Reactivity of alpha rhythms to eyes opening (the Berger effect) during menstrual cycle phases

ADHD-AID: Aiding Tool for Detecting Children's Attention Deficit Hyperactivity Disorder via EEG-Based Multi-Resolution Analysis and Feature Selection

The severe effects of attention deficit hyperactivity disorder (ADHD) among adolescents can be prevented by timely identification and prompt therapeutic intervention. Traditional diagnostic techniques are complicated and time-consuming because they are subjective-based assessments. Machine learning (ML) techniques can automate this process and prevent the limitations of manual evaluation. However, most of the ML-based models extract few features from a single domain. Furthermore, most ML-based studies have not examined the most effective electrode placement on the skull, which affects the identification process, while others have not employed feature selection approaches to reduce the feature space dimension and consequently the complexity of the training models. This study presents an ML-based tool for automatically identifying ADHD entitled "ADHD-AID". The present study uses several multi-resolution analysis techniques including variational mode decomposition, discrete wavelet transform, and empirical wavelet decomposition. ADHD-AID extracts thirty features from the time and time-frequency domains to identify ADHD, including nonlinear features, band-power features, entropy-based features, and statistical features. The present study also looks at the best EEG electrode placement for detecting ADHD. Additionally, it looks into the location combinations that have the most significant impact on identification accuracy. Additionally, it uses a variety of feature selection methods to choose those features that have the greatest influence on the diagnosis of ADHD, reducing the classification's complexity and training time. The results show that ADHD-AID has provided scores for accuracy, sensitivity, specificity, F1-score, and Mathew correlation coefficients of 0.991, 0.989, 0.992, 0.989, and 0.982, respectively, in identifying ADHD with 10-fold cross-validation. Also, the area under the curve has reached 0.9958. ADHD-AID's results are significantly higher than those of all earlier studies for the detection of ADHD in adolescents. These notable and trustworthy findings support the use of such an automated tool as a means of assistance for doctors in the prompt identification of ADHD in youngsters.

Implicit motor imagery performance and cortical activity throughout the menstrual cycle

Studies show that female motor and visuospatial skills are modulated by the menstrual cycle. Implicit motor imagery, meaning the involuntary imagination of movements during a task, involves kinesthetic, visual, and spatial aspects of the corresponding action and can be investigated by using the hand laterality judgment task (HLJT). In this study we aimed to investigate whether implicit motor imagery performance and cortical activity are altered throughout the menstrual cycle, as demonstrated by motor skills in females. Thus, 31 healthy women underwent HLJT during the menstrual, follicular and luteal phases of their menstrual cycles. Right-handed participants had to recognize the laterality (right or left) of hands presented in different views (palm or back) and orientations on a computer screen. Test performance and EEG event-related potentials were analyzed. Participants performed better in the test in the follicular and luteal phases when compared to the menstrual phase, and the accuracy of the test was positively correlated with estradiol levels in the follicular phase. The difference between medial and lateral hand orientations for rotation-related negativity was significant in the medial and left parieto-occipital regions only in the follicular phase. These findings suggest positive modulating action of estradiol in performing implicit motor imagery.

Effect of caffeine on resting-state alpha activity across the human menstrual cycle

RATIONALE

Caffeine is the most consumed stimulant worldwide, and there is great interest in understanding its neurophysiological effects. Resting-state electroencephalography (EEG) studies suggest that caffeine enhances arousal, which suppresses the spectral power of alpha frequencies associated with reduced alertness. However, it is unclear whether caffeine's neurophysiological effects vary across the human menstrual cycle.

OBJECTIVE

The objective of our study was to test whether caffeine's effect on EEG activity differs across the human menstrual cycle.

