Resting brain activity: Differences between genders

Individual posterior alpha rhythms and cognitive reserve as possible early prognostic markers in people with subjective memory complaints

Subjective memory complaints (SMCs) are a memory disorder that often precedes mild cognitive impairment (MCI) or Alzheimer's disease (AD). Both individual alpha rhythms and cognitive reserve (CR) represent key features of SMCs and provide useful tools to characterize and predict the course of the disorder. We studied whether older people with SMCs may also present some abnormal resting state electroencephalogram (rsEEG) alpha rhythms, and whether alpha rhythms are associated with CR. To do this, eyes-closed rsEEG were recorded in 68 older people with and without SMCs. The individual alpha indexes alpha/theta transition frequency (TF) and individual alpha frequency peak (IAFp) were computed. TF and IAFp were also used to determine the alpha1, alpha2, and alpha3 power frequency. Results indicated no differences in TF or IAFp between older people with SMCs and controls. The SMCs group showed a reduction in alpha3 power in comparison with controls. Specifically, women with SMCs were characterized by a significant decrease in alpha3 power compared to control women. Furthermore, only in SMCs group, greater CR was associated with slow IAFp. In sum, these results suggest that TF and IAFp are two stable indexes that are not influenced by the presence of SMCs. However, the reduction in alpha3, as observed in women with SMCs, shows an abnormal posterior rsEEG at alpha power. Finally, the compensatory mechanisms of CR appear to interact with the neurophysiological mechanisms that underlie the regulation of alpha rhythms.

Sex Differences in Alcohol Use: Is It All About Hormones?

Risky alcohol use and alcohol use disorders (AUD) are a rising problem in women, yet a major disparity in our understanding of what drives alcohol consumption in women remains. Historically biomedical research has focused on male subjects; however, recent increases in reporting of females, have highlighted major differences between the sexes. Here we review the current literature of the effect of gonadal steroid hormones (estrogens, androgens, and progestins), neurosteriods, and neurobiological factors on alcohol use in clinical and preclinical studies of both sexes. Further, we briefly discuss how fundamental sex differences in genetics, metabolism, neuroimmune, and stress responses may influence sex differences in alcohol intake. Comparing the sexes could aid in the discovery of novel therapeutics to treat AUD, and implementation of current treatment options in women.

Sex differences in the progression to Alzheimer's disease: a combination of functional and structural markers

Mild cognitive impairment (MCI) has been frequently interpreted as a transitional phase between healthy cognitive aging and dementia, particularly of the Alzheimer's disease (AD) type. Of note, few studies explored that transition from a multifactorial perspective, taking into consideration the effect of basic factors such as biological sex. In the present study 96 subjects with MCI (37 males and 59 females) were followed-up and divided into two subgroups according to their clinical outcome: "progressive" MCI (pMCI = 41), if they fulfilled the diagnostic criteria for AD at the end of follow-up; and "stable" MCI (sMCI = 55), if they remained with the initial diagnosis. Different markers were combined to characterize sex differences between groups, including magnetoencephalography recordings, cognitive performance, and brain volumes derived from magnetic resonance imaging. Results indicated that the pMCI group exhibited higher low-frequency activity, lower scores in neuropsychological tests and reduced brain volumes than the sMCI group, being these measures significantly correlated. When sex was considered, results revealed that this pattern was mainly due to the influence of the females' sample. Overall, females exhibited lower cognitive scores and reduced brain volumes. More interestingly, females in the pMCI group showed an increased theta activity that correlated with a more abrupt reduction of cognitive and volumetric scores as compared with females in the sMCI group and with males in the pMCI group. These findings suggest that females' brains might be more vulnerable to the effects of AD pathology, since regardless of age, they showed signs of more pronounced deterioration than males.

Altered resting-state brain oscillation and the associated cognitive impairments in late-life depression with different depressive severity: An EEG power spectrum and functional connectivity study

OBJECTIVE

Cognitive impairments are prevalent in late-life depression (LLD). However, it remains unclear whether there are concurrent brain oscillation alterations in resting condition across varying level of depression severity. This cross-sectional study aims to investigate the characteristics of altered resting-state oscillations, including power spectrum and functional connectivity, and their association with the cognitive impairments in LLD with different depression severity.

METHODS

A total of 65 patients with LLD and 40 elder participants without depression were recruited. Global cognition and subtle cognitive domains were evaluated. A five-minute resting-state electroencephalography (EEG) was conducted under eyes-closed conditions. Measurements included the ln-transformed absolute power for power spectrum analysis and the weighted phase lag index (wPLI) for functional connectivity analysis.

RESULTS

Attentional and executive dysfunction were exhibited in Moderate-Severe LLD group. Enhanced posterior upper gamma power was observed in both LLD groups. Additionally, enhanced parietal and fronto-parietal/occipital theta connectivity were observed in Moderate-Severe LLD group, which were associated with the attentional impairment.

LIMITATIONS

Limitations include a small sample size, concomitant medication use, and a relatively higher proportion of females.

CONCLUSIONS

Current study observed aberrant brain activity patterns in LLD across different levels of depression severity, which were linked to cognitive impairments. The altered posterior brain oscillations may be trait marker of LLD. Moreover, cognitive impairments and associated connectivity alterations were exhibited in moderate-severe group, which may be a state-like marker of moderate-to severe LLD. The study deepens understanding of cognitive impairments with the associated oscillation changes, carrying implications for neuromodulation targets in LLD.

Multivariate multiscale entropy (mMSE) as a tool for understanding the resting-state EEG signal dynamics: the spatial distribution and sex/gender-related differences

BACKGROUND

The study aimed to determine how the resting-state EEG (rsEEG) complexity changes both over time and space (channels). The complexity of rsEEG and its sex/gender differences were examined using the multivariate Multiscale Entropy (mMSE) in 95 healthy adults. Following the probability maps (Giacometti et al. in J Neurosci Methods 229:84-96, 2014), channel sets have been identified that correspond to the functional networks. For each channel set the area under curve (AUC), which represents the total complexity, MaxSlope-the maximum complexity change of the EEG signal at thefine scales (1:4 timescales), and AvgEnt-to the average entropy level at coarse-grained scales (9:12 timescales), respectively, were extracted. To check dynamic changes between the entropy level at the fine and coarse-grained scales, the difference in mMSE between the #9 and #4 timescale (DiffEnt) was also calculated.

RESULTS

We found the highest AUC for the channel sets corresponding to the somatomotor (SMN), dorsolateral network (DAN) and default mode (DMN) whereas the visual network (VN), limbic (LN), and frontoparietal (FPN) network showed the lowest AUC. The largest MaxSlope were in the SMN, DMN, ventral attention network (VAN), LN and FPN, and the smallest in the VN. The SMN and DAN were characterized by the highest and the LN, FPN, and VN by the lowest AvgEnt. The most stable entropy were for the DAN and VN while the LN showed the greatest drop of entropy at the coarse scales. Women, compared to men, showed higher MaxSlope and DiffEnt but lower AvgEnt in all channel sets.

CONCLUSIONS

Novel results of the present study are: (1) an identification of the mMSE features that capture entropy at the fine and coarse timescales in the channel sets corresponding to the main resting-state networks; (2) the sex/gender differences in these features.

