The functional Val158Met polymorphism of COMT predicts interindividual differences in brain alpha oscillations in young men

Genetic Foundations of Inter-individual Neurophysiological Variability

Neurophysiological brain activity shapes cognitive functions and individual traits. Here, we investigated the extent to which individual neurophysiological properties are genetically determined and how these adult traits align with cortical gene expression patterns across development. Using task-free magnetoencephalography in monozygotic and dizygotic twins, as well as unrelated individuals, we found that neurophysiological traits were significantly more similar between monozygotic twins, indicating a genetic influence, although individual-specific variability remained predominant. These heritable brain dynamics were predominantly associated with genes involved in neurotransmission, expressed along a topographical gradient that mirrors psychological functions, including attention, planning, and emotional processes. Furthermore, the cortical expression patterns of genes associated with individual differentiation aligned most strongly with gene expression profiles observed during adulthood in previously published longitudinal datasets. These findings underscore a persistent genetic influence on neurophysiological activity, supporting individual cognitive and behavioral variability.

Peak alpha frequency and electroencephalographic microstates are correlated with aggression in schizophrenia

Large scale retrospective studies have shown an association between schizophrenia and risk of violence. Overall, this increase in risk is small and does not justify or support stigmatizing public perceptions or media depictions of people with schizophrenia. Nonetheless, in some situations, some symptoms of schizophrenia can increase the risk of violent behavior. Prediction of this behavior would allow high impact preventive interventions. However, to date the neurobiological correlates of violent behavior in schizophrenia are not well understood, precluding the development of prognostic biomarkers. We used electroencephalography to measure alpha activity and microstates from 31 patients with schizophrenia and 18 age matched controls. Participants also completed multiple assessments of current aggressive tendencies and their lifetime history of aggressive acts. We found that individual alpha peak frequency was negatively correlated with aggression scores in both patients and controls (largest Spearman's r = -0.45). Furthermore, this result could be replicated in data taken from a single frontal channel suggesting that this may be possible to obtain in routine clinical settings (largest Spearman's r = -0.40). We also found that transitions between microstates corresponding to auditory and visual networks were inversely correlated with aggression scores. Finally, we found that, within patients, aggression was correlated with the degree of randomness between microstate transitions. This suggests that aggression is related to inappropriate switching between large scale brain networks and subsequent failure to appropriately integrate complicated environmental and internal stimuli. By elucidating some of the electrophysiological correlates of aggression, these data facilitate the development of prognostic biomarkers.

The emergence of the EEG dominant rhythm across the first year of life

The spectral composition of EEG provides important information on the function of the developing brain. For example, the frequency of the dominant rhythm, a salient features of EEG data, increases from infancy to adulthood. Changes of the dominant rhythm during infancy are yet to be fully characterized, in terms of their developmental trajectory and spectral characteristics. In this study, the development of dominant rhythm frequency was examined during a novel sustained attention task across 6-month-old (n = 39), 9-month-old (n = 30), and 12-month-old (n = 28) infants. During this task, computer-generated objects and faces floated down a computer screen for 10 s after a 5-second fixation cross. The peak frequency in the range between 5 and 9 Hz was calculated using center of gravity (CoG) and examined in response to faces and objects. Results indicated that peak frequency increased from 6 to 9 to 12 months of age in face and object conditions. We replicated the same result for the baseline. There was high reliability between the CoGs in the face, object, and baseline conditions across all channels. The developmental increase in CoG was more reliable than measures of mode frequency across different conditions. These findings suggest that CoG is a robust index of brain development across infancy.

Unraveling Catechol-O-Methyltransferase rs4680 SNP's Role in Patients' Response to Tramadol and Its Adverse Effects: A Pharmacogenetics Insight into Postoperative Pain Management

Effective postoperative pain management is essential for patient well-being and an efficient healthcare system. Variations in the Catechol O-Methyltransferase (COMT) gene, specifically rs4680, play a crucial role in pain perception and opioid response. This study seeks to elucidate the impact of rs4680 polymorphism on tramadol efficacy and adverse reactions in post-surgical patients. We performed an uncontrolled cohort pharmacogenetics study in which participants underwent postoperative tramadol administration. The frequencies of rs4680 alleles were determined and the association between rs4680 genotypes and the efficacy of tramadol analgesic as pain relief, measured by the Numeric Rating Scale (NRS), was analyzed. Secondary outcomes included tramadol-induced sedation levels, opioid-induced nausea and vomiting, and other adverse effects of tramadol. Data analysis, using IBM SPSS Statistics 23, focused on pain and side effect differences across genotypes, with statistical significance set to p ≤ 0.05. The COMT (rs4680) genotype distribution exhibited a 'G' allele frequency of 41.5% and an 'A' allele frequency of 58.5%, with the AA genotype present in 44% of individuals, adhering to the Hardy-Weinberg equilibrium (p = 0.788). Patients with the AA genotype reported lower pain scores post-tramadol administration across all times examined (p < 0.001), but also experienced statistically significant (p < 0.001) higher incidences of tramadol-induced nausea, vomiting, and sedation. However, GG genotype individuals experienced poor pain relief from tramadol, requiring more supplemental analgesia. These significant findings underscore the critical role of COMT rs4680 polymorphism in response to tramadol and the necessity of a personalized approach to postoperative pain management.

Genetic polymorphisms in COMT and BDNF influence synchronization dynamics of human neuronal oscillations

Neuronal oscillations, their inter-areal synchronization, and scale-free dynamics constitute fundamental mechanisms for cognition by regulating communication in neuronal networks. These oscillatory dynamics have large inter-individual variability that is partly heritable. We hypothesized that this variability could be partially explained by genetic polymorphisms in neuromodulatory genes. We recorded resting-state magnetoencephalography (MEG) from 82 healthy participants and investigated whether oscillation dynamics were influenced by genetic polymorphisms in catechol-O-methyltransferase (COMT) Val158Met and brain-derived neurotrophic factor (BDNF) Val66Met. Both COMT and BDNF polymorphisms influenced local oscillation amplitudes and their long-range temporal correlations (LRTCs), while only BDNF polymorphism affected the strength of large-scale synchronization. Our findings demonstrate that COMT and BDNF genetic polymorphisms contribute to inter-individual variability in neuronal oscillation dynamics. Comparison of these results to computational modeling of near-critical synchronization dynamics further suggested that COMT and BDNF polymorphisms influenced local oscillations by modulating the excitation-inhibition balance according to the brain criticality framework.

