non-invasive collection of neural data in healthy people and in individuals with neurological or psychiatric disorders, with the aim of advancing the understanding of brain function in health and disease. Currently, scientific practice is undergoing a tremendous change, aiming to improve both research reproducibility and transparency in data collection, documentation and analysis, and in manuscript review. To advance the practice of open science, the Organization for Human Brain Mapping originally created the Committee on Best Practice in Data Analysis and Sharing (COBIDAS), which produced a report for MRI-based data. This effort continues with the OHBM's creation of a COBIDAS MEEG committee whose task is to create a similar document that describes best practice recommendations for MEEG data. The document has been drafted by OHBM experts in MEEG, with input from the brain imaging community including OHBM members who volunteered to help with this effort and executive committee members of the International Federation for Clinical Neurophysiology. This document outlines the principles of open and reproducible research in MEEG, and also applies these principles to specific research practices. Not all MEEG data practice is described in this document. Instead, we present information that we believe should be reported to fully understand and potentially replicate any study. We describe both good practice and reporting standards that ensure data collection and analysis will adhere to the highest standards. We also deal with issues of nomenclature and terminology which, due to the relatively long history of MEEG, have come about as different subfields emerged.

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Section: Figuresmentioning

confidence: 99%

Best Practices in Data Analysis and Sharing in Neuroimaging using MEEG

Pernet¹,

Garrido²,

Gramfort³

et al. 2018

Preprint

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“…Furthermore, it is possible to extract information on the relationships between areas of interest to assess how connectivity and flow of information is altered in the scalp potentials [38]. It would also be of great interest to attempt to identify the sources within the brain that generate the alterations in scalp potentials [6].…”

Section: Future Perspectivesmentioning

confidence: 99%

“…This could be accomplished in a placebo-controlled, crossover study in healthy volunteers treated with low-dose remifentanil, which enables comparison of EEG alterations during remifentanil treatment in comparison with alterations during placebo therapy. In such a low-dose set-up, the healthy volunteer would still be conscious and able to rate pain sensations and side effects.In order to extract relevant EEG alterations reflecting the spontaneous neural activity in the brain rather than the nociceptive response to an external stimulus, a feasible approach would be to record the EEG in resting condition [6,7]. Resting EEG is characterized by brain oscillations present in distinct frequency bands such as delta (0.5-4 Hz), theta (4-8 Hz), alpha (8)(9)(10)(11)(12) reflecting the sum of excitatory and inhibitory post-synaptic activities [8].…”

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confidence: 99%

“…In order to extract relevant EEG alterations reflecting the spontaneous neural activity in the brain rather than the nociceptive response to an external stimulus, a feasible approach would be to record the EEG in resting condition [6,7]. Resting EEG is characterized by brain oscillations present in distinct frequency bands such as delta (0.5-4 Hz), theta (4)(5)(6)(7)(8), alpha (8)(9)(10)(11)(12), beta and gamma reflecting the sum of excitatory and inhibitory post-synaptic activities [8].…”

mentioning

confidence: 99%

“…Resting EEG is characterized by brain oscillations present in distinct frequency bands such as delta (0.5-4 Hz), theta (4)(5)(6)(7)(8), alpha (8)(9)(10)(11)(12), beta and gamma reflecting the sum of excitatory and inhibitory post-synaptic activities [8]. However, as the oscillations are widely distributed in the brain, the scalp potentials provide distinct information depending on the site of the scalp.…”

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confidence: 99%

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Altered Frequency Distribution in the Electroencephalogram is Correlated to the Analgesic Effect of Remifentanil