Sex-related patterns in the electroencephalogram and their relevance in machine learning classifiers

Deep learning is increasingly being proposed for detecting neurological and psychiatric diseases from electroencephalogram (EEG) data but the method is prone to inadvertently incorporate biases from training data and exploit illegitimate patterns. The recent demonstration that deep learning can detect the sex from EEG implies potential sex-related biases in deep learning-based disease detectors for the many diseases with unequal prevalence between males and females. In this work, we present the male- and female-typical patterns used by a convolutional neural network that detects the sex from clinical EEG (81% accuracy in a separate test set with 142 patients). We considered neural sources, anatomical differences, and non-neural artifacts as sources of differences in the EEG curves. Using EEGs from 1140 patients, we found electrocardiac artifacts to be leaking into the supposedly brain activity-based classifiers. Nevertheless, the sex remained detectable after rejecting heart-related and other artifacts. In the cleaned data, EEG topographies were critical to detect the sex, but waveforms and frequencies were not. None of the traditional frequency bands was particularly important for sex detection. We were able to determine the sex even from EEGs with shuffled time points and therewith completely destroyed waveforms. Researchers should consider neural and non-neural sources as potential origins of sex differences in their data, they should maintain best practices of artifact rejection, even when datasets are large, and they should test their classifiers for sex biases.

Abnormal spectral and scale-free properties of resting-state EEG in girls with Rett syndrome

Spontaneous EEG contains important information about neuronal network properties that is valuable for understanding different neurological and psychiatric conditions. Rett syndrome (RTT) is a rare neurodevelopmental disorder, caused by mutation in the MECP2 gene. RTT is characterized by severe motor impairments that prevent adequate assessment of cognitive functions. Here we probe EEG parameters obtained in no visual input condition from a 28-channels system in 23 patients with Rett Syndrome and 38 their typically developing peers aged 3-17 years old. Confirming previous results, RTT showed a fronto-central theta power (4-6.25 Hz) increase that correlates with a progression of the disease. Alpha power (6.75-11.75 Hz) across multiple regions was, on the contrary, decreased in RTT, also corresponding to general background slowing reported previously. Among novel results we found an increase in gamma power (31-39.5 Hz) across frontal, central and temporal electrodes, suggesting elevated excitation/inhibition ratio. Long-range temporal correlation measured by detrended fluctuation analysis within 6-13 Hz was also increased, pointing to a more predictable oscillation pattern in RTT. Overall measured EEG parameters allow to differentiate groups with high accuracy, ROC AUC value of 0.92 ± 0.08, indicating clinical relevance.

Effects of spaceflight on the EEG alpha power and functional connectivity

Electroencephalography (EEG) can detect changes in cerebral activity during spaceflight. This study evaluates the effect of spaceflight on brain networks through analysis of the Default Mode Network (DMN)'s alpha frequency band power and functional connectivity (FC), and the persistence of these changes. Five astronauts' resting state EEGs under three conditions were analyzed (pre-flight, in-flight, and post-flight). DMN's alpha band power and FC were computed using eLORETA and phase-locking value. Eyes-opened (EO) and eyes-closed (EC) conditions were differentiated. We found a DMN alpha band power reduction during in-flight (EC: p < 0.001; EO: p < 0.05) and post-flight (EC: p < 0.001; EO: p < 0.01) when compared to pre-flight condition. FC strength decreased during in-flight (EC: p < 0.01; EO: p < 0.01) and post-flight (EC: ns; EO: p < 0.01) compared to pre-flight condition. The DMN alpha band power and FC strength reduction persisted until 20 days after landing. Spaceflight caused electrocerebral alterations that persisted after return to earth. Periodic assessment by EEG-derived DMN analysis has the potential to become a neurophysiologic marker of cerebral functional integrity during exploration missions to space.

Aviation and neurophysiology: A systematic review

This paper systematically reviews 20 years of publications (N = 54) on aviation and neurophysiology. The main goal is to provide an account of neurophysiological changes associated with flight training with the aim of identifying neurometrics indicative of pilot's flight training level and task relevant mental states, as well as to capture the current state-of-art of (neuro)ergonomic design and practice in flight training. We identified multiple candidate neurometrics of training progress and workload, such as frontal theta power, the EEG Engagement Index and the Cognitive Stability Index. Furthermore, we discovered that several types of classifiers could be used to accurately detect mental states, such as the detection of drowsiness and mental fatigue. The paper advances practical guidelines on terminology usage, simulator fidelity, and multimodality, as well as future research ideas including the potential of Virtual Reality flight simulations for training, and a brain-computer interface for flight training.

Effects of Olfactory Stimulation with Aroma Oils on Psychophysiological Responses of Female Adults

This study investigated the effects of olfactory stimulation with aroma oils on the psychophysiological responses in women. Ten aromatic oils (lavender, rosemary, rose, eucalyptus, jasmine, geranium, chamomile, clary sage, thyme, and peppermint) were used on 23 women aged between 20 and 60 years. They inhaled the scent for 90 s through a glass funnel attached to their lab apron, 10 cm below their nose, while the pump was activated. Electroencephalography, blood pressure, and pulse rate were measured before and during inhalation of the aroma oils. The relative alpha (RA) power spectrums indicating relaxation and resting state of the brain significantly increased when lavender, rosemary, eucalyptus, jasmine, chamomile, clary sage, and thyme oils were inhaled compared to those of before olfactory stimulation. The ratio of alpha to high beta (RAHB), an indicator of brain stability and relaxation, significantly increased when rosemary, jasmine, clary sage, and peppermint oils were inhaled. The relative low beta (RLB) power spectrum, an indicator of brain activity in the absence of stress, significantly increased when stimulated with lavender, rosemary, rose, and geranium scents. Further, systolic blood pressure significantly decreased after introduction of all 10 types of aromatic oils, which indicates stress reduction. Thus, olfactory stimulation with aroma oil had a stabilizing effect on the prefrontal cortex and brain activity and decreased systolic blood pressure.

Study of Sex Differences in Unmedicated Patients With Major Depressive Disorder by Using Resting State Brain Functional Magnetic Resonance Imaging

Some important clinical characteristics of major depressive disorder (MDD) differ between sexes. We explored abnormal spontaneous neuronal activity in MDD patients using the amplitude of low-frequency fluctuation (ALFF) and its relationship to clinical manifestations in male and female patients, to seek the neural mechanisms underlying sex-related differences in depression. Twenty-five male MDD patients, 36 female MDD patients, and 25 male and 36 female matched healthy controls (HC) were included. The ALFF difference was investigated among four groups, and partial correlation analysis was used to explore a possible clinical relevance. The main effect results of sex difference were located in the bilateral caudate nucleus and posterior cingulate gyrus. Post hoc comparisons found that the male MDD patients showed decreased ALFF in the bilateral caudate nucleus and posterior cingulate gyrus when compared with female MDD patients/female HCs, and female MDD patients showed increased ALFF in the bilateral caudate nucleus and posterior cingulate gyrus when compared with male HCs. The average ALFF of the right caudate nucleus was positively correlated with illness duration in female MDD patients. Our results suggest that the sex-specific abnormal brain activity might be a potential pathomechanism of different symptoms in male and female MDD patients.