Alzheimer's Disease with Epileptiform EEG Activity: Abnormal Cortical Sources of Resting State Delta Rhythms in Patients with Amnesic Mild Cognitive Impairment

BACKGROUND

Patients with amnesic mild cognitive impairment due to Alzheimer's disease (ADMCI) typically show a "slowing" of cortical resting-state eyes-closed electroencephalographic (rsEEG) rhythms. Some of them also show subclinical, non-convulsive, and epileptiform EEG activity (EEA) with an unclear relationship with that "slowing."

OBJECTIVE

Here we tested the hypothesis that the "slowing" of rsEEG rhythms is related to EEA in ADMCI patients.

METHODS

Clinical and instrumental datasets in 62 ADMCI patients and 38 normal elderly (Nold) subjects were available in a national archive. No participant had received a clinical diagnosis of epilepsy. The eLORETA freeware estimated rsEEG cortical sources. The area under the receiver operating characteristic curve (AUROCC) indexed the accuracy of eLORETA solutions in the classification between ADMCI-EEA and ADMCI-noEEA individuals.

RESULTS

EEA was observed in 15% (N = 8) of the ADMCI patients. The ADMCI-EEA group showed: 1) more abnormal Aβ 42 levels in the cerebrospinal fluid as compared to the ADMCI-noEEA group and 2) higher temporal and occipital delta (<4 Hz) rsEEG source activities as compared to the ADMCI-noEEA and Nold groups. Those source activities showed moderate accuracy (AUROCC = 0.70-0.75) in the discrimination between ADMCI-noEEA versus ADMCI-EEA individuals.

CONCLUSION

It can be speculated that in ADMCI-EEA patients, AD-related amyloid neuropathology may be related to an over-excitation in neurophysiological low-frequency (delta) oscillatory mechanisms underpinning cortical arousal and quiet vigilance.

Brief segments of neurophysiological activity enable individual differentiation

Large, openly available datasets and current analytic tools promise the emergence of population neuroscience. The considerable diversity in personality traits and behaviour between individuals is reflected in the statistical variability of neural data collected in such repositories. Recent studies with functional magnetic resonance imaging (fMRI) have concluded that patterns of resting-state functional connectivity can both successfully distinguish individual participants within a cohort and predict some individual traits, yielding the notion of an individual's neural fingerprint. Here, we aim to clarify the neurophysiological foundations of individual differentiation from features of the rich and complex dynamics of resting-state brain activity using magnetoencephalography (MEG) in 158 participants. We show that akin to fMRI approaches, neurophysiological functional connectomes enable the differentiation of individuals, with rates similar to those seen with fMRI. We also show that individual differentiation is equally successful from simpler measures of the spatial distribution of neurophysiological spectral signal power. Our data further indicate that differentiation can be achieved from brain recordings as short as 30 seconds, and that it is robust over time: the neural fingerprint is present in recordings performed weeks after their baseline reference data was collected. This work, thus, extends the notion of a neural or brain fingerprint to fast and large-scale resting-state electrophysiological dynamics.

Individual alpha peak frequency is slower in schizophrenia and related to deficits in visual perception and cognition

The brain at rest generates cycles of electrical activity that have been shown to be abnormal in people with schizophrenia. The alpha rhythm (~ 10 Hz) is the dominant resting state electrical cycle and each person has a propensity toward a particular frequency of oscillation for this rhythm. This individual alpha peak frequency (IAPF) is hypothesized to be central to visual perceptual processes and may have downstream influences on cognitive functions such as attention, working memory, or problem solving. In the current study we sought to determine whether IAPF was slower in schizophrenia, and whether lower IAPF predicted deficits in visual perception and cognition that are often observed in schizophrenia. Eyes-closed resting state EEG activity, visual attention, and global cognitive functioning were assessed in individuals with schizophrenia (N = 104) and a group of healthy controls (N = 101). Compared to controls, the schizophrenia group showed slower IAPF and was associated with poorer discrimination of visual targets and nontargets on a computerized attention task, as well as impaired global cognition measured using neuropsychological tests across groups. Notably, disruptions in visual attention fully mediated the relationship between IAPF and global cognition across groups. The current findings demonstrate that slower alpha oscillatory cycling accounts for global cognitive deficits in schizophrenia by way of impairments in perceptual discrimination measured during a visual attention task.

Calibrating rhythmic stimulation parameters to individual EEG markers: the consistency of individual alpha frequency in practical lab settings

Rhythmic stimulation can be applied to modulate neuronal oscillations. Such 'entrainment' is optimized when stimulation frequency is individually-calibrated based on magneto/encephalography markers. It remains unknown how consistent such individual markers are across days/sessions, within a session, or across cognitive states, hemispheres, and estimation methods, especially in a realistic, practical, lab setting. We here estimated individual alpha frequency (IAF) repeatedly from short EEG measurements at rest or during an attention task (cognitive state), using single parieto-occipital electrodes in 24 participants on four days (between-sessions), with multiple measurements over an hour on one day (within-session). First, we introduce an algorithm to automatically reject power spectra without a sufficiently clear peak to ensure unbiased IAF estimations. Then we estimated IAF via the traditional 'maximum' method and a 'Gaussian fit' method. IAF was reliable within- and between-sessions for both cognitive states and hemispheres, though task-IAF estimates tended to be more variable. Overall, the 'Gaussian fit' method was more reliable than the 'maximum' method. Furthermore, we evaluated how far from an approximated 'true' task-related IAF the selected 'stimulation frequency' was, when calibrating this frequency based on a short rest-EEG, a short task-EEG, or simply selecting 10Hertz for all participants. For the 'maximum' method, rest-EEG calibration was best, followed by task-EEG, and then 10 Hertz. For the 'Gaussian fit' method, rest-EEG and task-EEG-based calibration were similarly accurate, and better than 10 Hertz. These results lead to concrete recommendations about valid, and automated, estimation of individual oscillation markers in experimental and clinical settings.

