Temporal stability of posterior EEG alpha over twelve years

A posterior-alpha ageing network is differentially associated with antidepressant effects of venlafaxine and rTMS

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder, but chances for remission largely decrease with each failed treatment attempt. It is therefore desirable to assign a given patient to the most promising individual treatment option as early as possible. We used a polygenic score (PGS) informed electroencephalography (EEG) data-driven approach to identify potential predictors for MDD treatment outcome. Post-hoc we conducted exploratory analyses in order to understand the results in depth. First, an EEG independent component analysis produced 54 functional brain networks in a large heterogeneous cohort of psychiatric patients (n = 4,045; 5-84 yrs.). Next, the network that was associated to PGS for antidepressant-response (PRS-AR) in an independent sample (n = 722) was selected: an age-related posterior alpha network that explained >60 % of EEG variance, and was highly stable over recording time. Translational analyses were performed in two other independent datasets to examine if the network was predictive of psychopharmacotherapy (n = 535) and/or repetitive transcranial magnetic stimulation (rTMS) and concomitant psychotherapy (PT; n = 186) outcome. The network predicted remission to venlafaxine (p = 0.015), resulting in a normalized positive predicted value (nPPV) of 138 %, and rTMS + PT - but in opposite direction for women (p = 0.002) relative to men (p = 0.018) - yielding a nPPV of 131 %. Blinded out-of-sample validations for venlafaxine (n = 29) and rTMS + PT (n = 36) confirmed the findings for venlafaxine, while results for rTMS + PT could not be replicated. These data suggest the existence of a relatively stable EEG posterior alpha aging network related to PGS-AR that has potential as MDD treatment predictor.

Closed-loop neurostimulation for the treatment of psychiatric disorders

Despite increasing prevalence and huge personal and societal burden, psychiatric diseases still lack treatments which can control symptoms for a large fraction of patients. Increasing insight into the neurobiology underlying these diseases has demonstrated wide-ranging aberrant activity and functioning in multiple brain circuits and networks. Together with varied presentation and symptoms, this makes one-size-fits-all treatment a challenge. There has been a resurgence of interest in the use of neurostimulation as a treatment for psychiatric diseases. Initial studies using continuous open-loop stimulation, in which clinicians adjusted stimulation parameters during patient visits, showed promise but also mixed results. Given the periodic nature and fluctuations of symptoms often observed in psychiatric illnesses, the use of device-driven closed-loop stimulation may provide more effective therapy. The use of a biomarker, which is correlated with specific symptoms, to deliver stimulation only during symptomatic periods allows for the personalized therapy needed for such heterogeneous disorders. Here, we provide the reader with background motivating the use of closed-loop neurostimulation for the treatment of psychiatric disorders. We review foundational studies of open- and closed-loop neurostimulation for neuropsychiatric indications, focusing on deep brain stimulation, and discuss key considerations when designing and implementing closed-loop neurostimulation.

Temporal stability and correlation of EEG markers and depression questionnaires scores in healthy people

Mental disorders, especially depression, have become a rising problem in modern society. The development of methods and markers for the early detection of mental disorders is an actual problem. Psychological questionnaires are the only tools for evaluating the symptoms of mental disorders in clinical practice today. The electroencephalography (EEG) based non-invasive and cost-effective method seems feasible for the early detection of depression in occupational and family medicine centers and personal monitoring. The reliability of the EEG markers in the early detection of depression assumes their high temporal stability and correlation with the scores of depression questionnaires. The study was been performed on 17 healthy people over three years. Two hypotheses have been evaluated in the current study: first, the temporal stability of EEG markers is close to the stability of the scores of depression questionnaires, and second, EEG markers and depression questionnaires' scores are not correlated in healthy people. The results of the performed study support both hypotheses: the temporal stability of EEG markers is high and close to the stability of depression questionnaires scores and the correlation between the EEG markers and depression questionnaires scores is not detected in healthy people. The results of the current study contribute to the interpretation of results in depression EEG studies and to the feasibility of EEG markers in the detection of depression.