Prefrontal cortex hemodynamic response to acute high intensity intermittent exercise during executive function processing

We investigated prefrontal cortex (PFC) hemodynamic response, through functional near infrared spectroscopy (fNIRS) during executive function (EF) processing in response to acute high intensity intermittent exercise (HIIE) in young adults. We also assessed the associated sex differences in the cognitive scores and related PFC hemodynamic functions in response to HIIE. 49 young healthy adult participants (32 women, 17 men) were randomly assigned to either control or HIIE intervention groups. HIIE group participants performed 4 × 4 minutes of HIIE on cycle ergometer with 3 minutes of active recovery between the bouts; control group relaxed for the time equivalent to intervention. fNIRS data was collected during the performance of the EF tests including Color Word Stroop Test (CWST) and Trail Making Test (TMT) in pre and post sessions in both the groups. Results indicated a significant change in the hemodynamic response in the form of increased oxygenated and decreased deoxygenated hemoglobin in the PFC areas specific to the EF tasks, with improved CWST and TMT scores in response to HIIE intervention. PFC activation was different in men and women in response to HIIE, however similar scores of task performance were observed in men and women during the performance of executive functions in response to HIIE. The study concludes that an acute HIIE session improves executive function which is associated with an increase activation of PFC. Sex differences exist in the activation of PFC in response to HIIE during EF processing. Our study adds to the current evidence regarding exercise and cognition.

EEG theta and beta bands as brain oscillations for different knee osteoarthritis phenotypes according to disease severity

This study aims to investigate the multivariate relationship between different sociodemographic, clinical, and neurophysiological variables with resting-state, high-definition, EEG spectral power in subjects with chronic knee osteoarthritis (OA) pain. This was a cross-sectional study. Sociodemographic and clinical data were collected from 66 knee OA subjects. To identify associated factors, we performed independent univariate and multivariate regression models by frequency bands (delta, theta, alpha, beta, low-beta, and high-beta) and by pre-defined regions (frontal, central, and parietal). From adjusted multivariate models, we found that: (1) increased frontocentral high-beta power and reduced central theta activity are positively correlated with pain intensity (β = 0.012, 95% CI 0.004-0.020; and β = - 0.008; 95% CI 0.014 to - 0.003; respectively); (2) delta and alpha oscillations have a direct relationship with higher cortical inhibition; (3) diffuse increased power at low frequencies (delta and theta) are associated with poor cognition, aging, and depressive symptoms; and (4) higher alpha and beta power over sensorimotor areas seem to be a maladaptive compensatory mechanism to poor motor function and severe joint degeneration. Subjects with higher pain intensity and higher OA severity (likely subjects with maladaptive compensatory mechanisms to severe OA) have higher frontocentral beta power and lower theta activity. On the other hand, subjects with less OA severity and less pain have higher theta oscillations power. These associations showed the potential role of brain oscillations as a marker of pain intensity and clinical phenotypes in chronic knee OA patients. Besides, they suggest a potential compensatory mechanism of these two brain oscillators according to OA severity.

Resting-State Theta Oscillations and Reward Sensitivity in Risk Taking

Females demonstrate greater risk aversion than males on a variety of tasks, but the underlying neurobiological basis is still unclear. We studied how theta (4–7 Hz) oscillations at rest related to three different measures of risk taking. Thirty-five participants (15 females) completed the Bomb Risk Elicitation Task (BRET), which allowed us to measure risk taking during an economic game. The Domain-Specific Risk-Taking Scale (DOSPERT) was used to measure self-assessed risk attitudes as well as reward and punishment sensitivities. In addition, the Barratt Impulsiveness Scale (BIS11) was included to quantify impulsiveness. To obtain measures of frontal theta asymmetry and frontal theta power, we used magnetoencephalography (MEG) acquired prior to task completion, while participants were at rest. Frontal theta asymmetry correlated with average risk taking during the game but only in the female sample. By contrast, frontal theta power correlated with risk taking as well as with measures of reward and punishment sensitivity in the joint sample. Importantly, we showed that reward sensitivity mediated a correlation between risk taking and the power of theta oscillations localized to the anterior cingulate cortex. In addition, we observed significant sex differences in source- and sensor-space theta power, risk taking during the game, and reward sensitivity. Our findings suggest that sensitivity to rewards, associated with resting-state theta oscillations in the anterior cingulate cortex, is a trait that potentially contributes to sex differences in risk taking.

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.

Sexually dimorphic patterns in electroencephalography power spectrum and autism-related behaviors in a rat model of fragile X syndrome

Fragile X syndrome (FXS), a neurodevelopmental disorder with autistic features, is caused by the loss of the fragile X mental retardation protein. Sex-specific differences in the clinical profile have been observed in FXS patients, but few studies have directly compared males and females in rodent models of FXS. To address this, we performed electroencephalography (EEG) recordings and a battery of autism-related behavioral tasks on juvenile and young adult Fmr1 knockout (KO) rats. EEG analysis demonstrated that compared to wild-type, male Fmr1 KO rats showed an increase in gamma frequency band power in the frontal cortex during the sleep-like immobile state, and both male and female KO rats failed to show an increase in delta frequency power in the sleep-like state, as observed in wild-type rats. Previous studies of EEG profiles in FXS subjects also reported abnormally increased gamma frequency band power, highlighting this parameter as a potential translatable biomarker. Both male and female Fmr1 KO rats displayed reduced exploratory behaviors in the center zone of the open field test, and increased distance travelled in an analysis of 24-h home cage activity, an effect that was more prominent during the nocturnal phase. Reduced wins against wild-type opponents in the tube test of social dominance was seen in both sexes. In contrast, increased repetitive behaviors in the wood chew test was observed in male but not female KO rats, while increased freezing in a fear conditioning test was observed only in the female KO rats. Our findings highlight sex differences between male and female Fmr1 KO rats, and indicate that the rat model of FXS could be a useful tool for the development of new therapeutics for treating this debilitating neurodevelopmental disorder.

Gender differences in adolescent sleep neurophysiology: a high-density sleep EEG study

During adolescence, differences between males and females in physiology, behavior and risk for psychopathology are accentuated. The goal of the current study was to examine gender differences in sleep neurophysiology using high-density sleep EEG in early adolescence. We examined gender differences in sleep EEG power and coherence across frequency bands for both NREM and REM sleep in a sample of 61 adolescents (31 girls and 30 boys; mean age = 12.48; SD = 1.34). In addition, sleep spindles were individually detected and characterized. Compared to boys, girls had significantly greater spindle activity, as reflected in higher NREM sigma power, spindle amplitude, spindle frequency and spindle density over widespread regions. Furthermore, power in higher frequency bands (16.2–44 Hz) was larger in girls than boys in a state independent manner. Oscillatory activity across frequency bands and sleep states was generally more coherent in females as compared to males, suggesting greater connectivity in females. An exception to this finding was the alpha band during NREM and REM sleep, where coherence was higher (NREM) or not different (REM) in boys compared to girls. Sleep spindles are generated through thalamocortical circuits, and thus, the greater spindle activity across regions in females may represent a stronger thalamocortical circuit in adolescent females as compared to males. Moreover, greater global connectivity in females may reflect functional brain differences with implications for cognition and mental health. Given the pronounced gender differences, our study highlights the importance of taking gender into account when designing and interpreting studies of sleep neurophysiology.