No evidence for a single oscillator underlying discrete visual percepts

Theories of perception based on discrete sampling posit that visual consciousness is reconstructed based on snapshot-like perceptual moments, as opposed to being updated continuously. According to a model proposed by Schneider (2018), discrete sampling can explain both the flash-lag and the Fröhlich illusion, whereby a lag in the conscious updating of a moving stimulus alters its perceived spatial location in comparison to stationary stimulus. The alpha-band frequency, which is associated with phasic modulation of stimulus detection and the temporal resolution of perception, has been proposed to reflect the duration of perceptual moments. The goal of this study was to determine whether a single oscillator (e.g., alpha) is underlying the duration of perceptual moments, which would predict that the point of subjective equality (PSE) in the flash-lag and Fröhlich illusions are positively correlated across individuals. Although our displays induced robust flash-lag and Fröhlich effects, virtually zero correlation was seen between the PSE in the two illusions, indicating that the illusion magnitudes are unrelated across observers. These findings suggest that, if discrete sampling theory is true, these illusory percepts either rely on different oscillatory frequencies or not on oscillations at all. Alternatively, discrete sampling may not be the mechanism underlying these two motion illusions or our methods were ill-suited to test the theory.

Genetic Determinants of Neurobehavioral Responses to Caffeine Administration during Sleep Deprivation: A Randomized, Cross Over Study (NCT03859882)

This study investigated whether four single nucleotide polymorphisms (SNPs) moderated caffeine effects on vigilance and performance in a double-blind and crossover total sleep deprivation (TSD) protocol in 37 subjects. In caffeine (2 × 2.5 mg/kg/24 h) or placebo-controlled condition, subjects performed a psychomotor vigilance test (PVT) and reported sleepiness every six hours (Karolinska sleepiness scale (KSS)) during TSD. EEG was also analyzed during the 09:15 PVT. Carriers of the TNF-α SNP A allele appear to be more sensitive than homozygote G/G genotype to an attenuating effect of caffeine on PVT lapses during sleep deprivation only because they seem more degraded, but they do not perform better as a result. The A allele carriers of COMT were also more degraded and sensitive to caffeine than G/G genotype after 20 h of sleep deprivation, but not after 26 and 32 h. Regarding PVT reaction time, ADORA2A influences the TSD effect but not caffeine, and PER3 modulates only the caffeine effect. Higher EEG theta activity related to sleep deprivation was observed in mutated TNF-α, PER3, and COMT carriers, in the placebo condition particularly. In conclusion, there are genetic influences on neurobehavioral impairments related to TSD that appear to be attenuated by caffeine administration. (NCT03859882).

Abnormalities of Cortical Sources of Resting State Delta Electroencephalographic Rhythms Are Related to Epileptiform Activity in Patients With Amnesic Mild Cognitive Impairment Not Due to Alzheimer's Disease

In the present exploratory and retrospective study, we hypothesized that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms might be more abnormal in patients with epileptiform EEG activity (spike-sharp wave discharges, giant spikes) and amnesic mild cognitive impairment not due to Alzheimer's disease (noADMCI-EEA) than matched noADMCI patients without EEA (noADMCI-noEEA). Clinical, neuroimaging, neuropsychological, and rsEEG data in 32 noADMCI and 30 normal elderly (Nold) subjects were available in a national archive. Age, gender, and education were carefully matched among them. No subject had received a clinical diagnosis of epilepsy. Individual alpha frequency peak (IAF) was used to determine the delta, theta, and alpha frequency bands of rsEEG rhythms. Fixed beta and gamma bands were also considered. Regional rsEEG cortical sources were estimated by eLORETA freeware. Area under receiver operating characteristic (AUROC) curves indexed the accuracy of eLORETA solutions in the classification between noADMCI-EEA and noADMCI-noEEA individuals. As novel findings, EEA was observed in 41% of noADMCI patients. Furthermore, these noADMCI-EEA patients showed higher temporal delta source activities as compared to noADMCI-no EEA patients and Nold subjects. Those activities discriminated individuals of the two NoADMCI groups with an accuracy of about 70%. The significant percentage of noADMCI-EEA patients showing EEA and marked abnormalities in temporal rsEEG rhythms at delta frequencies suggest a substantial role of underlying neural hypersynchronization mechanisms in their brain dysfunctions.

Abnormalities of resting-state EEG in patients with prodromal and overt dementia with Lewy bodies: Relation to clinical symptoms

OBJECTIVE

Here we tested if cortical sources of resting state electroencephalographic (rsEEG) rhythms may differ in sub-groups of patients with prodromal and overt dementia with Lewy bodies (DLB) as a function of relevant clinical symptoms.

METHODS

We extracted clinical, demographic and rsEEG datasets in matched DLB patients (N = 60) and control Alzheimer's disease (AD, N = 60) and healthy elderly (Nold, N = 60) seniors from our international database. The eLORETA freeware was used to estimate cortical rsEEG sources.

RESULTS

As compared to the Nold group, the DLB and AD groups generally exhibited greater spatially distributed delta source activities (DLB > AD) and lower alpha source activities posteriorly (AD > DLB). As compared to the DLB "controls", the DLB patients with (1) rapid eye movement (REM) sleep behavior disorders showed lower central alpha source activities (p < 0.005); (2) greater cognitive deficits exhibited higher parietal and central theta source activities as well as higher central, parietal, and occipital alpha source activities (p < 0.01); (3) visual hallucinations pointed to greater parietal delta source activities (p < 0.005).

CONCLUSIONS

Relevant clinical features were associated with abnormalities in spatial and frequency features of rsEEG source activities in DLB patients.

SIGNIFICANCE

Those features may be used as neurophysiological surrogate endpoints of clinical symptoms in DLB patients in future cross-validation prospective studies.