A genetic variation in the adenosine A2A receptor gene contributes to variability in oscillatory alpha power in wake and sleep EEG and A1 adenosine receptor availability in the human brain

The EEG alpha rhythm (∼ 8-13 Hz) is one of the most salient human brain activity rhythms, modulated by the level of attention and vigilance and related to cerebral energy metabolism. Spectral power in the alpha range in wakefulness and sleep strongly varies among individuals based on genetic predisposition. Knowledge about the underlying genes is scarce, yet small studies indicated that the variant rs5751876 of the gene encoding A2A adenosine receptors (ADORA2A) may contribute to the inter-individual variation. The neuromodulator adenosine is directly linked to energy metabolism as product of adenosine tri-phosphate breakdown and acts as a sleep promoting molecule by activating A1 and A2A adenosine receptors. We performed sleep and positron emission tomography studies in 59 healthy carriers of different rs5751876 alleles, and quantified EEG oscillatory alpha power in wakefulness and sleep, as well as A1 adenosine receptor availability with 18F-CPFPX. Oscillatory alpha power was higher in homozygous C-allele carriers (n = 27, 11 females) compared to heterozygous and homozygous carriers of the T-allele (n(C/T) = 23, n(T/T) = 5, 13 females) (F(18,37) = 2.35, p = 0.014, Wilk's Λ = 0.487). Furthermore, a modulatory effect of ADORA2A genotype on A1 adenosine receptor binding potential was found across all considered brain regions (F(18,40) = 2.62, p = 0.006, Wilk's Λ = 0.459), which remained significant for circumscribed occipital region of calcarine fissures after correction for multiple comparisons. In female participants, a correlation between individual differences in oscillatory alpha power and A1 receptor availability was observed. In conclusion, we confirmed that a genetic variant of ADORA2A affects individual alpha power, while a direct modulatory effect via A1 adenosine receptors in females is suggested.

Stability, change, and reliable individual differences in electroencephalography measures: a lifespan perspective on progress and opportunities

Electroencephalographic (EEG) methods have great potential to serve both basic and clinical science approaches to understand individual differences in human neural function. Importantly, the psychometric properties of EEG data, such as internal consistency and test-retest reliability, constrain their ability to differentiate individuals successfully. Rapid and recent technological and computational advancements in EEG research make it timely to revisit the topic of psychometric reliability in the context of individual difference analyses. Moreover, pediatric and clinical samples provide some of the most salient and urgent opportunities to apply individual difference approaches, but the changes these populations experience over time also provide unique challenges from a psychometric perspective. Here we take a developmental neuroscience perspective to consider progress and new opportunities for parsing the reliability and stability of individual differences in EEG measurements across the lifespan. We first conceptually map the different profiles of measurement reliability expected for different types of individual difference analyses over the lifespan. Next, we summarize and evaluate the state of the field's empirical knowledge and need for testing measurement reliability, both internal consistency and test-retest reliability, across EEG measures of power, event-related potentials, nonlinearity, and functional connectivity across ages. Finally, we highlight how standardized pre-processing software for EEG denoising and empirical metrics of individual data quality may be used to further improve EEG-based individual differences research moving forward. We also include recommendations and resources throughout that individual researchers can implement to improve the utility and reproducibility of individual differences analyses with EEG across the lifespan.

Neural Dynamics of a Single Human with Long-Term, High Temporal Density Electroencephalography

We undertake a longitudinal study with high temporal recording density, capturing daily electroencephalograms (EEG) of an individual in an in-situ setting for 370 consecutive days. Resting-state EEG retains a high level of stability over the course of the year, and inter-session variability remains unchanged, whether the sessions are one day, one week, or one month apart. On the other hand, EEG for certain cognitive tasks experience a steady decline in similarity over the same time period. Clustering analysis reveals that days with low similarity scores should not be considered as outliers, but instead are part of a cluster of days with a consistent alternate spectral signature. This has methodological and design implications for the selection of baseline references or templates in fields ranging from neurophysiology to brain-computer interfaces (BCI) and neurobiometrics.

Frontal and parietal EEG alpha asymmetry: a large-scale investigation of short-term reliability on distinct EEG systems

EEG resting-state alpha asymmetry is one of the most widely investigated forms of functional hemispheric asymmetries in both basic and clinical neuroscience. However, studies yield inconsistent results. One crucial prerequisite to obtain reproducible results is the reliability of the index of interest. There is a body of research suggesting a moderate-to-good reliability of EEG resting-state alpha asymmetry, but unfortunately sample sizes in these studies are typically small. This study presents the first large-scale short-term reliability study of frontal and parietal EEG resting-state alpha asymmetry. We used the Dortmund Vital Study data set containing 370 participants. In each participant, EEG resting state was recorded eight times, twice with their eyes opened, twice with their eyes-closed, each on two different EEG systems. We found good reliability of EEG alpha power and alpha asymmetry on both systems for electrode pairs. We also found that alpha power asymmetry reliability is higher in the eyes-closed condition than in the eyes-open condition. The frontomedial electrode pair showed weaker reliability than the frontolateral and parietal electrode pairs. Interestingly, we found no population-level alpha asymmetry in frontal electrodes, one of the most investigated electrode sites in alpha asymmetry research. In conclusion, our results suggest that while EEG alpha asymmetry is an overall reliable measure, frontal alpha asymmetry should be assessed using multiple electrode pairs.