METHODS

Fifty-six female participants were randomly assigned to complete the experiment while in either their menstrual (n = 21), follicular (n = 19), or luteal (n = 16) phase. Each participant completed two study sessions in the same menstrual phase, approximately 1 month apart, during which they were administered either a caffeine pill (200 mg, oral) or a placebo pill in a counterbalanced order using a randomized double-blinded procedure. We measured their eyes-closed resting-state EEG approximately 30 min after pill administration and conducted a spectral power analysis at different frequency bands.

RESULTS

Caffeine reduced EEG power in the alpha₁ frequency band (8-10 Hz), but only for participants who self-reported higher weekly caffeine consumption. Importantly, caffeine's effects did not differ by menstrual phase.

CONCLUSIONS

We conclude that when studying caffeine's effects on resting-state EEG, participants' baseline caffeine consumption is more influential than their menstrual cycle phase. This study has important implications for the inclusion of menstruating individuals in neurophysiological studies of caffeine.

HPA axis activity across the menstrual cycle - a systematic review and meta-analysis of longitudinal studies

Differential HPA axis function has been proposed to underlie sex-differences in mental disorders; however, the impact of fluctuating sex hormones across the menstrual cycle on HPA axis activity is still unclear. This meta-analysis investigated basal cortisol concentrations as a marker for HPA axis activity across the menstrual cycle. Through a systematic literature search of five databases, 121 longitudinal studies were included, summarizing data of 2641 healthy, cycling participants between the ages of 18 and 45. The meta-analysis showed higher cortisol concentrations in the follicular vs. luteal phase (d_SMC = 0.12, p =.004, [0.04 - 0.20]). Comparisons between more precise cycle phases were mostly insignificant, aside from higher concentrations in the menstrual vs. premenstrual phase (d_SMC = 0.17, [0.02 - 0.33], p =.03). In all included studies, nine samples used established cortisol parameters to indicate HPA axis function, specifically diurnal profiles (k = 4) and the cortisol awakening response (CAR) (k = 5). Therefore, the meta-analysis highlights the need for more rigorous investigation of HPA axis activity and menstrual cycle phase.

Psychophysiological Indicators of Postural Control. Contribution of the Russian Scientific School. Part I

This article aimed to systematically review the published results of studies of psychophysiological mechanisms of posture maintenance and identify the key factors that influence the effectiveness of postural control. The recommendations of "Preferred Reporting Elements for Systematic Reviews and Meta-Analyzes" (PRISMA) were followed for the review. The results were classified, taking into account the target psychophysiological mechanisms and factors affecting postural control. The article presents the theoretical and empirical results of the Russian scientific school of research on the role of support afferentation in the sensorimotor mechanisms of cognitive and postural functions. Due to the limited number of randomized studies found, it was impossible to make meta-analytic comparisons, so the literature analysis was carried out only qualitatively. Meanwhile, our systematic review provides promising information about possible relationships between stabilometric and psychological indicators of postural control, which have theoretical significance and application in the correction and training of posture control. However, more thorough research is needed to overcome the methodological shortcomings that we have encountered in our qualitative analysis.

Human resting-state EEG and radiofrequency GSM mobile phone exposure: the impact of the individual alpha frequency

PURPOSE

With the extensive use of mobile phone (MP), several studies have been realized to investigate the effects of radiofrequency electromagnetic fields (RF-EMF) exposure on brain activity at rest via electroencephalography (EEG), and the most consistent effect has been seen on the alpha band power spectral density (PSD). However, some studies reported an increase or a decrease of the PSD, while others showed no effect. It has been suggested that these differences might partly be due to a variability of the physiological state of the brain between subjects. So, the aim of this study was to investigate the alpha band modulation, exploring the impact of the alpha band frequency ranges applied in the PSD analysis.

