EEG frontal asymmetry in the depressed and remitted elderly: is it related to the trait or to the state of depression?

Frontal alpha asymmetry is associated with chronic stress and depression, but not with somatoform disorders

Cardinal characteristics of somatoform disorders (SFDs) are worry of illness, and impaired affective processing. We used relative frontal alpha asymmetry (FAA), a method to measure functional lateralization of affective processing, to investigate psychobiological correlates of SFDs. With alpha activity being inversely related to cortical network activity, relative FAA refers to alpha activity on the right frontal lobe minus alpha activity on the left frontal lobe. Less relative left frontal activity, reflected by negative FAA scores, is associated with lower positive and greater negative affectivity, such as observed in depression. Due to its negative affective component (illness anxiety), we expected to find less relative left frontal activity pattern in SFDs, and positive associations with self-reported chronic stress and depression symptoms. We recorded resting-state EEG activity with 64 electrodes, placed in a 10-10 system in 26 patients with a primary SFD, 23 patients with a major depressive disorder and 25 healthy control participants. The groups did not differ in FAA. Nevertheless, across all participants, less relative left frontal activity was associated with chronic stress and depression symptoms. We concluded that FAA may not serve as an indicator of SFDs. As the relationship of FAA and depressive symptoms was fully mediated by chronic stress, future studies have to clarify whether the association between FAA and chronic stress may represent a shared underlying factor for the manifestation of mental health complaints, such as depression.

Network analysis of frontal lobe alpha asymmetry confirms the neurophysiological basis of four subtypes of depressive behavior

Introduction

Although depression is widespread carries a major disease burden, current treatments remain non-universally effective, arguably due to the heterogeneity of depression, and leading to the consideration of depressive "subtypes" or "depressive behavior subtypes." One such model of depressive behavior (DB) subtypes was investigated for its associations with frontal lobe asymmetry (FLA), using a different data analytic procedure than in previous research in this field.

Methods

100 community volunteers (54 males, 46 females) aged between 18 yr. and 75 years (M = 32.53 yr., SD = 14.13 yr) completed the Zung Self-rating Depression Scale (SDS) and underwent 15 min of eyes closed EEG resting data collection across 10 frontal lobe sites. DB subtypes were defined on the basis of previous research using the SDS, and alpha-wave (8-13 Hz) data produced an index of FLA. Data were examined via network analysis.

Results

Several network analyses were conducted, producing two models of the association between DB subtypes and FLA, confirming unique neurophysiological profiles for each of the four DB subtypes.

Discussion

As well as providing a firm basis for using these DB subtypes in clinical settings, these findings provide a reasonable explanation for the inconsistency in previous FLA-depression research.

EEG frontal lobe asymmetry as a function of sex, depression severity, and depression subtype

To investigate possible contributors to the inconsistent association between frontal lobe asymmetry (FLA) and depression, EEG data were collected across five frontal sites, and examined for their associations with four subtypes of depression (Depressed mood, Anhedonia, Cognitive depression, Somatic depression). One hundred community volunteers (54 males, 46 females) aged at least 18 yr completed standardized scales for depression and anxiety, and gave EEG data under Eyes Open and Eyes Closed conditions. Results indicated that, although there was no significant correlation between the differences in EEG power across each of the five pairs of frontal sites and total depression scores, there were several meaningful correlations (accounting for at least 10% of the variance) between specific EEG site differences data and each of the four depression subtypes. There were also different patterns of association between FLA and the depression subtypes according to sex, and total depression severity. These findings help to explain the apparent inconsistency in previous FLA-depression results, and argue for a more nuanced approach to this hypothesis.

Resting-state electroencephalography of neural oscillation and functional connectivity patterns in late-life depression

BACKGROUND

The clinical manifestations of late-life depression (LLD) are highly heterogeneous. Currently, abnormal characteristics of resting-state electroencephalography (EEG) power and functional connectivity are considered trait markers of depressive symptoms in major depression. However, the relationship between EEG spectral features and functional connectivity in LLD remains unknown.

METHODS

Forty-one patients with LLD and 44 participants without depression underwent an eyes-closed resting-state EEG. EEG power spectra, alpha asymmetry, and functional connectivity were calculated and analyzed.