Sex Differences in QEEG in Psychopath Offenders

Introduction. Functional brain differences related to sex in psychopathic behavior represent an important field of neuroscience research; there are few studies on this area, mainly in offender samples. Objective. The aim of this study was to investigate the presence of electrophysiological differences between male and female psychopath offenders; specifically, we wanted to assess whether the results in quantitative EEG, low-resolution electromagnetic tomography (LORETA), and changes in synchronous brain activity could be related to sex influence. Sample and Methods. The study included 31 male and 12 female psychopath offenders, according to the Hare Psychopathy Checklist-Revised criteria from 2 prisons located in Havana City. The EEG visual inspection characteristics and the use of frequency domain quantitative analysis techniques are described. Results. The resting EEG visual analyses revealed a high percentage of EEG abnormalities in both studied groups. Significant statistical differences between the mean parameters of cross spectral measures between psychopathic offender groups were found in the beta band at bilateral frontal derivation and centroparietal areas. LORETA showed differences especially in the paralimbic and parieto-occipital areas Synchronization likelihood revealed a significant group effect in the 26 to 30 Hz band. These results indicate that combining quantitative EEG, LORETA analysis, and synchronization likelihood may improve the neurofunctional differentiation between psychopath offenders of both sexes.

Abnormal alpha band power in the dynamic pain connectome is a marker of chronic pain with a neuropathic component

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High theta and low gamma activity in the dynamic pain connectome is linked to chronic pain.

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High alpha-band activity is present when neuropathic pain is likely.

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Spectral frequency band strength distinguish neuropathic from non-neuropathic pain.

We previously identified alpha frequency slowing and beta attenuation in the dynamic pain connectome related to pain severity and interference in patients with multiple sclerosis-related neuropathic pain (NP). Here, we determined whether these abnormalities, are markers of aberrant temporal dynamics in non-neuropathic inflammatory pain (non-NP) or when NP is also suspected. We measured resting-state magnetoencephalography (MEG) spectral density in 45 people (17 females, 28 males) with chronic back pain due to ankylosing spondylitis (AS) and 38 age/sex matched healthy controls. We used painDETECT scores to divide the chronic pain group into those with only non-NP (NNP) and those who likely also had a component of NP in addition to their inflammatory pain. We also assessed pain severity, pain interference, and disease activity with the Brief Pain Inventory and Bath AS Disease Activity Index (BASDAI). We examined spectral power in the dynamic pain connectome, including nodes of the ascending nociceptive pathway (ANP), default mode (DMN), and salience networks (SN). Compared to the healthy controls, the AS patients exhibited increased theta power in the DMN and decreased low-gamma power in the DMN and ANP, but did not exhibit beta-band attenuation or peak-alpha slowing. The NNP patients were not different from HCs. Compared to both healthy controls and NNP, NP patients had increased alpha power in the ANP. Increased alpha power within the ANP was associated with reduced BASDAI in the NNP group, and increased pain in the mixed-NP group within the DMN, SN, and ANP. Thus, high theta and low gamma activity may be markers of chronic pain but high alpha-band activity may relate to particular features of neuropathic chronic pain.

Investigating Sex Differences in Classification of Five Emotions from EEG and Eye Movement Signals

People generally agree that emotion processing differs between male and female. However, current hypothesis of sex differences needs more objective evidence and quantitative assessment. In this paper, we investigate the sex difference in classifying ve emotions from eletroencephalograph and eye movement signals. We adopt two neural-network-based clas-si ers to objectively investigate sex differences from different perspectives. From experimental results, we nd the following three observations: (1) a general higher accuracy of same-sex strategy suggests sex-speci c factors have in uence on emotion classi cation; (2) both blink duration and frequency differ from female to male and they are negatively correlated under different emotional states; and (3) there are larger differences of brain activities in the Theta, Alpha, and Beta bands between male and female for disgust, sad, and neutral emotions.

BOLD and EEG signal variability at rest differently relate to aging in the human brain

Variability of neural activity is regarded as a crucial feature of healthy brain function, and several neuroimaging approaches have been employed to assess it noninvasively. Studies on the variability of both evoked brain response and spontaneous brain signals have shown remarkable changes with aging but it is unclear if the different measures of brain signal variability - identified with either hemodynamic or electrophysiological methods - reflect the same underlying physiology. In this study, we aimed to explore age differences of spontaneous brain signal variability with two different imaging modalities (EEG, fMRI) in healthy younger (25 ​± ​3 years, N ​= ​135) and older (67 ​± ​4 years, N ​= ​54) adults. Consistent with the previous studies, we found lower blood oxygenation level dependent (BOLD) variability in the older subjects as well as less signal variability in the amplitude of low-frequency oscillations (1-12 ​Hz), measured in source space. These age-related reductions were mostly observed in the areas that overlap with the default mode network. Moreover, age-related increases of variability in the amplitude of beta-band frequency EEG oscillations (15-25 ​Hz) were seen predominantly in temporal brain regions. There were significant sex differences in EEG signal variability in various brain regions while no significant sex differences were observed in BOLD signal variability. Bivariate and multivariate correlation analyses revealed no significant associations between EEG- and fMRI-based variability measures. In summary, we show that both BOLD and EEG signal variability reflect aging-related processes but are likely to be dominated by different physiological origins, which relate differentially to age and sex.

Association of Polygenic Liability for Alcohol Dependence and EEG Connectivity in Adolescence and Young Adulthood

Differences in the connectivity of large-scale functional brain networks among individuals with alcohol use disorders (AUD), as well as those at risk for AUD, point to dysfunctional neural communication and related cognitive impairments. In this study, we examined how polygenic risk scores (PRS), derived from a recent GWAS of DSM-IV Alcohol Dependence (AD) conducted by the Psychiatric Genomics Consortium, relate to longitudinal measures of interhemispheric and intrahemispheric EEG connectivity (alpha, theta, and beta frequencies) in adolescent and young adult offspring from the Collaborative Study on the Genetics of Alcoholism (COGA) assessed between ages 12 and 31. Our findings indicate that AD PRS (p-threshold < 0.001) was associated with increased fronto-central, tempo-parietal, centro-parietal, and parietal-occipital interhemispheric theta and alpha connectivity in males only from ages 18-31 (beta coefficients ranged from 0.02-0.06, p-values ranged from 10-6-10-12), but not in females. Individuals with higher AD PRS also demonstrated more performance deficits on neuropsychological tasks (Tower of London task, visual span test) as well as increased risk for lifetime DSM-5 alcohol and opioid use disorders. We conclude that measures of neural connectivity, together with neurocognitive performance and substance use behavior, can be used to further understanding of how genetic risk variants from large GWAS of AUD may influence brain function. In addition, these data indicate the importance of examining sex and developmental effects, which otherwise may be masked. Understanding of neural mechanisms linking genetic variants emerging from GWAS to risk for AUD throughout development may help to identify specific points when neurocognitive prevention and intervention efforts may be most effective.