Inter- and Intra-individual Variability in Brain Oscillations During Sports Motor Imagery

The aim of this work was to re-evaluate electrophysiological data from a previous study on motor imagery (MI) with a special focus on observed inter- and intra-individual differences. More concretely, we investigated event-related desynchronization/synchronization patterns during sports MI (playing tennis) compared with simple MI (squeezing a ball) and discovered high variability across participants. Thirty healthy volunteers were divided in two groups; the experimental group (EG) performed a physical exercise between two imagery sessions, and the control group (CG) watched a landscape movie without physical activity. We computed inter-individual differences by assessing the dissimilarities among subjects for each group, condition, time period, and frequency band. In the alpha band, we observe some clustering in the ranking of the subjects, therefore showing smaller distances than others. Moreover, in our statistical evaluation, we observed a consistency in ranking across time periods both for the EG and for the CG. For the latter, we also observed similar rankings across conditions. On the contrary, in the beta band, the ranking of the subjects was more similar for the EG across conditions and time periods than for the subjects of the CG. With this study, we would like to draw attention to variability measures instead of primarily focusing on the identification of common patterns across participants, which often do not reflect the whole neurophysiological reality.

Rapid fast-delta decay following prolonged wakefulness marks a phase of wake-inertia in NREM sleep

Sleep-wake driven changes in non-rapid-eye-movement sleep (NREM) sleep (NREMS) EEG delta (δ-)power are widely used as proxy for a sleep homeostatic process. Here, we noted frequency increases in δ-waves in sleep-deprived mice, prompting us to re-evaluate how slow-wave characteristics relate to prior sleep-wake history. We identified two classes of δ-waves; one responding to sleep deprivation with high initial power and fast, discontinuous decay during recovery sleep (δ2) and another unrelated to time-spent-awake with slow, linear decay (δ1). Reanalysis of previously published datasets demonstrates that δ-band heterogeneity after sleep deprivation is also present in human subjects. Similar to sleep deprivation, silencing of centromedial thalamus neurons boosted subsequent δ2-waves, specifically. δ2-dynamics paralleled that of temperature, muscle tone, heart rate, and neuronal ON-/OFF-state lengths, all reverting to characteristic NREMS levels within the first recovery hour. Thus, prolonged waking seems to necessitate a physiological recalibration before typical NREMS can be reinstated.

Changes in EEG delta-activity are widely used as proxy of sleep propensity. Here the authors demonstrate in mice and humans the presence of two types of delta-waves, only one of which reports on prior sleep-wake history with dynamics denoting a wake-inertia process accompanying deepest non-rapid-eye-movement sleep (NREM) sleep.

Topographic specificity of alpha power during auditory spatial attention

Visual and somatosensory spatial attention both induce parietal alpha (8-14 ​Hz) oscillations whose topographical distribution depends on the direction of spatial attentional focus. In the auditory domain, contrasts of parietal alpha power for leftward and rightward attention reveal qualitatively similar lateralization; however, it is not clear whether alpha lateralization changes monotonically with the direction of auditory attention as it does for visual spatial attention. In addition, most previous studies of alpha oscillation did not consider individual differences in alpha frequency, but simply analyzed power in a fixed spectral band. Here, we recorded electroencephalography in human subjects when they directed attention to one of five azimuthal locations. After a cue indicating the direction of an upcoming target sequence of spoken syllables (yet before the target began), alpha power changed in a task-specific manner. Individual peak alpha frequencies differed consistently between central electrodes and parieto-occipital electrodes, suggesting multiple neural generators of task-related alpha. Parieto-occipital alpha increased over the hemisphere ipsilateral to attentional focus compared to the contralateral hemisphere, and changed systematically as the direction of attention shifted from far left to far right. These results showing that parietal alpha lateralization changes smoothly with the direction of auditory attention as in visual spatial attention provide further support to the growing evidence that the frontoparietal attention network is supramodal.

Effect of mobile phone radiofrequency signal on the alpha rhythm of human waking EEG: A review

In response to the exponential increase in mobile phone use and the resulting increase in exposure to radiofrequency electromagnetic fields (RF-EMF), there have been several studies to investigate via electroencephalography (EEG) whether RF-EMF exposure affects brain activity. Data in the literature have shown that exposure to radiofrequency signals modifies the waking EEG with the main effect on the alpha band frequency (8-13 Hz). However, some studies have reported an increase in alpha band power, while others have shown a decrease, and other studies showed no effect on EEG power. Given that changes in the alpha amplitude are associated with attention and some cognitive aspects of human behavior, researchers deemed necessary to look whether alpha rhythm was modulated under RF-EMF exposure. The present review aims at comparing and discussing the main findings obtained so far regarding RF-EMF effects on alpha rhythm of human waking spontaneous EEG, focusing on differences in protocols between studies, which might explain the observed discrepancies and inconclusive results.

Sleep deprivation and Modafinil affect cortical sources of resting state electroencephalographic rhythms in healthy young adults

OBJECTIVE

It has been reported that sleep deprivation affects the neurophysiological mechanisms underpinning the vigilance. Here, we tested the following hypotheses in the PharmaCog project (www.pharmacog.org): (i) sleep deprivation may alter posterior cortical delta and alpha sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms in healthy young adults; (ii) after the sleep deprivation, a vigilance enhancer may recover those rsEEG source markers.

METHODS

rsEEG data were recorded in 36 healthy young adults before (Pre-sleep deprivation) and after (Post-sleep deprivation) one night of sleep deprivation. In the Post-sleep deprivation, these data were collected after a single dose of PLACEBO or MODAFINIL. rsEEG cortical sources were estimated by eLORETA freeware.

RESULTS

In the PLACEBO condition, the sleep deprivation induced an increase and a decrease in posterior delta (2-4 Hz) and alpha (8-13 Hz) source activities, respectively. In the MODAFINIL condition, the vigilance enhancer partially recovered those source activities.

CONCLUSIONS

The present results suggest that posterior delta and alpha source activities may be both related to the regulation of human brain arousal and vigilance in quiet wakefulness.