RESULTS

Although alpha frontal asymmetry and cortical functional connectivity between the two groups showed no significant differences, the LLD group exhibited abnormal neural oscillation patterns of higher beta frequency activity in the parietal, central, and occipital lobes while alpha activity was increased in the parietal central electrodes.

LIMITATIONS

The number of EEG electrodes used in this study was low, and the sample size was limited.

CONCLUSIONS

Increased alpha and beta frequency band powers were observed in patients with LLD. These abnormal patterns may be associated with a disturbed balance of cortical excitation, inhibition, and hyperactivity. In the future, a neurofeedback protocol based on the findings of neural oscillation patterns in certain types of LLD should be explored.

Frontal Alpha Asymmetry and Negative Mood: A Cross-Sectional Study in Older and Younger Adults

Frontal alpha asymmetry (FAA) has been associated with emotional processing and affective psychopathology. Negative and withdrawal stimuli and behaviors have been related to high levels of right cortical activity, while positive and approach stimuli and behaviors have been related to increased left cortical activity. Inconsistent results in terms of depressive and anxious symptoms and their relationship to FAA have been previously observed, especially at older ages. Additionally, no studies to date have evaluated whether loneliness, a negative feeling, is related to FAA. Therefore, this study aimed (i) to compare FAA between younger and older adults and (ii) to investigate the possible relationships between loneliness, depressive and anxious symptomatology with FAA in young and older adults. Resting electroencephalogram recordings of 39 older (Mage = 70.51, SD = 7.12) and 57 younger adults (Mage = 22.54, SD = 3.72) were analyzed. Results showed greater left than right cortical activity for both groups and higher FAA for older than younger adults. FAA was not predicted by loneliness, depressive or anxious symptomatology as shown by regression analyses. Findings bring clarity about FAA patterns at different ages and open the discussion about the relationship between negative emotional processing and frontal cortical imbalances, especially at older ages.

Left and right temporal-parietal junctions (TPJs) as "match/mismatch" hedonic machines: A unifying account of TPJ function

Experimental and theoretical studies have tried to gain insights into the involvement of the Temporal Parietal Junction (TPJ) in a broad range of cognitive functions like memory, attention, language, self-agency and theory of mind. Recent investigations have demonstrated the partition of the TPJ in discrete subsectors. Nonetheless, whether these subsectors play different roles or implement an overarching function remains debated. Here, based on a review of available evidence, we propose that the left TPJ codes both matches and mismatches between expected and actual sensory, motor, or cognitive events while the right TPJ codes mismatches. These operations help keeping track of statistical contingencies in personal, environmental, and conceptual space. We show that this hypothesis can account for the participation of the TPJ in disparate cognitive functions, including "humour", and explain: a) the higher incidence of spatial neglect in right brain damage; b) the different emotional reactions that follow left and right brain damage; c) the hemispheric lateralisation of optimistic bias mechanisms; d) the lateralisation of mechanisms that regulate routine and novelty behaviours. We propose that match and mismatch operations are aimed at approximating "free energy", in terms of the free energy principle of decision-making. By approximating "free energy", the match/mismatch TPJ system supports both information seeking to update one's own beliefs and the pleasure of being right in one's own' current choices. This renewed view of the TPJ has relevant clinical implications because the misfunctioning of TPJ-related "match" and "mismatch" circuits in unilateral brain damage can produce low-dimensional deficits of active-inference and predictive coding that can be associated with different neuropsychological disorders.

Electroencephalography Findings in Older Adults Undergoing Geriatric Treatment: A Surrogate for the Outcome?