Resting posterior alpha power and adolescent major depressive disorder

For several decades, resting electroencephalogram (EEG) alpha oscillations have been used to characterize neurophysiological alterations related to major depressive disorder. Prior research has generally focused on frontal alpha power and asymmetry despite resting alpha being maximal over posterior electrode sites. Research in depressed adults has shown evidence of hemispheric asymmetry for posterior alpha power, however, the resting posterior alpha-depression link among adolescents remains unclear. To clarify the role of posterior alpha among depressed adolescents, the current study acquired eyes-closed 128-channel resting EEG data from 13 to 18 year-old depressed (n = 31) and healthy (n = 35) female adolescents. Results indicated a significant group by hemisphere interaction, as depressed adolescents exhibited significantly larger posterior alpha (i.e., lower brain activity) over the right versus left hemisphere, whereas healthy adolescents showed no hemispheric differences. Relatively greater alpha over the right versus left hemisphere correlated with depression symptoms, anhedonia symptoms, rumination, and self-criticism. Further, depressed adolescents had reduced overall posterior alpha compared to healthy youth; though, no associations with symptoms and related traits emerged. Resting posterior alpha may be a promising neurophysiological index of adolescent depression, and more broadly, may relate to risk factors characterized by enhanced perseveration.

Signal quality and power spectrum analysis of remote ultra long-term subcutaneous EEG

OBJECTIVE

Ultra long-term subcutaneous electroencephalography (sqEEG) monitoring is a new modality with great potential for both health and disease, including epileptic seizure detection and forecasting. However, little is known about the long-term quality and consistency of the sqEEG signal, which is the objective of this study.

METHODS

The largest multicenter cohort of sqEEG was analyzed, including 14 patients with epilepsy and 12 healthy subjects, implanted with a sqEEG device (24/7 EEG^™ SubQ), and recorded from 23 to 230 days (median 42 days), with a median data capture rate of 75% (17.9 hours/day). Median power spectral density plots of each subject were examined for physiological peaks, including at diurnal and nocturnal periods. Long-term temporal trends in signal impedance and power spectral features were investigated with subject-specific linear regression models and group-level linear mixed-effects models.

RESULTS

sqEEG spectrograms showed an approximate 1/f power distribution. Diurnal peaks in the alpha range (8-13Hz) and nocturnal peaks in the sigma range (12-16Hz) were seen in the majority of subjects. Signal impedances remained low, and frequency band powers were highly stable throughout the recording periods.

SIGNIFICANCE

The spectral characteristics of minimally invasive, ultra long-term sqEEG are similar to scalp EEG, whereas the signal is highly stationary. Our findings reinforce the suitability of this system for chronic implantation on diverse clinical applications, from seizure detection and forecasting to brain-computer interfaces.

Long-term stability of resting state EEG-based linear and nonlinear measures

This preliminary study is aimed to evaluate the stability of various linear and nonlinear EEG measures over three years on healthy adults. The linear measures, relative powers of EEG frequency bands, interhemispheric (IHAS) and spectral (SASI) asymmetries plus nonlinear Higuchi's fractal dimension (HFD) and detrended fluctuation analyses (DFA), have been calculated from the resting state eyes closed EEG of 17 participants during two sessions separated over three years. Our results indicate that the stability is highest for the nonlinear (HFD and DFA) and the linear (relative powers of EEG frequency bands) EEG measures that use the signal from a single EEG channel and frequency band, followed by the SASI employing signals from a single channel and two frequency bands and lowest for the IHAS employing signals from two channels. The result support the prospect of using EEG-based measures in clinical practice.