SIGNIFICANCE

Future research in healthy young adults may use this methodology to preselect new symptomatic drug candidates designed to normalize brain arousal and vigilance in seniors with dementia.

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

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.

Clinical and Experimental Human Sleep-Wake Pharmacogenetics

Sleep and wakefulness are highly complex processes that are elegantly orchestrated by fine-tuned neurochemical changes among neuronal and non-neuronal ensembles, nuclei, and networks of the brain. Important neurotransmitters and neuromodulators regulating the circadian and homeostatic facets of sleep-wake physiology include melatonin, γ-aminobutyric acid, hypocretin, histamine, norepinephrine, serotonin, dopamine, and adenosine. Dysregulation of these neurochemical systems may cause sleep-wake disorders, which are commonly classified into insomnia disorder, parasomnias, circadian rhythm sleep-wake disorders, central disorders of hypersomnolence, sleep-related movement disorders, and sleep-related breathing disorders. Sleep-wake disorders can have far-reaching consequences on physical, mental, and social well-being and health and, thus, need be treated with effective and rational therapies. Apart from behavioral (e.g., cognitive behavioral therapy for insomnia), physiological (e.g., chronotherapy with bright light), and mechanical (e.g., continuous positive airway pressure treatment of obstructive sleep apnea) interventions, pharmacological treatments often are the first-line clinical option to improve disturbed sleep and wake states. Nevertheless, not all patients respond to pharmacotherapy in uniform and beneficial fashion, partly due to genetic differences. The improved understanding of the neurochemical mechanisms regulating sleep and wakefulness and the mode of action of sleep-wake therapeutics has provided a conceptual framework, to search for functional genetic variants modifying individual drug response phenotypes. This article will summarize the currently known genetic polymorphisms that modulate drug sensitivity and exposure, to partly determine individual responses to sleep-wake pharmacotherapy. In addition, a pharmacogenetic strategy will be outlined how based upon classical and opto-/chemogenetic strategies in animals, as well as human genetic associations, circuit mechanisms regulating sleep-wake functions in humans can be identified. As such, experimental human sleep-wake pharmacogenetics forms a bridge spanning basic research and clinical medicine and constitutes an essential step for the search and development of novel sleep-wake targets and therapeutics.

Interrogating the Relationship Between Schizotypy, the Catechol-O-Methyltransferase (COMT) Val158Met Polymorphism, and Neuronal Oscillatory Activity

The COMT Val158Met polymorphism affects the availability of synaptic dopamine in the prefrontal cortex and has been widely studied as a genetic risk factor for psychosis. Schizotypy is associated with an increased risk of psychosis, with some studies implicating similar neurobiological mechanisms to schizophrenia. The present study sought to interrogate the link between the COMT Val158Met polymorphism and schizotypy using electroencephalogram (EEG) to identify neurophysiological mechanisms underpinning psychosis risk. Neurotypical (N = 91) adults were genotyped for the COMT Val158Met polymorphism, completed the Schizotypal Personality Questionnaire (SPQ), and had eyes open resting-state EEG recorded for 4 min. SPQ suspiciousness subscale scores were higher for individuals homozygous for Val/Val and Met/Met versus Val/Met genotypes. Delta, theta, alpha-2, beta-1, and beta-2 amplitudes were lower for Val/Val than Met/Met individuals. Lower theta amplitudes were correlated with higher total SPQ scores (P = 0.050), and multiple regression revealed that higher delta, and lower theta and beta-2 amplitudes (but not COMT genotype) best predicted total SPQ scores (P = 0.014). This study demonstrates the importance of COMT genotype in determining trait suspiciousness and EEG oscillatory activity. It also highlights relationships between dopaminergic alterations, EEG and schizotypy that are dissimilar to those observed in schizophrenia.

On the Physiological Modulation and Potential Mechanisms Underlying Parieto-Occipital Alpha Oscillations

The parieto-occipital alpha (8–13 Hz) rhythm is by far the strongest spectral fingerprint in the human brain. Almost 90 years later, its physiological origin is still far from clear. In this Research Topic I review human pharmacological studies using electroencephalography (EEG) and magnetoencephalography (MEG) that investigated the physiological mechanisms behind posterior alpha. Based on results from classical and recent experimental studies, I find a wide spectrum of drugs that modulate parieto-occipital alpha power. Alpha frequency is rarely affected, but this might be due to the range of drug dosages employed. Animal and human pharmacological findings suggest that both GABA enhancers and NMDA blockers systematically decrease posterior alpha power. Surprisingly, most of the theoretical frameworks do not seem to embrace these empirical findings and the debate on the functional role of alpha oscillations has been polarized between the inhibition vs. active poles hypotheses. Here, I speculate that the functional role of alpha might depend on physiological excitation as much as on physiological inhibition. This is supported by animal and human pharmacological work showing that GABAergic, glutamatergic, cholinergic, and serotonergic receptors in the thalamus and the cortex play a key role in the regulation of alpha power and frequency. This myriad of physiological modulations fit with the view that the alpha rhythm is a complex rhythm with multiple sources supported by both thalamo-cortical and cortico-cortical loops. Finally, I briefly discuss how future research combining experimental measurements derived from theoretical predictions based of biophysically realistic computational models will be crucial to the reconciliation of these disparate findings.

Catechol-O-methyltransferase Gene Polymorphism (Val158Met) and Development of Pre-eclampsia

OBJECTIVES

Catechol-O-methyltransferase (COMT) is a key enzyme in degradation pathways of estrogens and catecholamines. The present meta-analysis was done to elucidate the association of COMT Val158Met polymorphism with pre-eclampsia among pregnant women.

METHODS

A literature search was conducted in electronic databases including PubMed, Scopus, Elsevier, Springer and Google Scholar to find eligible studies. The pooled odds ratios (ORs) with 95% confidence intervals were calculated under dominant, recessive, co-dominant, and allelic models.