Background: Comprehensive geriatric care (CGC) is a multidisciplinary approach developed to meet the needs of older patients. Electroencephalography (EEG) provides valuable information for monitoring the cerebral function. As a surrogate, EEG findings may help to estimate the course of diseases as well as the treatment outcomes. Objectives: Therefore, the aim of the present study is to investigate EEG findings in older patients receiving CGC. Methods: Patients with an initial EEG in a geriatric unit between May 2019 and April 2020 and treated using the CGC approach were analyzed. EEG abnormalities were defined as generalized (diffuse) background slowing and/or intermittent/persistent focal slowing and/or epileptiform discharges. Assessment results for the Barthel index (BI), Tinetti Balance and Gait test (TBGT), and Timed Up and Go test (TUG) were analyzed in relation to the presence of EEG abnormalities. Results: The study included 398 patients (mean age: 83.0 ± 6.57 years, 69.3% were female). Abnormal EEG patterns were found in 94 (23.6%) patients. Patients with EEG abnormalities had a mean age of 83.4 years versus a mean of 82.8 years in those without (p = 0.451). Based on all calculated scores, the majority of the patients improved after CGC, with a tendency to higher-grade improvements in those without EEG abnormalities (BI: 86.2% vs. 75.5%, p = 0.024; TUG: 53.3% vs. 31.9%, p < 0.001); for TBGT, only a gradual difference was detected (TBGT: 79.9% vs. 71.3%, p = 0.088). The presence of EEG abnormalities was associated with the parameters dementia (36.2% vs. 22.4%, p = 0.010), known epilepsy/seizure (19.1% vs. 5.9%, p < 0.001), structural brain lesion (47.9% vs. 19.7%, p < 0.001), and delirium (9.6% vs. 3.6%, p = 0.030) during hospitalization. Conclusions: We found EEG abnormalities in almost a quarter of the patients treated in the geriatric unit. In older patients, the presence of EEG abnormalities is associated with lower improvements after CGC.

The relationship between emotional regulation and hemispheric lateralization in depression: a systematic review and a meta-analysis

From a neurobiological perspective, diverse studies have associated emotional regulation with cognitive deficits. Structural and/or metabolic changes in the frontal cortex are often inferred from dysfunction in cognitive-emotional processing. In addition, electroencephalographic findings support the idea that alpha band oscillations are responses to these same processes. Thus, the objective of this meta-analytical literature review is to verify whether the possible hemispheric lateralization attributed to frontal alpha asymmetry (FAA) correlates with emotional regulation and the cognitive deficits underlying depression. The data included in our meta-analysis are from articles published from 2009 to July 2020, which utilized DSM or ICD criteria to diagnose depression or anxiety disorders and included a control group. For statistical analysis, the measurements obtained through the 10-20 electroencephalography system were used. The frontal alpha asymmetry index was calculated from the difference between the logarithm of the absolute spectral values in the alpha rhythm observed from the F4 and F3 electrodes that were fixed to the scalp of the frontal region of the right and left hemispheres (ln µV² RH-ln µV² LH) = (F4-F3). Eighteen articles were included in the systematic review. Of these, 9 were homogeneous enough for statistical analyses (total N: 1061; N_Dep: 326; N_cont: 735). Nine others could not be statistically analyzed due to the absence of FAA measurements from the F4 and F3 electrodes. A random effects meta-analysis revealed low heterogeneity (Qt = 11,00, df = 8, p = 0.20, I² = 27%) and an average effect size of the studies equal to -0.03 (CI = [-0.07 to 0.01]). The results, although not significant, suggested a slight tendency toward left lateralization in the depression group. Although the effects shown in these data did not confirm hemispherical lateralization in depressed patients, it was found that emotional regulation and cognitive processes share similar neural circuits. Therefore, future research on this complex relationship is encouraged, especially studies that are focused on the search for quantitative biological markers in depression.

No relationship between frontal alpha asymmetry and depressive disorders in a multiverse analysis of five studies

For decades, the frontal alpha asymmetry (FAA) - a disproportion in EEG alpha oscillations power between right and left frontal channels - has been one of the most popular measures of depressive disorders (DD) in electrophysiology studies. Patients with DD often manifest a left-sided FAA: relatively higher alpha power in the left versus right frontal lobe. Recently, however, multiple studies failed to confirm this effect, questioning its reproducibility. Our purpose is to thoroughly test the validity of FAA in depression by conducting a multiverse analysis - running many related analyses and testing the sensitivity of the effect to changes in the analytical approach - on data from five independent studies. Only 13 of the 270 analyses revealed significant results. We conclude the paper by discussing theoretical assumptions underlying the FAA and suggest a list of guidelines for improving and expanding the EEG data analysis in future FAA studies.

Classification of cognitive reserve in healthy older adults based on brain activity using support vector machine

OBJECTIVE

Cognitive reserve (CR) refers to the capacity of the brain to actively cope with damage via the implementation of remedial cognitive processes. Traditional CR measurements focus on static proxies, which may not be able to appropriately estimate dynamic changes in CR. This study therefore investigated the cognitive performance and characteristics of brain activity of low- and high-CR healthy adults during resting and n-back task states and categorized subjects according to magnetoencephalographic (MEG) information using a support vector machine (SVM) classifier.