MATERIALS AND METHODS

Twenty-one healthy volunteers took part to the study with a double-blind, randomized and counterbalanced crossover design, during which eyes-open (EO) and eyes-closed (EC) resting-state EEG was recorded. The exposure system was a sham or a real GSM (global system for mobile) 900 MHz MP (pulse modulated at 217 Hz, mean power of 250 mW and 2 W peak, with a maximum specific absorption rate of 0.70 W/kg on 1 g tissue). The experimental protocol presented a baseline recording phase without MP exposure, an exposure phase during which the exposure system was placed against the left ear, and the post-exposure phase without MP. EEG data from baseline and exposure phases were analyzed and PSD was computed for the alpha band in the fixed range of 8-12 Hz and for the individual alpha band frequency range (IAF).

RESULTS

Results showed a trend in decrease or increase of EEG power of both alpha oscillations during exposure in relation to EC and EO recording conditions, respectively, but not reaching statistical significance. Findings did not provide evidence for a different sensitivity to RF-EMF MP related to individual variability in the frequency of the alpha band.

CONCLUSION

In conclusion, these results did not show alpha band activity modulation during resting-state under RF-EMF. It might be argued the need of a delay after the exposure in order to appreciate an EEG spectral power modulation related to RF-EMF exposure.

Sex differences in resting EEG in healthy young adults

Resting EEG, measured in eyes-closed (EC) and eyes-open (EO) states, can provide insight into behavioural differences between groups. Surprisingly, differences in resting EEG between females and males have not been investigated systematically in previous literature. The present study utilised the four traditional EEG bands to confirm their baseline EC topographies and reactivity (EO minus EC) across groups, to clarify topographical differences between sexes, and to confirm alpha as a measure of arousal. Participants were eighty healthy young adults (40 female), with a mean age of 20.4 (range 18-26) years. Continuous resting EEG was recorded from 30 scalp sites during three 2-minute conditions (EO1, EC, EO2), and EOG-corrected. Data from each condition were divided into 60 sequential 2-second epochs. Accepted artefact-free epochs were Fourier Transformed, and absolute amplitudes in the delta (0.5-3.5 Hz), theta (4.0-7.5 Hz), alpha (8.0-13.0 Hz), and beta (13.5-29.5 Hz) bands were calculated. Across groups in EC, significant topographical differences were found between the band amplitudes, broadly compatible with previous reports. Females had greater overall amplitudes in delta, alpha and beta, enhanced midline activity in theta, and parietal and midline activity in the alpha and beta bands. From EC to EO, reactivity was apparent across the bands as significant reductions, particularly in the parietal region. For females compared to males, the reduction in parietal midline delta and theta, parietal alpha and parietal midline beta was significantly larger. Additionally, across groups, alpha activity was confirmed as an inverse measure of arousal. These findings indicate significant differences in neuronal activity between young adult females and males, and help our interpretation of alpha changes.

Menstrual Cycle Variations in Gray Matter Volume, White Matter Volume and Functional Connectivity: Critical Impact on Parietal Lobe

The role of gonadal hormones in neural plasticity remains unclear. This study aimed to examine the effects of naturally fluctuating hormone levels over the menstrual cycle in healthy females. Gray matter, functional connectivity (FC) and white matter changes over the cycle were assessed by using functional magnetic resonance imaging (fMRI), resting state fMRI, and structural MRIs, respectively, and associated with serum gonadal hormone levels. Moreover, electrocutaneous sensitivity was evaluated in 14 women in four phases of their menstrual cycle (menstrual, follicular, ovulatory, and luteal). Electrocutaneous sensitivity was greater during follicular compared to menstrual phase. Additionally, pain unpleasantness was lower in follicular phase than other phases while pain intensity ratings did not change over the cycle. Significant variations in cycle phase effects on gray matter volume were found in the left inferior parietal lobule (IPL) using voxel-based morphometry. Subsequent Freesurfer analysis revealed greater thickness of left IPL during the menstrual phase when compared to other phases. Also, white matter volume fluctuated across phases in left IPL. Blood estradiol was positively correlated with white matter volume both in left parietal cortex and whole cortex. Seed-driven FC between left IPL and right secondary visual cortex was enhanced during ovulatory phase. A seed placed in right IPL revealed enhanced FC between left and right IPL during the ovulatory phase. Additionally, we found that somatosensory cortical gray matter was thinner during follicular compared to menstrual phase. We discuss these results in the context of likely evolutionary pressures selecting for enhanced perceptual sensitivity across modalities specifically during ovulation.