Graversen

Malver

Kurita

et al. 2014

Basic Clin Pharma Tox

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Opioids alter resting state brain oscillations by multiple and complex factors, which are still to be elucidated. To increase our knowledge, multi-channel electroencephalography (EEG) was subjected to multivariate pattern analysis (MVPA), to identify the most descriptive frequency bands and scalp locations altered by remifentanil in healthy volunteers. Sixty-two channels of resting EEG followed by independent measures of pain scores to heat and bone pain were recorded in 21 healthy males before and during remifentanil infusion in a placebo-controlled, double-blind crossover study. EEG frequency distributions were extracted by a continuous wavelet transform and normalized into delta, theta, alpha, beta and gamma bands. Alterations relative to pre-treatment responses were calculated for all channels and used as input to the MVPA. Compared to placebo, remifentanil increased the delta band and decreased the theta and alpha band oscillations as a mean over all channels (all p ≤ 0.007). The most discriminative channels in these frequency bands were F1 in delta (83.33%, p = 0.0023) and theta bands (95.24%, p < 0.0001), and C6 in the alpha band (80.95%, p = 0.0054). These alterations were correlated to individual changes in heat pain in the delta (p = 0.045), theta (p = 0.038) and alpha (p = 0.039) bands and to bone pain in the alpha band (p = 0.0092). Hence, MVPA of multi-channel EEG was able to identify frequency bands and corresponding channels most sensitive to altered brain activity during remifentanil treatment. As the EEG alterations were correlated to the analgesic effect, the approach may prove to be a novel methodology for monitoring individual efficacy to opioids.Remifentanil is a selective l-receptor opioid agonist with short onset and duration of action [1,2]. This provides a remarkable titratability, which has proved useful for balanced anaesthesia and analgosedation as well as scientific research in experimental and clinical settings [3]. For scientific research on the underlying mechanisms of action of remifentanil, electroencephalography (EEG) provides information about the time course of electrical activity in the brain. This has been investigated in several previous studies, and the results indicate a relationship between EEG changes and the potency of remifentanil [4,5]. However, although the results of these studies have shed light on many of the underlying mechanisms of remifentanil, data are conflicting and the linkage between altered brain activity and the analgesic effect of remifentanil still remains unclear.Elucidation of the association between pain stimulation/measurement and altered EEG characteristics is therefore warranted. This could be accomplished in a placebo-controlled, crossover study in healthy volunteers treated with low-dose remifentanil, which enables comparison of EEG alterations during remifentanil treatment in comparison with alterations during placebo therapy. In such a low-dose set-up, the healthy volunteer would still be conscious and able to rate pain sensations...

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Effects of RF‐EMF on the Human Resting‐State EEG—the Inconsistencies in the Consistency. Part 1: Non‐Exposure‐Related Limitations of Comparability Between Studies

Danker‐Hopfe

Eggert

Dorn

et al. 2019

Bioelectromagnetics

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The results of studies on possible effects of radiofrequency electromagnetic fields (RF‐EMFs) on human waking electroencephalography (EEG) have been quite heterogeneous. In the majority of studies, changes in the alpha‐frequency range in subjects who were exposed to different signals of mobile phone‐related EMF sources were observed, whereas other studies did not report any effects. In this review, possible reasons for these inconsistencies are presented and recommendations for future waking EEG studies are made. The physiological basis of underlying brain activity, and the technical requirements and framework conditions for conducting and analyzing the human resting‐state EEG are discussed. Peer‐reviewed articles on possible effects of EMF on waking EEG were evaluated with regard to non‐exposure‐related confounding factors. Recommendations derived from international guidelines on the analysis and reporting of findings are proposed to achieve comparability in future studies. In total, 22 peer‐reviewed studies on possible RF‐EMF effects on human resting‐state EEG were analyzed. EEG power in the alpha frequency range was reported to be increased in 10, decreased in four, and not affected in eight studies. All reviewed studies differ in several ways in terms of the methodologies applied, which might contribute to different results and conclusions about the impact of EMF on human resting‐state EEG. A discussion of various study protocols and different outcome parameters prevents a scientifically sound statement on the impact of RF‐EMF on human brain activity in resting‐state EEG. Further studies which apply comparable, standardized study protocols are recommended. Bioelectromagnetics. 2019;40:291–318. © 2019 The Authors. Bioelectromagnetics Published by Wiley Periodicals, Inc.

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Guidelines for the Recording and Evaluation of Pharmaco-EEG Data in Man: The International Pharmaco-EEG Society (IPEG)

Cited by 148 publications

References 499 publications

Best Practices in Data Analysis and Sharing in Neuroimaging using MEEG

Best Practices in Data Analysis and Sharing in Neuroimaging using MEEG

Altered Frequency Distribution in the Electroencephalogram is Correlated to the Analgesic Effect of Remifentanil

Effects of RF‐EMF on the Human Resting‐State EEG—the Inconsistencies in the Consistency. Part 1: Non‐Exposure‐Related Limitations of Comparability Between Studies

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