RESULTS

This meta-analysis included 6 eligible studies consisting 2596 cases and 4223 controls. The ORs for the COMT G472A polymorphism and pre-eclampsia were indicative of positive association under several genetic models. The results indicated that COMT Val158Met polymorphism was significantly associated with the increased risk of pre-eclampsia in recessive model (AA vs. AG + GG: OR = 1.522 [95% CI: 1.089-2.127]; p = 0.014), co-dominant model (AA vs. GG: OR = 1.605 [95% CI: 1.102-2.336]; p = 0.014), and allelic model (A vs. T: OR = 1.200 [95% CI: 1.021-1.402]; p = 0.021).

CONCLUSIONS

In summary, COMT Val158Met polymorphism is positively associated with the increased risk of pre-eclampsia among pregnant women, especially the homozygous carriers. It could be of value to investigate its association with pre-eclampsia in combination with additional risk factors. However, very large studies with different ethnic population are required to accurately demonstrate the role of this candidate gene in development of pre-eclampsia.

Individual Alpha Peak Frequency in Ice Hockey Shooting Performance

There are several important inter- and intra-individual variations in individual alpha peak frequency (IAPF) in the cognitive domain. The rationale for the present study was to extend the research on IAPF in the cognitive domain to IAPF in the sport domain. Specifically, the purpose of the present study was twofold: (a) to explore whether baseline IAPF is related to performance in an ice hockey shooting task and (b) to explore whether a shooting task has an effect on IAPF variability. The present investigation is one of the first studies to examine links between IAPF and sport performance. Study results did not show significant changes in IAPF when comparing baseline IAPF and pre- to post-task IAPF across three performance levels. The findings support previous literature in the cognitive domain suggesting that IAPF is a stable neurophysiological marker. Future research should consider the following methodological suggestions: (a) measuring IAPF during sport performance instead of at a resting state, (b) changing the pre-performance resting baseline instructions to take into account sport-specific mental preparation,

Dynamic spatiotemporal variability of alpha-BOLD relationships during the resting-state and task-evoked responses

Accurate characterization of the spatiotemporal relationship between two of the most prominent neuroimaging measures of neuronal activity, the 8-13Hz, occipito-parietal EEG alpha oscillation and the BOLD fMRI signal, must encompass the intrinsically dynamic nature of both alpha power and brain function. Here, during the eyes-open resting state, we use a 16s sliding-window analysis and demonstrate that the mean spatial network of dynamic alpha-BOLD correlations is highly comparable to the static network calculated over six minutes. However, alpha-BOLD correlations showed substantial spatiotemporal variability within-subjects and passed through many different configurations such that the static network was fully represented in only ~10% of 16s epochs, with visual and parietal regions (coherent on average) often opposingly correlated with each other or with alpha. We find that the common assumption of static-alpha BOLD correlations greatly oversimplifies temporal variation in brain network dynamics. Fluctuations in alpha-BOLD coupling significantly depended upon the instantaneous amplitude of alpha power, and primary and lateral visual areas were most strongly negatively correlated with alpha during different alpha power states, possibly suggesting the action of multiple alpha mechanisms. Dynamic alpha-BOLD correlations could not be explained by eye-blinks/movements, head motion or non-neuronal physiological variability. Individual's mean alpha power and frequency were found to contribute to between-subject variability in alpha-BOLD correlations. Additionally, application to a visual stimulation dataset showed that dynamic alpha-BOLD correlations provided functional information pertaining to the brain's response to stimulation by exhibiting spatiotemporal fluctuations related to variability in the trial-by-trial BOLD response magnitude. Significantly weaker visual alpha-BOLD correlations were found both preceding and following small amplitude BOLD response trials compared to large response trials.

Functional Polymorphisms in Dopaminergic Genes Modulate Neurobehavioral and Neurophysiological Consequences of Sleep Deprivation

Sleep deprivation impairs cognitive performance and reliably alters brain activation in wakefulness and sleep. Nevertheless, the molecular regulators of prolonged wakefulness remain poorly understood. Evidence from genetic, behavioral, pharmacologic and imaging studies suggest that dopaminergic signaling contributes to the behavioral and electroencephalographic (EEG) consequences of sleep loss, although direct human evidence thereof is missing. We tested whether dopamine neurotransmission regulate sustained attention and evolution of EEG power during prolonged wakefulness. Here, we studied the effects of functional genetic variation in the dopamine transporter (DAT1) and the dopamine D₂ receptor (DRD2) genes, on psychomotor performance and standardized waking EEG oscillations during 40 hours of wakefulness in 64 to 82 healthy volunteers. Sleep deprivation consistently enhanced sleepiness, lapses of attention and the theta-to-alpha power ratio (TAR) in the waking EEG. Importantly, DAT1 and DRD2 genotypes distinctly modulated sleep loss-induced changes in subjective sleepiness, PVT lapses and TAR, according to inverted U-shaped relationships. Together, the data suggest that genetically determined differences in DAT1 and DRD2 expression modulate functional consequences of sleep deprivation, supporting the hypothesis that striato-thalamo-cortical dopaminergic pathways modulate the neurobehavioral and neurophysiological consequences of sleep loss in humans.

Acute effects of cocaine and cannabis on reversal learning as a function of COMT and DRD2 genotype

RATIONALE

Long-term cannabis and cocaine use has been associated with impairments in reversal learning. However, how acute cannabis and cocaine administration affect reversal learning in humans is not known.

OBJECTIVE

In this study, we aimed to establish the acute effects of administration of cannabis and cocaine on valence-dependent reversal learning as a function of DRD2 Taq1A (rs1800497) and COMT Val108/158Met (rs4680) genotype.

METHODS

A double-blind placebo-controlled randomized 3-way crossover design was used. Sixty-one regular poly-drug users completed a deterministic reversal learning task under the influence of cocaine, cannabis, and placebo that enabled assessment of both reward- and punishment-based reversal learning.

RESULTS

Proportion correct on the reversal learning task was increased by cocaine, but decreased by cannabis. Effects of cocaine depended on the DRD2 genotype, as increases in proportion correct were seen only in the A1 carriers, and not in the A2/A2 homozygotes. COMT genotype did not modulate drug-induced effects on reversal learning.