Major Depression and Brain Asymmetry in a Decision-Making Task with Negative and Positive Feedback

Depressed patients are characterized by hypoactivity of the left and hyperactivity of the right frontal areas during the resting state. Depression is also associated with impaired decision-making, which reflects multiple cognitive, affective, and attentional processes, some of which may be lateralized. The aim of this study was to investigate brain asymmetry during a decision-making task performed in negative and positive feedback conditions in patients with Major Depressive Disorder (MDD) in comparison to healthy control participants. The electroencephalogram (EEG) was recorded from 60 MDD patients and 60 healthy participants while performing a multi-stage decision-making task. Frontal, central, and parietal alpha asymmetry were analyzed with EEGlab/ERPlab software. Evoked potential responses (ERPs) showed general lateralization suggestive of an initial right dominance developing into a more complex pattern of asymmetry across different scalp areas as information was processed. The MDD group showed impaired mood prior to performance, and decreased confidence during performance in comparison to the control group. The resting state frontal alpha asymmetry showed lateralization in the healthy group only. Task-induced alpha power and ERP P100 and P300 amplitudes were more informative biomarkers of depression during decision making. Asymmetry coefficients based on task alpha power and ERP amplitudes showed consistency in the dynamical changes during the decision-making stages. Depression was characterized by a lack of left dominance during the resting state and left hypoactivity during the task baseline and subsequent decision-making process. Findings add to understanding of the functional significance of lateralized brain processes in depression.

Detection and analysis of MEG signals in occipital region with double-channel OPM sensors

BACKGROUND

Magnetoencephalography (MEG) has high temporal and spatial resolution and good spatial accuracy in determining the locations of source activity among most non-invasive imaging. The recently developed technology of optically-pumped magnetometer (OPM) has sensitivity comparable to that of the superconducting quantum interference device (SQUID) used in commercial MEG system.

NEW METHOD

Double-channel OPM-MEG system detects human photic blocking of alpha rhythm at the occipital region of skull in the magnetically shielded environment via a wearable whole-cortex 3D-printed helmet.

RESULTS

The alpha rhythm can be detected by the OPM-MEG system, the MEG signals are undoubtedly caused by photic blocking and similar with the results measured by SQUID magnetometer.

COMPARISON WITH EXISTING METHODS

Due to the dependency of current commercial whole-cortex SQUID-MEG system on the liquid helium, the separation from the liquid helium space to the human head is usually at least a few centimeters. The wearable OPM-MEG system, however, can significantly improve the detection efficiency since its sensors can be mounted close to scalp, normally less than 1 cm.

CONCLUSIONS

OPM-MEG system successfully detects alpha rhythm blocked by light stimulation and works well in the home-made magnetically shielded environment. OPM-MEG system shows a substitute for the traditional MEG system.

EEG alpha activity increased in response to transcutaneous electrical nervous stimulation in young healthy subjects but not in the healthy elderly