APPROACH

Forty-one volunteers were divided into groups with low and high CR indexes based on their education, occupational attainment, leisure and social activities.

MAIN RESULTS

The results can be summarized as follows. First, subjects with a higher CR had higher accuracies and faster reaction times in the task. Second, subjects with a lower CR had a higher M300 intensity but a constant M300 latency. Third, subjects with a higher CR had a higher beta intensity in the parietal and occipital regions during the task, whereas subjects with a higher CR had a higher gamma intensity in the right temporal region in the resting state. Finally, subjects with a higher CR had negative gamma asymmetry between the right and left occipital regions, whereas subjects with a lower CR had positive values in the resting state.

SIGNIFICANCE

These MEG results were subsequently used to classify subjects into high-/low-CR subjects using an SVM classifier, and a mean accuracy of 88.89% was obtained. This objective and nonstatic method for determining CR level warrants further research for a wider variety of future clinical applications.

Resting-state EEG beta band power predicts quality of life outcomes in patients with depressive disorders: A longitudinal investigation

BACKGROUND

Quality of life is severely impaired in patients with depressive disorders. Previous studies have focused on biomarkers predicting depressive symptomatology; however, studies investigating biomarkers predicting quality of life outcomes are limited. Improving quality of life is important because it is related not only to mental health but also to physical health. We need to develop a biomarker related to quality of life as a therapeutic target for patients with depressive disorders. Resting-state electroencephalography (EEG) is easy to record in clinical settings. The index of bandwidth spectral power predicts treatment response in depressive disorders and thus may be a candidate biomarker. However, no longitudinal studies have investigated whether EEG-recorded power could predict quality of life outcomes in patients with depressive disorders.

METHODS

The resting-state EEG-recorded bandwidth spectral power at baseline and the World Health Organization Quality of Life (QOL)-26 scores at 3-year follow-up were measured in 44 patients with depressive disorders.

RESULTS

The high beta band power (20-30 Hz) at baseline significantly predicted QOL at the 3-year follow-up after considering depressive symptoms and medication effects in a longitudinal investigation in patients with depressive disorders (β = 0.38, p = 0.01).

LIMITATIONS

We did not have healthy subjects as a comparison group in this study.

CONCLUSIONS

Our findings suggest that resting-state beta activity has the potential to be a useful biomarker for predicting future quality of life outcomes in patients with depressive disorders.

Brainwaves Oscillations as a Potential Biomarker for Major Depression Disorder Risk

Major depressive disorder (MDD) is a multidimensional disorder that is characterized by the presence of alterations in mood, cognitive capacity, sensorimotor, and homeostatic functions. Given that about half of the patients diagnosed with MDD do not respond to the various current treatments, new techniques are being sought to predict not only the course of the disease but also the characteristics that differentiate responders from non-responders. Using the electroencephalogram, a noninvasive and inexpensive tool, most studies have proposed that patients with MDD have some lateralization in brain electrical activity, with alterations in alpha and theta rhythms being observed, which would be related to dysfunctions in emotional capacity such as the absence or presence of responses to the different existing treatments. These alterations help in the identification of subjects at high risk of suffering from depression, in the differentiation into responders and nonresponders to various therapies (pharmacological, electroconvulsive therapy, and so on), as well as to establish in which period of the disease the treatment will be more effective. Although the data are still inconclusive and more research is needed, these alpha and theta neurophysiological markers could support future clinical practice when it comes to establishing an early diagnosis and treating state disorders more successfully and accurately of mood disorders.

Stability of frontal alpha asymmetry in depressed patients during antidepressant treatment

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Frontal alpha asymmetry (FAA) is moderately stable over time.

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Antidepressant response prediction with FAA remains consistent, even after 8 weeks of treatment.

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FAA is a differential predictor of antidepressant response robust to state and drug effects.

Introduction

Frontal alpha asymmetry (FAA) is a proposed prognostic biomarker in major depressive disorder (MDD), conventionally acquired with electroencephalography (EEG). Although small studies attributed trait-like properties to FAA, a larger sample is needed to reliably asses this characteristic. Furthermore, to use FAA to predict treatment response, determining its stability, including the potential dependency on depressive state or medication, is essential.