CONCLUSIONS

These data indicate that acute administration of cannabis and cocaine has opposite effects on reversal learning. The effects of cocaine, but not cannabis, depend on interindividual genetic differences in the dopamine D2 receptor gene.

Heritability and molecular-genetic basis of resting EEG activity: a genome-wide association study

Several EEG parameters are potential endophenotypes for different psychiatric disorders. The present study consists of a comprehensive behavioral- and molecular-genetic analysis of such parameters in a large community sample (N = 4,026) of adolescent twins and their parents, genotyped for 527,829 single nucleotide polymorphisms (SNPs). Biometric heritability estimates ranged from .49 to .85, with a median of .78. The additive effect of all SNPs (SNP heritability) varied across electrodes. Although individual SNPs were not significantly associated with EEG parameters, several genes were associated with delta power. We also obtained an association between the GABRA2 gene and beta power (p < .014), consistent with findings reported by others, although this did not survive Bonferroni correction. If EEG parameters conform to a largely polygenic model of inheritance, larger sample sizes will be required to detect individual variants reliably.

COMT polymorphism modulates the resting-state EEG alpha oscillatory response to acute nicotine in male non-smokers

Performance improvements in cognitive tasks requiring executive functions are evident with nicotinic acetylcholine receptor (nAChR) agonists, and activation of the underlying neural circuitry supporting these cognitive effects is thought to involve dopamine neurotransmission. As individual difference in response to nicotine may be related to a functional polymorphism in the gene encoding catechol-O-methyltransferase (COMT), an enzyme that strongly influences cortical dopamine metabolism, this study examined the modulatory effects of the COMT Val158Met polymorphism on the neural response to acute nicotine as measured with resting-state electroencephalographic (EEG) oscillations. In a sample of 62 healthy non-smoking adult males, a single dose (6 mg) of nicotine gum administered in a randomized, double-blind, placebo-controlled design was shown to affect α oscillatory activity, increasing power of upper α oscillations in frontocentral regions of Met/Met homozygotes and in parietal/occipital regions of Val/Met heterozygotes. Peak α frequency was also found to be faster with nicotine (vs. placebo) treatment in Val/Met heterozygotes, who exhibited a slower α frequency compared to Val/Val homozygotes. The data tentatively suggest that interindividual differences in brain α oscillations and their response to nicotinic agonist treatment are influenced by genetic mechanisms involving COMT.

Modulation of the COMT Val(158)Met polymorphism on resting-state EEG power

The catechol-O-methyltransferase (COMT) Val(158)Met polymorphism impacts cortical dopamine (DA) levels and may influence cortical electrical activity in the human brain. This study investigated whether COMT genotype influences resting-state electroencephalogram (EEG) power in the frontal, parietal and midline regions in healthy volunteers. EEG recordings were conducted in the resting-state in 13 postmenopausal healthy woman carriers of the Val/Val genotype and 11 with the Met/Met genotype. The resting EEG spectral absolute power in the frontal (F3, F4, F7, F8, FC3 and FC4), parietal (CP3, CP4, P3 and P4) and midline (Fz, FCz, Cz, CPz, Pz and Oz) was analyzed during the eyes-open and eyes-closed conditions. The frequency bands considered were the delta, theta, alpha1, alpha2, beta1 and beta2. EEG data of the Val/Val and Met/Met genotypes, brain regions and conditions were analyzed using a general linear model analysis. In the individuals with the Met/Met genotype, delta activity was increased in the eyes-closed condition, theta activity was increased in the eyes-closed and in the eyes-open conditions, and alpha1 band, alpha2 band and beta1band activity was increased in the eyes-closed condition. A significant interaction between COMT genotypes and spectral bands was observed. Met homozygote individuals exhibited more delta, theta and beta1 activity than individuals with the Val/Val genotype. No significant interaction between COMT genotypes and the resting-state EEG regional power and conditions were observed for the three brain regions studied. Our findings indicate that the COMT Val(158)Met polymorphism does not directly impact resting-state EEG regional power, but instead suggest that COMT genotype can modulate resting-state EEG spectral power in postmenopausal healthy women.

Association between COMT Val158Met genotype and EEG alpha peak frequency tested in two independent cohorts

This study could not confirm the association between the Catechol-O-Methyltransferase Val158Met polymorphism (COMT) and electroencephalographic (EEG) alpha peak frequency (APF) in two independent cohorts of 187 (96 depressed and 91 healthy participants) and 413 healthy participants. If COMT and APF play a role in depression or antidepressant treatment response, they do not have a shared pathway. We emphasize the importance of publishing null-findings for obtaining more accurate overall estimates of genetic effects.

Inter- and intra-individual variability in alpha peak frequency

Converging electrophysiological evidence suggests that the alpha rhythm plays an important and active role in cognitive processing. Here, we systematically studied variability in posterior alpha peak frequency both between and within subjects. We recorded brain activity using MEG in 51 healthy human subjects under three experimental conditions - rest, passive visual stimulation and an N-back working memory paradigm, using source reconstruction methods to separate alpha activity from parietal and occipital sources. We asked how alpha peak frequency differed within subjects across cognitive conditions and regions of interest, and looked at the distribution of alpha peak frequency between subjects. In both regions we observed an increase of alpha peak frequency from resting state and passive visual stimulation conditions to the N-back paradigm, with a significantly higher alpha peak frequency in the 2-back compared to the 0-back condition. There was a trend for a greater increase in alpha peak frequency during the N-back task in the occipital vs. parietal cortex. The average alpha peak frequency across all subjects, conditions, and regions of interest was 10.3 Hz with a within-subject SD of 0.9 Hz and a between-subject SD of 2.8 Hz. We also measured beta peak frequencies, and except in the parietal cortex during rest, found no indication of a strictly harmonic relationship with alpha peak frequencies. We conclude that alpha peak frequency in posterior regions increases with increasing cognitive demands, and that the alpha rhythm operates across a wider frequency range than the 8-12 Hz band many studies tend to include in their analysis. Thus, using a fixed and limited alpha frequency band might bias results against certain subjects and conditions.