Neural Efficiency of Human-Robotic Feedback Modalities Under Stress Differs With Gender

Sensory feedback, which can be presented in different modalities - single and combined, aids task performance in human-robotic interaction (HRI). However, combining feedback modalities does not always lead to optimal performance. Indeed, it is not known how feedback modalities affect operator performance under stress. Furthermore, there is limited information on how feedback affects neural processes differently for males and females and under stress. This is a critical gap in the literature, particularly in the domain of surgical robotics, where surgeons are under challenging socio-technical environments that burden them physiologically. In the present study, we posited operator performance as the summation of task performance and neurophysiological cost of maintaining that performance. In a within-subject design, we used functional near-infrared spectroscopy to assess cerebral activations of 12 participants who underwent a 3D manipulation task within a virtual environment with concurrent feedback (visual and visual + haptic) in the presence and absence of a cognitive stressor. Cognitive stress was induced with the serial-7 subtraction test. We found that while task performance was higher with visual than visual + haptic feedback, it degraded under stress. The two feedback modalities were found to be associated with varying neural activities and neural efficiencies, and these were stress- and gender-dependent. Our findings engender further investigation into effectiveness of feedback modalities on males and females under stressful conditions in HRI.

Sex Differences in the Complexity of Healthy Older Adults' Magnetoencephalograms

The analysis of resting-state brain activity recording in magnetoencephalograms (MEGs) with new algorithms of symbolic dynamics analysis could help obtain a deeper insight into the functioning of the brain and identify potential differences between males and females. Permutation Lempel-Ziv complexity (PLZC), a recently introduced non-linear signal processing algorithm based on symbolic dynamics, was used to evaluate the complexity of MEG signals in source space. PLZC was estimated in a broad band of frequencies (2–45 Hz), as well as in narrow bands (i.e., theta (4–8 Hz), alpha (8–12 Hz), low beta (12–20 Hz), high beta (20–30 Hz), and gamma (30–45 Hz)) in a sample of 98 healthy elderly subjects (49 males, 49 female) aged 65–80 (average age of 72.71 ± 4.22 for males and 72.67 ± 4.21 for females). PLZC was significantly higher for females than males in the high beta band at posterior brain regions including the precuneus, and the parietal and occipital cortices. Further statistical analyses showed that higher complexity values over highly overlapping regions than the ones mentioned above were associated with larger hippocampal volumes only in females. These results suggest that sex differences in healthy aging can be identified from the analysis of magnetoencephalograms with novel signal processing methods.

A hybrid model for EEG-based gender recognition

The gender recognition is an important research field to study evidence regarding some personal characteristics in the information and data society. However, some current traditional methods such as vision and sound have been exposed their own security weaknesses. Recently, biometric gender recognition based on Electroencephalography (EEG) signals has been widely used in information safety and medical fields. It is necessary to explore potential of using EEG to present a more robust and accurate result with larger training data based on sophisticated machine learning approaches. In this contribution, we present an automated gender recognition system by a hybrid model based on EEG data of resting state from twenty-eight subjects. These data are useful and handy to get insights into assessing the differences in personal gender. For achieving a good performance and a strong robustness, the system develops a hybrid model of combining random forest and logistic regression, and employs four common entropy measures to analyze the non-stationary EEG signals. Result also suggests that the recognition performance achieve an improved progress with an accuracy of 0.9982 and AUC of 0.9926 based on a nested tenfold cross-validation loop, implying that show a significant potential applicability of the proposed approach and is capable of recognizing personal gender.

Individual EEG alpha profiles are gender-dependent and indicate subjective experiences in Whole-Body Perceptual Deprivation

We use a unique environment of Whole Body Perceptual Deprivation (WBPD) to induce an altered state of consciousness (ASC) in our participants, and employ online EEG recording. We present individual EEG alpha profiles, and show how these data can be analyzed at the individual level. Our goal is to investigate to what degree subjective experience matches EEG alpha profile, and in particular, the various alpha hemispheric asymmetries observed in the frontal, parietal, and occipital lobes. Specifically, we consider positive (frontal L < R) or negative (frontal L > R) affect; a more verbal (L > R) or a more imagistic (R > L) mode of thinking; and a more trancelike (frontal > parietal) or more reflective (frontal < parietal) state of consciousness. Our results indicate that the individual alpha profiles are reflected in individual differences in subjective experience. However, the alpha profiles are confounded with the gender of the participant. Specifically, there is a predominant R > L asymmetry found for male participants, and a predominant L > R asymmetry found for female participants.

Resting heart rate variability in young women is a predictor of EEG reactions to linguistic ambiguity in sentences

Recent research has found a relationship between heart rate variability (HRV) and cognitive control mechanisms underlying various experimental tasks. This study explored the interaction between gender and resting-state HRV in brain oscillatory activity during visual recognition of linguistic ambiguity while taking state and trait anxiety scores into account. It is well known that stress or anxiety increases arousal levels, particularly under uncertainty situations. We tasked 50 young Mandarin speakers (26 women; average age 26.00 ± 4.449) with the recognition of linguistic ambiguity in English (foreign) sentences with the purpose of imposing a sense of uncertainty in decision-making. Our results revealed a dependency between resting-state HRV and theta/alpha power in individual women. Low HRV women showed stronger theta/alpha desynchronization compared with their high HRV counterparts, independent of topographic localization. However, low and high HRV men exhibited comparable theta/alpha activity. Trait anxiety scores affected alpha power in the parieto-occipital regions, whereas men with higher scores and women with lower scores showed stronger alpha desynchronization. We posit that stress-provoking situations may impose additional effects on theta/alpha desynchronization in the frontal and temporal regions, a condition in which the interdependency between brain oscillatory activity and resting-state HRV could interact with cognitive control differently in men and women.

Hemodynamic effects of sex and handedness on the Wisconsin Card Sorting Test: the contradiction between neuroimaging and behavioural results

This study investigated the potential role of sex and handedness on the performance of a computerised Wisconsin Card Sorting Test (WCST) in healthy participants by applying functional near-infrared spectroscopy (fNIRS). We demonstrated significant (p < 0.05) sex-related differences of hemodynamic response in the prefrontal cortex of 70 healthy participants (female, n = 35 and male, n = 35; right-handed, n = 40 and left-handed, n = 30). In contrast, behavioural results of the WCST do not show sex bias, which is consistent with previous literature. Because of this, we compared ours and sparse previous fNIRS studies on the WCST. We propose that, according to recent studies of neurovascular coupling, this contradiction between neuroimaging and behavioural results may be explained by normal variability in neurovascular dynamics.