Methods

In the international Study to Predict Optimized Treatment in Depression (iSPOT-D), a multi-center, randomized, prospective open-label trial, 1008 MDD participants were randomized to treatment with escitalopram, sertraline or venlafaxine-extended release. Treatment response was established eight weeks after treatment initiation and resting state EEG was measured both at baseline and after eight weeks (n = 453).

Results

FAA did not change significantly after eight weeks of treatment (n = 453, p = .234), nor did we find associations with age, sex, depression severity, or change in depression severity. After randomizing females to escitalopram or sertraline, for whom treatment response could be predicted in an earlier study, FAA after eight weeks resulted in equivalent response prediction as baseline FAA (one tailed p = .028).

Conclusion

We demonstrate that FAA is a stable trait, robust to time, state and pharmacological status. This confirms FAA stability. Furthermore, as prediction of treatment response is irrespective of moment of measurement and use of medication, FAA can be used as a state-invariant prognostic biomarker with promise to optimize MDD treatments.

Prediction of rTMS treatment response in major depressive disorder using machine learning techniques and nonlinear features of EEG signal

BACKGROUND

Prediction of therapeutic outcome of repetitive transcranial magnetic stimulation (rTMS) treatment is an important purpose that eliminates financial and psychological consequences of applying inefficient therapy. To achieve this goal we proposed a method based on machine learning to classify responders (R) and non- responders (NR) to rTMS treatment for major depression disorder (MDD) patients.

METHODS

19 electrodes resting state EEG was recorded from 46 MDD patients before treatment. Then patients underwent 7 weeks of rTMS, and 23 of them responded to treatment. Features extracted from EEG include Lempel-Ziv complexity (LZC), Katz fractal dimension (KFD), correlation dimension (CD), the power spectral density, features based on bispectrum, frontal and prefrontal cordance and combination of them. The most relevant features were selected by the minimal-redundancy-maximal-relevance (mRMR) feature selection algorithm. For classifying two groups of R and NR, k-nearest neighbors (KNN) were applied. The performance of the proposed method was evaluated by leave-1-out cross-validation. For further study, the capability of features in differentiating R and NR was investigated by a statistical test.

RESULTS

Effective EEG features for prediction of rTMS treatment response were found. EEG beta power, the sum of bispectrum diagonal elements in delta and beta bands and CD were the most discriminative features. Power of beta classified R and NR with the high performance of 91.3% accuracy, 91.3% specificity, and 91.3% sensitivity.

LIMITATIONS

Lack of large sample size restricted our method for using in clinical applications.

CONCLUSION

This considerable high accuracy indicates that our proposed method with power and some of the nonlinear and bispectral features can lead to promising results in predicting treatment outcome of rTMS for MDD patients only by one session pretreatment EEG recording.

Frontal Alpha Asymmetry Correlates with Suicidal Behavior in Major Depressive Disorder

Objective

Based on the constant associations made between major depressive disorder (MDD) and alpha asymmetry, and MDD and suicide, this study aimed to examine the relationship between frontal alpha asymmetry and suicide in MDD patients.

Methods

Sixty-six MDD patients, of whom fifteen were male and fifty-one were female, were recruited. Independent groups were created based on the median score of frontal alpha asymmetry: the left dominant (LD) group and the right dominant (RD) group. The alpha band (8‒12 Hz) and its sub-bands (i.e., low alpha band: 8‒10 Hz; high alpha band: 10‒12 Hz) were of interest. Source level alpha asymmetry was calculated as well.

Results

Suicidal behavior was positively correlated with the asymmetry indices of the low alpha band and the alpha band in the LD group and that of the high alpha band in the RD group. Source level analysis revealed positive correlations between suicidal behavior and the asymmetry index of the low alpha band in the LD group.

Conclusion

Frontal alpha asymmetry, especially that of the low alpha band, might reflect the cognitive deficits associated with suicidal behaviors in MDD patients.

An Electrophysiological Biomarker That May Predict Treatment Response to ECT

OBJECTIVE

Electroconvulsive therapy (ECT) is the most effective treatment for major depression but also carries risk of cognitive side effects. The ability to predict whether treatment will be effective before initiation of treatment could significantly improve quality of care, reduce suffering, and diminish costs. We sought to carry out a comprehensive and definitive study of the relationship between the background electroencephalography (EEG) and therapeutic response to ECT.