Contribution of neurophysiological endophenotype, individual frequency of EEG alpha oscillations, to mechanisms of emotional reactivity

We studied the relationship between individual alpha frequency (IAF) of EEG (neurophysiological endophenotype reflecting individual predisposition to efficacious cognitive and creative activity) and individual emotional reactivity. The psychophysiological study included healthy men in two models of evoked emotions - anxious apprehension (awaiting of inescapable aversive punishment) and discrete (opposite) emotions. Analysis of self-report, multichannel EEG, galvanic skin response, and cardiovascular reactivity showed that individuals with high IAF are characterized by predominance of parasympathetic influences in autonomic regulation circuit, proactive strategies of coping with inescapable threat, higher activity of positive emotional attitude and availability of memory traces about positive experience. Individuals with low IAF demonstrate predominance of sympathetic influences and maladaptive avoidance-like coping with inescapable threat and insufficiency of positive emotional activation mechanisms. It is suggested that IAF participates in the formation of individual emotional space and strategies of coping with emotional challenges.

Dopaminergic Neurogenetics of Sleep Disorders in Reward Deficiency Syndrome (RDS)

It is well-known that sleep has a vital function especially as it relates to prevention of substance-related disorders as discussed in the DSM-V. We are cognizant that certain dopaminergic gene polymorphisms have been associated with various sleep disorders. The importance of "normal dopamine homeostasis" is tantamount for quality of life especially for the recovering addict. Since it is now know that sleep per se has been linked with metabolic clearance of neurotoxins in the brain, it is parsonomiuos to encourage continued research in sleep science, which should ultimately result in attenuation of sleep deprivation especially associated with substance related disorders.

Dopaminergic role in regulating neurophysiological markers of sleep homeostasis in humans

While dopamine affects fundamental brain processes such as movement control, emotional responses, addiction, and pain, the roles for this neurotransmitter in regulating wakefulness and sleep are incompletely understood. Genetically modified animal models with reduced dopamine clearance exhibit hypersensitivity to caffeine, reduced-responsiveness to modafinil, and increased homeostatic response to prolonged wakefulness when compared with wild-type animals. Here we studied sleep-wake regulation in humans and combined pharmacogenetic and neurophysiologic methods to analyze the effects of the 3'-UTR variable-number-tandem-repeat polymorphism of the gene (DAT1, SLC6A3) encoding dopamine transporter (DAT). Previous research demonstrated that healthy homozygous 10-repeat (10R/10R) allele carriers of this genetic variant have reduced striatal DAT protein expression when compared with 9-repeat (9R) allele carriers. Objective and subjective estimates of caffeine sensitivity were higher in 10R allele homozygotes than in carriers of the 9R allele. Moreover, caffeine and modafinil affected wakefulness-induced changes in functional bands (delta, sigma, beta) of rhythmic brain activity in wakefulness and sleep in a DAT1 genotype-dependent manner. Finally, the sleep deprivation-induced increase in well established neurophysiologic markers of sleep homeostasis, including slow-wave sleep, electroencephalographic slow-wave activity (0.5-4.5 Hz), and number of low-frequency (0.5-2.0 Hz) oscillations in non-rapid-eye-movement sleep, was significantly larger in the 10R/10R genotype than in the 9R allele carriers of DAT1. Together, the data suggest that the dopamine transporter contributes to homeostatic sleep-wake regulation in humans.

Personalized Medicine in ADHD and Depression: Use of Pharmaco-EEG

This chapter summarises recent developments on personalised medicine in psychiatry with a focus on ADHD and depression and their associated biomarkers and phenotypes. Several neurophysiological subtypes in ADHD and depression and their relation to treatment outcome are reviewed. The first important subgroup consists of the 'impaired vigilance' subgroup with often-reported excess frontal theta or alpha activity. This EEG subtype explains ADHD symptoms well based on the EEG Vigilance model, and these ADHD patients responds well to stimulant medication. In depression this subtype might be unresponsive to antidepressant treatments, and some studies suggest these depressive patients might respond better to stimulant medication. Further research should investigate whether sleep problems underlie this impaired vigilance subgroup, thereby perhaps providing a route to more specific treatments for this subgroup. Finally, a slow individual alpha peak frequency is an endophenotype associated with treatment resistance in ADHD and depression. Future studies should incorporate this endophenotype in clinical trials to investigate further the efficacy of new treatments in this substantial subgroup of patients.

Age-dependent effect of Alzheimer's risk variant of CLU on EEG alpha rhythm in non-demented adults

Polymorphism in the genomic region harboring the CLU gene (rs11136000) has been associated with the risk for Alzheimer’s disease (AD). CLU C allele is assumed to confer risk for AD and the allele T may have a protective effect. We investigated the influence of the AD-associated CLU genotype on a common neurophysiological trait of brain activity (resting-state alpha-rhythm activity) in non-demented adults and elucidated whether this influence is modified over the course of aging. We examined quantitative electroencephalography (EEG) in a cohort of non-demented individuals (age range 20–80) divided into young (age range 20–50) and old (age range 51–80) cohorts and stratified by CLU polymorphism. To rule out the effect of the apolipoprotein E (ApoE) genotype on EEG characteristics, only subjects without the ApoE ε4 allele were included in the study. The homozygous presence of the AD risk variant CLU CC in non-demented subjects was associated with an increase of alpha3 absolute power. Moreover, the influence of CLU genotype on alpha3 was found to be higher in the subjects older than 50 years of age. The study also showed age-dependent alterations of alpha topographic distribution that occur independently of the CLU genotype. The increase of upper alpha power has been associated with hippocampal atrophy in patients with mild cognitive impairment (Moretti etal., 2012a). In our study, the CLU CC-dependent increase in upper alpha rhythm, particularly enhanced in elderly non-demented individuals, may imply that the genotype is related to preclinical dysregulation of hippocampal neurophysiology in aging and that this factor may contribute to the pathogenesis of AD.