Developmental changes in the cortical sources of spontaneous alpha throughout adolescence

This study investigated age-, gender-, and puberty-related changes in two cortical sources of spontaneous alpha during eyes-open and eyes-closed conditions in a cohort of adolescents aged 9-23 years. In total, 29 preadolescents (9-12 years, 14 females), 29 mid-adolescents (13-17 years, 14 females), and 33 late adolescents (18-23 years, 17 females) had their resting brain activity measured using electroencephalography (EEG) during eyes-open and eyes-closed conditions. Standardised Low Resolution Brain Electromagnetic Tomography (sLORETA) was used to estimate the cortical sources of spontaneous alpha. Two cortical sources were chosen as regions of interest (ROIs): prefrontal cortex and occipital cortex. Significant age-related changes in the cortical sources of alpha were found, particularly in prefrontal regions; prefrontal alpha power was greater during the eyes-open condition compared to the eyes-closed condition for late adolescents, but equivalent across the eyes-open and eyes-closed conditions for both pre- and mid-adolescents. In addition, more advanced pubertal stage predicted reduced alpha power in male, but not female, adolescents aged 9-17 years. This study provides an important initial step towards understanding developmental changes in the cortical sources of spontaneous alpha in the typically developing brain. Moreover, the results from this study underscore the need to tease out the effects of age, gender, and puberty when examining the cortical sources of alpha during the adolescent period.

Functionally disconnected: A look at how study design influences neurofeedback data and mechanisms in attention-deficit/hyperactivity disorder

Neurofeedback (NF) is a form of behavioral therapy used to treat e.g. attention-deficit/hyperactivity disorder (ADHD). Briefly, subjects are fed-back a putatively dysfunctional parameter of their brain activity in real time and must learn to control it in a suggested direction. NF protocols for ADHD have been used in practice for decades, though no clear standards on NF design have been implemented. Furthermore, studies often present only data from the general outcome of the NF treatment and do not look at how exactly the NF paradigm affects brain functionality, or what exactly the NF is training. The current study is two-fold: firstly, we look at how the functional connectivity (FC) patterns within key networks associated with ADHD differ between rests, feedback trials, success and failure in a complete functional near-infrared spectroscopy-based NF experiment on adults with ADHD. Secondly, due to methodological concerns discovered during the analysis of our data, we address important considerations in the design of NF that are often ignored in protocols being used widely in therapy and research today. In particular, we examine the common average reference and its impact on network activity as well as the importance of balancing the randomization in a design. Finally, we discuss how these methodological considerations may have influenced our FC results.

Estimation of Complexity of Sampled Biomedical Continuous Time Signals Using Approximate Entropy

Non-linear analysis found many applications in biomedicine. Approximate entropy (ApEn) is a popular index of complexity often applied to biomedical data, as it provides quite stable indications when processing short and noisy epochs. However, ApEn strongly depends on parameters, which were chosen in the literature in wide ranges. This paper points out that ApEn depends on sampling rate of continuous time signals, embedding dimension, tolerance (under which a match is identified), epoch duration and low frequency trends. Moreover, contradicting results can be obtained changing parameters. This was found both in simulations and in experimental EEG. These limitations of ApEn suggest the introduction of an alternative index, here called modified ApEn, which is based on the following principles: oversampling is compensated, self-recurrences are ignored, a fixed percentage of recurrences is selected and low frequency trends are removed. The modified index allows to get more stable measurements of the complexity of the tested simulated data and EEG. The final conclusions are that, in order to get a reliable estimation of complexity using ApEn, parameters should be chosen within specific ranges, data must be sampled close to the Nyquist limit and low frequency trends should be removed. Following these indications, different studies could be more easily compared, interpreted and replicated. Moreover, the modified ApEn can be an interesting alternative, which extends the range of parameters for which stable indications can be achieved.

The right thalamus may play an important role in anesthesia-awakening regulation in frogs

Background

Previous studies have shown that the mammalian thalamus is a key structure for anesthesia-induced unconsciousness and anesthesia-awakening regulation. However, both the dynamic characteristics and probable lateralization of thalamic functioning during anesthesia-awakening regulation are not fully understood, and little is known of the evolutionary basis of the role of the thalamus in anesthesia-awakening regulation.

Methods

An amphibian species, the South African clawed frog (Xenopus laevis) was used in the present study. The frogs were immersed in triciane methanesulfonate (MS-222) for general anesthesia. Electroencephalogram (EEG) signals were recorded continuously from both sides of the telencephalon, diencephalon (thalamus) and mesencephalon during the pre-anesthesia stage, administration stage, recovery stage and post-anesthesia stage. EEG data was analyzed including calculation of approximate entropy (ApEn) and permutation entropy (PE).

Results

Both ApEn and PE values differed significantly between anesthesia stages, with the highest values occurring during the awakening period and the lowest values during the anesthesia period. There was a significant correlation between the stage durations and ApEn or PE values during anesthesia-awakening cycle primarily for the right diencephalon (right thalamus). ApEn and PE values for females were significantly higher than those for males.

Discussion

ApEn and PE measurements are suitable for estimating depth of anesthesia and complexity of amphibian brain activity. The right thalamus appears physiologically positioned to play an important role in anesthesia-awakening regulation in frogs indicating an early evolutionary origin of the role of the thalamus in arousal and consciousness in land vertebrates. Sex differences exist in the neural regulation of general anesthesia in frogs.

Gender differences in brain networks during verbal Sternberg tasks: A simultaneous near-infrared spectroscopy and electro-encephalography study

Gender differences in psychological processes have been of great interest in a variety of fields including verbal fluency, emotion processing and working memory. Previous studies suggested that women outperform men in verbal working memory (VWM). However, the inherent mechanisms are still unclear. To obtain a deeper insight into the gender differences in brain networks in VWM, this study used near-infrared spectroscopy (NIRS) and electro-encephalography (EEG) simultaneously to investigate gender-related brain networks during verbal Sternberg tasks. NIRS results confirmed that women surpass men in VWM from the perspective of both brain activation and connectivity. Results of EEG (effective connectivity and event-related spectral power) showed that men tend to use a more visuospatial strategy to encode memory. In addition, novel analysis methods of brain networks can provide useful information about the gender specifics of brain functions. Gender-related pseudo-color maps constructed from all channels of average HbO₂ activity during low- and high-load tasks (from 0 to 6 seconds after beginning).

Effect of essential oil and supercritical carbon dioxide extract from the root of Angelica gigas on human EEG activity

OBJECTIVES

The present study aimed to investigate the effect of inhalation of essential oil (EO) and supercritical carbon dioxide extract (SC-CO₂) from the root of A. gigas on human electroencephalographic (EEG) activity.

MATERIALS AND METHODS

For this purpose, the EO was obtained from the root of A. gigas by steam distillation and SC-CO₂ was obtained at 50 °C and 400 bar for 1 h. The EEG readings were recorded using the QEEG-8 system from 8 electrode sites according to the International 10-20 system.

RESULTS

In the EEG study, the absolute low beta (left temporal and left parietal) activity significantly increased during the inhalation of EO. In the case of SC-CO₂ inhalation, there was no significant change in absolute waves.

CONCLUSION

The results revealed that the EO of A. gigas root produced significant changes in the absolute low beta activity and these changes may enhance the language learning abilities of human brain.