METHODS

Twenty-one channel resting EEG was collected pre-ECT and 2 to 3 days after ECT course from 2 separate data sets, one to develop an EEG model of therapeutic response (n = 30) and a second to test this model (n = 40). A 3-way principal components analysis was applied and coherence and spectral amplitude across 6 frequency bands were examined. The primary outcome measure was the Montgomery-Asberg Rating Scale (MADRS).

RESULTS

Four patterns of amplitude and coherence along with baseline MADRS score accounted for 85% of the variance in posttreatment course MADRS score in study 1 (R = 0.85, F = 11.7, P < 0.0002) and 53% of the variance in MADRS score in study 2 (R = 0.53, F = 5.5, P < 0.003). Greater pre-ECT course anterior delta coherence accounted for the majority of variance in therapeutic response (study 1: R = 0.44, P = 0.01; study 2: R = 0.16, P = 0.008).

CONCLUSIONS

These results suggest a putative electrophysiological biomarker that can predict therapeutic response before a course of ECT. Greater baseline anterior delta coherence is significantly associated with a better subsequent therapeutic response and could be indicative of intact circuitry allowing for improved seizure propagation.

The moderating effect of heart rate variability on the relationship between alpha asymmetry and depressive symptoms

Electroencephalographic (EEG) research has suggested relatively reduced brain activity in the left frontal and right posterior region trait-markers of depression. However, inconsistent results have been reported. Based on previous studies reporting the heart rate variability (HRV) as an index of emotional regulation, this study makes a novel investigation of the role of heart rate variability (HRV) as a moderator in the relationship between frontal and parietal alpha asymmetry and depression. Resting EEG (eyes open) was recorded in 38 patients with MDD and 34 healthy subjects. Frontal and parietal alpha asymmetries were calculated at total (8–12 Hz), high (10–12 Hz), and low (8–10 Hz) alpha frequency bands. Three vagally mediated HRV (vmHRV) components (LF, HF, and the LF/HF ratio) were calculated in the frequency domain. Relatively greater right parietal alpha activity significantly predicted the severity of depression only when HF was low (or the LF/HF ratio was high) at low alpha frequency band. The interaction effect of parietal alpha asymmetry and vmHRV remained significant after including anxiety score as a covariate. No moderation effect of vmHRV was found for frontal sites and other frequency bands, as well as healthy subjects. These findings suggest that vmHRV moderates the association between parietal alpha asymmetry at low frequency band and depression for MDD patients. We suggest that the interaction between parietal alpha asymmetry and vmHRV may be a biomarker of MDD.

Electroencephalogram alpha asymmetry in patients with depressive disorders: current perspectives

PURPOSE

Electroencephalogram (EEG) alpha asymmetry (AA) in depressive disorders has been of interest over the last few decades, but it continues to remain unclear whether EEG AA can discriminate between healthy and depressive individuals.

MATERIALS AND METHODS

A systematic literature search for papers addressing EEG AA using the keywords alpha asymmetry, depression, and EEG was performed in PubMed. All studies were checked for sample size, gender, handedness, reference, recording protocol, EEG band range, impedance, type of analysis, drugs, and comorbidity.

RESULTS

A total of 61 articles were found, of which 44 met our inclusion criteria. They have been consecutively analyzed in respect of methodology and results. Approximately 25% (11/44) of the studies did not mention or ignored handedness, 41% (18/44) of the studies used data with only self-reported handedness, and only 34.1% (15/44) of all studies tested handedness. Only 35% (15/44) of the studies reported pharmacological treatment, and only 35% (15/44) of the studies controlled for medication. A total of 52% (23/44) of the studies reported comorbidity, and only 30% (13/44) of the studies controlled for comorbidity. Only 29.6% (13/44) of the studies reported education. In all, 30.5% (13/44) of the studies analyzed group differences and correlations, while 15.9 (7/44) of the studies used only correlational analyses. A total of 52.3% (23/44) of the studies analyzed only group differences. Alpha range was fixed (8-13 Hz) in 59.1% (26/44) of all studies. Reference to common average was used in seven of 44 studies (15.9%). In all, nine of 44 (20.5%) studies used the midline central position as reference, 22 of 44 (50%) studies used the ear or the mastoid as reference, and four of 44 (9.1%) studies used the nose as reference.