Predicting Depression Symptoms in Families at Risk for Depression: Interrelations of Posterior EEG Alpha and Religion/Spirituality

BACKGROUND

Posterior EEG alpha has been identified as a putative biomarker of clinical outcomes in major depression (MDD). Separately, personal importance of religion and spirituality (R/S) has been shown to provide protective benefits for individuals at high familial risk for MDD. This study directly explored the joint value of posterior alpha and R/S on predicting clinical health outcomes of depression.

METHODS

Using a mixed-effects model approach, we obtained virtual estimates of R/S at age 21 using longitudinal data collected at 5 timepoints spanning 25 years. Current source density and frequency principal component analysis was used to quantify posterior alpha in 72-channel resting EEG (eyes open/closed). Depression severity was measured between 5 and 10 years after EEG collection using PHQ-9 and IDAS-GD scales.

RESULTS

Greater R/S (p = .008, η²_p = 0.076) and higher alpha (p = .02, η²_p = 0.056) were separately associated with fewer symptoms across scales. However, an interaction between alpha and R/S (p = .02, η²_p = 0.062) was observed, where greater R/S predicted fewer symptoms with low alpha but high alpha predicted fewer symptoms with lower R/S.

LIMITATIONS

Small-to-medium effect sizes and homogeneity of sample demographics caution overall interpretation and generalizability.

CONCLUSIONS

Findings revealed a complementary role of R/S and alpha in that either variable exerted protective effects only if the other was present at low levels. These findings confirm the relevance of R/S importance and alpha oscillations as predictors of depression symptom severity. More research is needed on the neurobiological mechanism underlying the protective effects of R/S importance for MDD.

Family Risk for Depression and Prioritization of Religion or Spirituality: Early Neurophysiological Modulations of Motivated Attention

The personal importance of religion or spirituality (R/S) has been associated with a lower risk for major depression (MDD), suicidal behavior, reduced cortical thinning and increased posterior EEG alpha, which has also been linked to antidepressant treatment response in MDD. Building on prior event-related potential (ERP) findings using an emotional hemifield paradigm, this study examined whether abnormal early (preconscious) responsivity to negative arousing stimuli, which is indicative of right parietotemporal dysfunction in both MDD patients and individuals at clinical high risk for MDD, is likewise moderated by R/S. We reanalyzed 72-channel ERP data from 127 individuals at high or low family risk for MDD (Kayser et al., 2017, NeuroImage Clin. 14, 692-707) after R/S stratification (low R/S importance, low/high risk, n = 38/61; high R/S importance, n = 15/13). ERPs were transformed to reference-free current source density (CSD) and quantified by temporal principal components analysis (tPCA). This report focused on N2 sink (peak latency 212 ms), the earliest prominent CSD-tPCA component previously found to be sensitive to emotional content. While overall N2 sink reflected activation of occipitotemporal cortex (prestriate/cuneus), as estimated via a distributed inverse solution, affective significance was marked by a relative (i.e., superimposed) positivity. Statistical analyses employed both non-parametric permutation tests and repeated measures ANOVA for mixed factorial designs with unstructured covariance matrix, including sex, age, and clinical covariates. Participants with low R/S importance, independent of risk status, showed greater ERP responsivity to negative than neutral stimuli, particularly over the right hemisphere. In contrast, early emotional ERP responsivity and asymmetry was substantially reduced for high risk individuals with high R/S importance, however, enhanced for low risk individuals with high R/S importance. Hemifield modulations of these effects (i.e., emotional ERP enhancements with left visual field/right hemisphere stimulus presentations) further corroborated these observations. Results suggest down-regulation of a right-lateralized network for salience detection at an early processing stage in high risk and high R/S importance individuals, presumably to prevent overactivation of ventral brain regions further downstream. These findings may point to a neurophysiological mechanism underlying resilience of families at risk for depression with high R/S prioritization.

State and trait neural correlates of the balance between work and nonwork roles

Difficulty managing the demands of work and nonwork roles (often referred to in terms of managing balance) can be detrimental to psychological wellbeing and contribute to occupational burnout. The current study investigated the neural correlates of perceived satisfaction with this balance using both trait and state EEG alpha measures. EEG was recorded from 14 participants in full time employment (12 females, aged 35.1 ± 10.1 years) during a resting state and performance of an auditory oddball task; e-mail and messaging alert sounds were used as target stimuli. It was predicted that dissatisfaction with the balance between work and nonwork roles would be associated with increased resting alpha power, consistent with studies of burnout, and diminished alpha response to oddball distractors, consistent with difficulty suppressing automatic responses to work-related stimuli. Significant correlations between self-reported measures of work/nonwork balance and both resting, and task-related alpha responses, supported our predictions. Furthermore, an exploratory partial correlation between work and nonwork balance and resting EEG, controlling for task-related alpha response, suggested that the three variables were interrelated. We propose that dissatisfaction with work/nonwork balance is associated with a state hypervigilance to work-related cues, and a trait neural marker of fatigue, both symptomatic of lowered cognitive capacity.