Encephalography Connectivity on Sources in Male Nonsmokers after Nicotine Administration during the Resting State

We present an encephalography (EEG) connectivity study where 30 healthy male nonsmokers were randomly allocated either to a nicotine group (14 subjects, 7 mg of transdermal nicotine) or to a placebo group. EEG activity was recorded in an eyes-open (EO) and eyes-closed (EC) condition before and after drug administration. This is a reanalysis of a previous dataset. Through a source reconstruction procedure, we extracted 13 time series representing 13 sources belonging to a resting-state network. Here, we conducted connectivity analysis (renormalized partial directed coherence; rPDC) on sources, focusing on the frequency range of 8.5-18.4 Hz, subdivided into 3 frequency bands (α1, α2, and β1) with the hypothesis that an increase in vigilance would modulate connectivity. Furthermore, a phase-amplitude coupling (mean resultant vector length; VL) analysis, was performed investigating whether an increase of vigilance would modulate phase-amplitude coupling. In the VL analysis we estimated the coupling of the phases of 3 low frequencies (α1, α2, and β1), respectively, with the amplitude of high-frequency oscillations (30-40 Hz, low γ). With rPDC we found that during the EC condition, nicotine decreased feedback connectivity (from the precentral gyrus to precuneus, angular gyrus, cuneus and superior occipital gyrus) at 10.5-12.4 Hz. The VL analysis showed nicotine-induced increases in coupling at 10.5-18.4 Hz in the precuneus, cuneus and superior occipital gyrus during the EC condition. During the EO condition, no significant results were found in connectivity or phase-amplitude coupling measures at any frequency range. In conclusion, the results suggest that nicotine potentially increases the level of vigilance in the EC condition.

EEG Source Reconstruction in Male Nonsmokers after Nicotine Administration during the Resting State

Modern psychopharmacological research in humans focuses on how specific psychoactive molecules modulate oscillatory brain activity. We present state-of-the-art EEG methods applied in a resting-state drug study. Thirty healthy male nonsmokers were randomly allocated either to a nicotine group (14 subjects, 7 mg transdermal nicotine) or a placebo group (16 subjects). EEG activity was recorded in eyes-open (EO) and eyes-closed (EC) conditions before and after drug administration. A source reconstruction (minimum norm algorithm) analysis was conducted within a frequency range of 8.5-18.4 Hz subdivided into three different frequency bands. During EO, nicotine reduced the power of oscillatory activity in the 12.5- to 18.4-Hz frequency band in the left middle frontal gyrus. In contrast, in the EC condition, nicotine reduced the power in the 8.5- to 10.4-Hz frequency band in the superior frontal gyri and in the 10.5- to 12.4-Hz and 12.5- to 18.4-Hz frequency bands in the supplementary motor areas. In summary, nicotine reduced the power of the 12.5- to 18.4-Hz band in the left middle frontal gyrus during EO, and it reduced power from 8.5 to 18.4 Hz in a brain area spanning from the superior frontal gyri to the supplementary motor areas during EC. In conclusion, the results suggest that nicotine counteracts the phenomenon of anteriorization of α activity, hence potentially increasing the level of vigilance.

Making Brains run Faster: are they Becoming Smarter?

A brief overview of structural and functional brain characteristics related to g is presented in the light of major neurobiological theories of intelligence: Neural Efficiency, P-FIT and Multiple-Demand system. These theories provide a framework to discuss the main objective of the paper: what is the relationship between individual alpha frequency (IAF) and g? Three studies were conducted in order to investigate this relationship: two correlational studies and a third study in which we experimentally induced changes in IAF by means of transcranial alternating current stimulation (tACS). (1) In a large scale study (n = 417), no significant correlations between IAF and IQ were observed. However, in males IAF positively correlated with mental rotation and shape manipulation and with an attentional focus on detail. (2) The second study showed sex-specific correlations between IAF (obtained during task performance) and scope of attention in males and between IAF and reaction time in females. (3) In the third study, individuals’ IAF was increased with tACS. The induced changes in IAF had a disrupting effect on male performance on Raven’s matrices, whereas a mild positive effect was observed for females. Neuro-electric activity after verum tACS showed increased desynchronization in the upper alpha band and dissociation between fronto-parietal and right temporal brain areas during performance on Raven’s matrices. The results are discussed in the light of gender differences in brain structure and activity.

Influence of Binasal and Uninasal Inhalations of Essential Oil of Abies koreana Twigs on Electroencephalographic Activity of Human

Objectives. The present work investigates the effect of essential oil from the twigs of Abies koreana on electroencephalographic (EEG) activity of human brain in order to understand the influence of binasal and uninasal inhalations. Methods. To accomplish this study, the essential oil from the twigs of A. koreana (AEO) was isolated by steam distillation and the EEG readings were recorded using QEEG-8 system from 8 grounding electrodes according to the International 10-20 System. Results. D-Limonene (25.29%), bornyl acetate (19.31%), camphene (12.48%), α-pinene (11.88%), β-pinene (6.45%), and eudesm-7(11)-en-ol (5.38%) were the major components in the essential oil. In the EEG study, the absolute alpha (left frontal and right parietal) and absolute fast alpha (right parietal) values significantly increased during the binasal inhalation of AEO. In the uninasal inhalation, absolute beta and theta values decreased significantly, especially in the right frontal and left and right parietal regions. The results revealed that the AEO produced different EEG power spectrum changes according to the nostril difference. Conclusion. The changes in EEG values due to the inhalation of AEO may contribute to the enhancement of relaxation (binasal inhalation) and alertness/attention (right uninasal inhalation) states of brain which could be used in aromatherapy treatments.

Influence of Fragrances on Human Psychophysiological Activity: With Special Reference to Human Electroencephalographic Response

The influence of fragrances such as perfumes and room fresheners on the psychophysiological activities of humans has been known for a long time, and its significance is gradually increasing in the medicinal and cosmetic industries. A fragrance consists of volatile chemicals with a molecular weight of less than 300 Da that humans perceive through the olfactory system. In humans, about 300 active olfactory receptor genes are devoted to detecting thousands of different fragrance molecules through a large family of olfactory receptors of a diverse protein sequence. The sense of smell plays an important role in the physiological effects of mood, stress, and working capacity. Electrophysiological studies have revealed that various fragrances affected spontaneous brain activities and cognitive functions, which are measured by an electroencephalograph (EEG). The EEG is a good temporal measure of responses in the central nervous system and it provides information about the physiological state of the brain both in health and disease. The EEG power spectrum is classified into different frequency bands such as delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz) and gamma (30-50 Hz), and each band is correlated with different features of brain states. A quantitative EEG uses computer software to provide the topographic mapping of the brain activity in frontal, temporal, parietal and occipital brain regions. It is well known that decreases of alpha and beta activities and increases of delta and theta activities are associated with brain pathology and general cognitive decline. In the last few decades, many scientific studies were conducted to investigate the effect of inhalation of aroma on human brain functions. The studies have suggested a significant role for olfactory stimulation in the alteration of cognition, mood, and social behavior. This review aims to evaluate the available literature regarding the influence of fragrances on the psychophysiological activities of humans with special reference to EEG changes.