CONCLUSION

Discriminative power of EEG AA for depressed and healthy controls remains unclear. A systematic analysis of 44 studies revealed that differences in methodology and disregarding proper sampling are problematic. Ignoring handedness, gender, age, medication, and comorbidity could explain inconsistent findings. Hence, we formulated a guideline for requirements for future studies on EEG AA in order to allow for better comparisons.

Frontal alpha asymmetry as a diagnostic marker in depression: Fact or fiction? A meta-analysis

BACKGROUND

Frontal alpha asymmetry (FAA) has frequently been reported as potential discriminator between depressed and healthy individuals, although contradicting results have been published. The aim of the current study was to provide an up to date meta-analysis on the diagnostic value of FAA in major depressive disorder (MDD) and to further investigate discrepancies in a large cross-sectional dataset.

METHODS

SCOPUS database was searched through February 2017. Studies were included if the article reported on both MDD and controls, provided an FAA measure involving EEG electrodes F3/F4, and provided data regarding potential covariates. Hedges' d was calculated from FAA means and standard deviations (SDs). Potential covariates, such as age and gender, were explored. Post hoc analysis was performed to elucidate interindividual differences that could explain interstudy discrepancies.

RESULTS

16 studies were included (MDD: n = 1883, controls: n = 2161). After resolving significant heterogeneity by excluding studies, a non-significant Grand Mean effect size (ES) was obtained (d = - 0.007;CI = [- 0.090]-[0.075]). Crosssectional analyses showed a significant three-way interaction for Gender × Age × Depression severity in the depressed group, which was prospectively replicated in an independent sample.

CONCLUSIONS

The main result was a non-significant, negligible ES, demonstrating limited diagnostic value of FAA in MDD. The high degree of heterogeneity across studies indicates covariate influence, as was confirmed by crosssectional analyses, suggesting future studies should address this Gender × Age × Depression severity interaction. Upcoming studies should focus more on prognostic and research domain usages of FAA rather than a pure diagnostic tool.

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant’s treatment outcome may help during antidepressant’s selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant’s treatment outcome for the MDD patients.

The effects of gender and depression severity on the association between alpha asymmetry and depression across four brain regions

Data describing the association between EEG asymmetry and depression status have been equivocal. Effects from brain regions involved, depression severity, and the generalisability of findings across genders, have been inconsistently examined and/or verified. This study investigated these issues within a community sample to potentially expand the asymmetry hypothesis to non-severe depression participants. The singular effects of brain region and electrode site, gender, and depression severity, plus the interaction between gender and depression severity across brain regions were investigated in a study of alpha asymmetry among 46 males and 54 females (M age=32.5 yr, SD=14.13 yr) using the Self-rating Depression Scale (Zung, 1973). There was no significant difference across genders or age for depression severity. Dichotomous classification of depressed state produced similar but slightly different results from analysis of the whole range of depression status, although the frontal region was the only area where depression was consistently significantly associated with EEG asymmetry, and then only for females. However, the direction of those differences for females was opposite of that predicted by the EEG asymmetry-depression hypothesis. Several methodological issues that may have contributed to these findings are discussed, with suggestions made for future research that focusses upon individual depression symptom profiles rather than dichotomous or total depression scores in order to assist in developing a clinically-relevant model of EEG asymmetry in depressed persons.

EEG marker of inhibitory brain activity correlates with resting-state cerebral blood flow in the reward system in major depression

Frontal alpha band asymmetry (FAA) is a marker of altered reward processing in major depressive disorder (MDD), associated with reduced approach behavior and withdrawal. However, its association with brain metabolism remains unclear. The aim of this study was to investigate FAA and its correlation with resting-state cerebral blood flow (rCBF). We hypothesized an association of FAA with regional rCBF in brain regions relevant to reward processing and motivated behavior, such as the striatum. We enrolled 20 patients and 19 healthy subjects. FAA scores and rCBF were quantified with the use of EEG and arterial spin labeling. Correlations of the two were evaluated, as well as the association with FAA and psychometric assessments of motivated behavior and anhedonia. Patients showed a left-lateralized pattern of frontal alpha activity and a correlation of FAA lateralization with subscores of Hamilton Depression Rating Scale linked to motivated behavior. An association of rCBF and FAA scores was found in clusters in the dorsolateral prefrontal cortex bilaterally (patients), in the left medial frontal gyrus, in the right caudate head and in the right inferior parietal lobule (whole group). No correlations were found in healthy controls. Higher inhibitory right-lateralized alpha power was associated with lower rCBF values in prefrontal and striatal regions, predominantly in the right hemisphere, which are involved in the processing of motivated behavior and reward. Inhibitory brain activity in the reward system may contribute to some of the motivational problems observed in MDD.