The Role of Religiosity in Families at High Risk for Depression

BACKGROUND

About forty years ago we began a study of the offspring of depressed (high-risk) and not depressed (low-risk) parents, matched for age and gender, from the same community. We interviewed all of their biological children, blind to the clinical status of the parents. Over the years, we returned to re-interview the families at baseline, 2, 10, 20, 25 30, and 35 years. As the years went by and the sample grew up, we also interviewed the third generation, the grandchildren. As technology became available, we included measures of electrophysiology and magnetic resonance imaging in order to better understand the mechanisms of risk. At the 10-year follow up, we included measures of religion and spirituality - namely, personal religious/spiritual importance and frequency of religious service attendance. We included these measures in all subsequent waves including a more extensive follow up of religious beliefs at the 35-year follow up.

ISSUES OF FOCUS

This paper describes the study design and highlights the key findings of the role of religious/spiritual belief in the transmission and endurance of depression using clinical and biological approaches.

METHODS

We describe study findings based on clinical measures, as well as physiological measures that employed electrophysiology and magnetic resonance imaging.

RESULTS

Taken together, the findings suggest that religiosity/spirituality is protective against depression in high-risk individuals at both clinical and physiological levels.

IMPLICATIONS

The findings suggest religiosity interacts with both culture and biology in its impact on depression.

Current Understanding of Religion, Spirituality, and Their Neurobiological Correlates

Religion and spirituality (R/S) have been prominent aspects of most human cultures through the ages; however, scientific inquiry into this phenomenon has been limited. We conducted a systematic literature review of research on the neurobiological correlates of R/S, which resulted in 25 reports studying primarily R/S with electroencephalography, structural neuroimaging (MRI), and functional neuroimaging (fMRI, PET). These studies investigated a wide range of religions (e.g., Christianity, Buddhism, Islam) and R/S states and behaviors (e.g., resting state, prayer, judgments) and employed a wide range of methodologies, some of which (e.g., no control group, varying measures of religiosity, small sample sizes) raise concerns about the validity of the results. Despite these limitations, the findings of these studies collectively suggest that the experience of R/S has specific neurobiological correlates and that these correlates are distinct from non-R/S counterparts. The findings implicate several brain regions potentially associated with R/S development and behavior, including the medial frontal cortex, orbitofrontal cortex, precuneus, posterior cingulate cortex, default mode network, and caudate. This research may suggest future clinical applications and interventions related to R/S and various disorders, including mood, anxiety, psychotic, pain, and vertiginous disorders. Further studies with more rigorous study designs are warranted to elucidate the neurobiological mechanisms of R/S and their potential clinical applications.

Resting EEG Measures of Brain Arousal in a Multisite Study of Major Depression

Several studies have found upregulated brain arousal during 15-minute EEG recordings at rest in depressed patients. However, studies based on shorter EEG recording intervals are lacking. Here we aimed to compare measures of brain arousal obtained from 2-minute EEGs at rest under eyes-closed condition in depressed patients and healthy controls in a multisite project-Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC). We expected that depressed patients would show stable and elevated brain arousal relative to controls. Eighty-seven depressed patients and 36 healthy controls from four research sites in the United States were included in the analyses. The Vigilance Algorithm Leipzig (VIGALL) was used for the fully automatic classification of EEG-vigilance stages (indicating arousal states) of 1-second EEG segments; VIGALL-derived measures of brain arousal were calculated. We found that depressed patients scored higher on arousal stability ( Z = -2.163, P = .015) and A stages (dominant alpha activity; P = .027) but lower on B1 stages (low-voltage non-alpha activity, P = .008) compared with healthy controls. No significant group differences were observed in Stage B2/3. In summary, we were able to demonstrate stable and elevated brain arousal during brief 2-minute recordings at rest in depressed patients. Results set the stage for examining the value of these measures for predicting clinical response to antidepressants in the entire EMBARC sample and evaluating whether an upregulated brain arousal is particularly characteristic for responders to antidepressants.

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.