Transcutaneous Electrical Nerve Stimulation (TENS) is used not only in the treatment of pain but also in the examination of sensory functions. With aging, there is decreased sensitivity to somatosensory stimuli. It is essential to examine the effect of TENS application on the sensory functions in the brain by recording the spontaneous electroencephalogram (EEG) activity and the effect of aging on the sensory functions of the brain during the application. The present study aimed to investigate the effect of the application of TENS on the brain’s electrical activity and the effect of aging on the sensory functions of the brain during application of TENS. A total of 15 young (24.2 ± 3.59) and 14 elderly (65.64 ± 4.92) subjects were included in the study. Spontaneous EEG was recorded from 32 channels during TENS application. Power spectrum analysis was performed by Fast Fourier Transform in the alpha frequency band (8–13 Hz) for all subjects. Repeated measures of analysis of variance was used for statistical analysis (p < 0.05). Young subjects had increased alpha power during the TENS application and had gradually increased alpha power by increasing the current intensity of TENS (p = 0.035). Young subjects had higher alpha power than elderly subjects in the occipital and parietal locations (p = 0.073). We can, therefore, conclude that TENS indicated increased alpha activity in young subjects. Young subjects had higher alpha activity than elderly subjects in the occipital and somatosensory areas. To our knowledge, the present study is one of the first studies examining the effect of TENS on spontaneous EEG in healthy subjects. Based on the results of the present study, TENS may be used as an objective method for the examination of sensory impairments, and in the evaluative efficiency of the treatment of pain conditions.

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.

Hormonal regulation of circuit function: sex, systems and depression

Major depressive disorder (MDD) is a debilitating chronic illness that is two times more prevalent in women than in men. The mechanisms associated with the increased female susceptibility to depression remain poorly characterized. Aberrant neuronal oscillatory activity within the putative depression network is an emerging mechanism underlying MDD. However, innate sex differences in network activity and its contribution to depression vulnerability have not been well described. In this review, current evidence of sex differences in neuronal oscillatory activity, including the influence of sex hormones and female cycling, will first be described followed by evidence of disrupted neuronal circuit function in MDD and the effects of antidepressant treatment. Lastly, current knowledge of sex differences in MDD-associated aberrant circuit function and oscillatory activity will be highlighted, with an emphasis on the role of sex steroids and female cycling. Collectively, it is clear that there are significant gaps in the literature regarding innate and pathologically associated sex differences in network activity and that the elucidation of these differences is invaluable to our understanding of sex-specific vulnerabilities and therapies for MDD.

Recording Brain Electromagnetic Activity During the Administration of the Gaseous Anesthetic Agents Xenon and Nitrous Oxide in Healthy Volunteers

Anesthesia arguably provides one of the only systematic ways to study the neural correlates of global consciousness/unconsciousness. However to date most neuroimaging or neurophysiological investigations in humans have been confined to the study of γ-Amino-Butyric-Acid-(GABA)-receptor-agonist-based anesthetics, while the effects of dissociative N-Methyl-D-Aspartate-(NMDA)-receptor-antagonist-based anesthetics ketamine, nitrous oxide (N2O) and xenon (Xe) are largely unknown. This paper describes the methods underlying the simultaneous recording of magnetoencephalography (MEG) and electroencephalography (EEG) from healthy males during inhalation of the gaseous anesthetic agents N2O and Xe. Combining MEG and EEG data enables the assessment of electromagnetic brain activity during anesthesia at high temporal, and moderate spatial, resolution. Here we describe a detailed protocol, refined over multiple recording sessions, that includes subject recruitment, anesthesia equipment setup in the MEG scanner room, data collection and basic data analysis. In this protocol each participant is exposed to varying levels of Xe and N2O in a repeated measures cross-over design. Following relevant baseline recordings participants are exposed to step-wise increasing inspired concentrations of Xe and N2O of 8, 16, 24 and 42%, and 16, 32 and 47% respectively, during which their level of responsiveness is tracked with an auditory continuous performance task (aCPT). Results are presented for a number of recordings to highlight the sensor-level properties of the raw data, the spectral topography, the minimization of head movements, and the unequivocal level dependent effects on the auditory evoked responses. This paradigm describes a general approach to the recording of electromagnetic signals associated with the action of different kinds of gaseous anesthetics, which can be readily adapted to be used with volatile and intravenous anesthetic agents. It is expected that the method outlined can contribute to the understanding of the macro-scale mechanisms of anesthesia by enabling methodological extensions involving source space imaging and functional network analysis.