Altered neuronal spontaneous activity correlates with glutamate concentration in medial prefrontal cortex of major depressed females: An fMRI-MRS study

BACKGROUND

Major depressive disorder (MDD) is twice more prevalent in females than in males. Yet, there have only been a few studies on the functional brain activity in female MDD patients and the detailed mechanisms underlying their neurobiology merit further investigations. In the present work, we used combined fMRI-MRS methods to investigate the altered intrinsic neuronal activity and its association with neurotransmitter concentration in female MDD patients.

METHODS

The whole brain amplitude of low frequency fluctuation (ALFF) analysis using resting state functional magnetic resonance imaging (fMRI) was performed to explore the alteration of intrinsic neuronal signals in MDD females (n=11) compared with female healthy controls (n=11). With a specific interest in the medial prefrontal cortex (mPFC) area, we quantified the concentration of amino acid neurotransmitters including GABA ((r-aminobutyric acid)), Glu (Glutamate), and Glx (Glutamate + Glutamine) using (1)H-MRS technology. Moreover, we conducted Pearson correlation analysis between the ALFF value and neurotransmitter concentration to find out the functional-biochemical relation in mPFC area. The relationship between the metabolites concentration and MDD symptomatology was also examined through Spearman correlation analysis.

RESULTS

We found that the female MDD patients showed increased neuronal spontaneous activity in left medial prefrontal cortex (mPFC) and left middle frontal cortex, with decreased ALFF level in right putamen and right middle temporal cortex (p<0.01, Alphasim corrected). The ALFF in mPFC was shown positively correlated with Glu concentration in female MDD patients (r=0.67, p=0.023). The Glu concentration in mPFC was positively correlated with patients HAMA scores (r=0.641, p=0.033).

LIMITATIONS

The relatively small sample size, metabolite information acquired only in mPFC and not all patients were unmedicated are the major limitations of our study.

CONCLUSIONS

Using combined fMRI-MRS methods, we found increased spontaneous neuronal activity was correlated with Glu concentration in mPFC of female MDD patients. Other regions including left middle frontal gyrus, right putamen and middle temporal gyrus also showed altered spontaneous neuronal activities. The abnormal intrinsic neuronal activities in fronto-cortical regions shed light on the pathogenesis underlying MDD females. The multimodal resting-state neuroimaging technique served as a useful tool for functional-biochemical investigation of MDD pathophysiology.

Interhemispheric Asymmetries and Theta Activity in the Rostral Anterior Cingulate Cortex as EEG Signature of HIV-Related Depression: Gender Matters

Resting EEGs of 40 people living with HIV (PLWH) on long-term antiretroviral treatment were examined for z-scored deviations from a healthy control (normative database) to examine the main and interaction effects of depression and gender. Regions of interest were frontal (alpha) and central (all bands) for interhemispheric asymmetries in quantitative EEGs and theta in the rostral anterior cingulate cortex (rACC) in low-resolution electromagnetic tomography (LORETA). Z-scored normed deviations of depressed PLWH, compared with nondepressed, showed right-dominant interhemispheric asymmetries in all regions. However, after adjusting for multiple testing, significance remained only central for theta, alpha, and beta. Reversed (left-dominant) frontal alpha asymmetry is a potential EEG marker of depression in the HIV negative population that was not reversed in depressive PLWH; however, corresponding with extant literature, gender had an effect on the size of frontal alpha asymmetry. The LORETA analysis revealed a trending interactional effect of depression and gender on theta activity in the rACC in Brodmann area 32. We found that compared to men, women had greater right-dominant frontal alpha-asymmetry and elevated theta activity in voxels of the rACC, which may indicate less likelihood of depression and a higher likelihood of response to antidepressants. In conclusion, subtle EEG deviations, such as right-dominant central theta, alpha, and beta asymmetries and theta activity in the rACC may mark HIV-related depressive symptoms and may predict the likelihood of response to antidepressants but gender effects need to be taken into account. Although this study introduced the use of LORETA to examine the neurophysiological correlates of negative affect in PLWH, further research is needed to assess the utility of this tool in diagnostics and treatment monitoring of depression in PLWH.

Mesolimbic confidence signals guide perceptual learning in the absence of external feedback

It is well established that learning can occur without external feedback, yet normative reinforcement learning theories have difficulties explaining such instances of learning. Here, we propose that human observers are capable of generating their own feedback signals by monitoring internal decision variables. We investigated this hypothesis in a visual perceptual learning task using fMRI and confidence reports as a measure for this monitoring process. Employing a novel computational model in which learning is guided by confidence-based reinforcement signals, we found that mesolimbic brain areas encoded both anticipation and prediction error of confidence—in remarkable similarity to previous findings for external reward-based feedback. We demonstrate that the model accounts for choice and confidence reports and show that the mesolimbic confidence prediction error modulation derived through the model predicts individual learning success. These results provide a mechanistic neurobiological explanation for learning without external feedback by augmenting reinforcement models with confidence-based feedback.

DOI:http://dx.doi.org/10.7554/eLife.13388.001

Much of our behavior is shaped by feedback from the environment. We repeat behaviors that previously led to rewards and avoid those with negative outcomes. At the same time, we can learn in many situations without such feedback. Our ability to perceive sensory stimuli, for example, improves with training even in the absence of external feedback.

Guggenmos et al. hypothesized that this form of perceptual learning may be guided by self-generated feedback that is based on the confidence in our performance. The general idea is that the brain reinforces behaviors associated with states of high confidence, and weakens behaviors that lead to low confidence.

To test this idea, Guggenmos et al. used a technique called functional magnetic resonance imaging to record the brain activity of healthy volunteers as they performed a visual learning task. In this task, the participants had to judge the orientation of barely visible line gratings and then state how confident they were in their decisions.

Feedback signals derived from the participants’ confidence reports activated the same brain areas typically engaged for external feedback or reward. Moreover, just as these regions were previously found to signal the difference between actual and expected rewards, so did they signal the difference between actual confidence levels and those expected on the basis of previous confidence levels. This parallel suggests that confidence may take over the role of external feedback in cases where no such feedback is available. Finally, the extent to which an individual exhibited these signals predicted overall learning success.

Future studies could investigate whether these confidence signals are automatically generated, or whether they only emerge when participants are required to report their confidence levels. Another open question is whether such self-generated feedback applies in non-perceptual forms of learning, where learning without feedback has likewise been a long-standing puzzle.

DOI:http://dx.doi.org/10.7554/eLife.13388.002

EEG alpha frequency correlates of burnout and depression: The role of gender

EEG alpha frequency band biomarkers of depression are widely explored. Due to their trait-like features, they may help distinguish between depressive and burnout symptomatology, which is often referred to as "work-related depression". The present correlational study strived to examine whether individual alpha frequency (IAF), power, and coherence in the alpha band can provide evidence for establishing burnout as a separate diagnostic entity. Resting EEG (eyes closed) was recorded in 117 individuals (42 males). In addition, the participants filled-out questionnaires of burnout and depression. Regression analyses highlighted the differential value of IAF and power in predicting burnout and depression. IAF was significantly related to depressive symptomatology, whereas power was linked mostly to burnout. Moreover, seven out of twelve interactions between EEG indicators and gender were significant. Connectivity patterns were significant for depression displaying gender-related differences. The results offer tentative support for establishing burnout as a separate clinical syndrome.