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder

Personalized medicine in psychiatry is in need of biomarkers that resemble central nervous system function at the level of neuronal activity. Electroencephalography (EEG) during sleep or resting-state conditions and event-related potentials (ERPs) have not only been used to discriminate patients from healthy subjects, but also for the prediction of treatment outcome in various psychiatric diseases, yielding information about tailored therapy approaches for an individual. This review focuses on baseline EEG markers for two psychiatric conditions, namely major depressive disorder and attention deficit hyperactivity disorder. It covers potential biomarkers from EEG sleep research and vigilance regulation, paroxysmal EEG patterns and epileptiform discharges, quantitative EEG features within the EEG main frequency bands, connectivity markers and ERP components that might help to identify favourable treatment outcome. Further, the various markers are discussed in the context of their potential clinical value and as research domain criteria, before giving an outline for future studies that are needed to pave the way to an electrophysiological biomarker-based personalized medicine.

Electroencephalogram alpha asymmetry in geriatric depression : Valid or vanished?

BACKGROUND

A correlation between asymmetry in electroencephalographs (EEG) and depression has been demonstrated in many studies. To the best of our knowledge there are no studies including oldest old geriatric patients.

OBJECTIVE

The objective of this study was to evaluate whether frontal and parietal alpha asymmetry can be used to differentiate between depressed and control patients in a cohort sample with a mean age of 80 years.

MATERIAL AND METHODS

Differences in the EEG were investigated in 39 right-handed female geriatric patients (mean age 80 years) with respect to frontal alpha asymmetry (FAA) and parietal alpha asymmetry (PAA) in depression (n = 14), depression combined with anxiety (n = 11) and normal controls (n = 14) as assessed with the hospital anxiety and depression scale (HADS). Band power was calculated for alpha 1 (6.9-8.9 Hz), alpha 2 (8.9-10.9 Hz) and alpha 3 bands (10.9-12.9 Hz). Furthermore, correlations between frontal and parietal alpha asymmetry and the geriatric depression scale (GDS), the HADS and the mini mental state examination (MMSE) were calculated.

RESULTS

A differentiation between the three groups was not possible with FAA and PAA. Significant correlations were found between PAA alpha 3 band and anxiety and depression.

CONCLUSION

The alpha asymmetry in EEG seemed to disappear with age. Correlations between PAA and anxiety and depression were found. The results are in line with the right (hemisphere) hemi-aging hypothesis.

Neural complexity in patients with poststroke depression: A resting EEG study

BACKGROUND

Poststroke depression (PSD) is one of the most common emotional disorders affecting post-stroke patients. However, the neurophysiological mechanism remains elusive. This study was aimed to study the relationship between complexity of neural electrical activity and PSD.

METHODS

Resting state eye-closed electroencephalogram (EEG) signals of 16 electrodes were recorded in 21 ischemic poststroke depression (PSD) patients, 22 ischemic poststroke non-depression (PSND) patients and 15 healthy controls (CONT). Lempel-Ziv Complexity (LZC) was used to evaluate changes in EEG complexity in PSD patients. Statistical analysis was performed to explore difference among different groups and electrodes. Correlation between the severity of depression (HDRS) and EEG complexity was determined with pearson correlation coefficients. Receiver operating characteristic (ROC) and binary logistic regression analysis were conducted to estimate the discriminating ability of LZC for PSD in specificity, sensitivity and accuracy.

RESULTS

PSD patients showed lower neural complexity compared with PSND and CONT subjects in the whole brain regions. There was no significant difference among different brain regions, and no interactions between group and electrodes. None of the LZC significantly correlated with overall depression severity or differentiated symptom severity of 7 items in PSD patients, but in stroke patients, significant correlation was found between HDRS and LZC in the whole brain regions, especially in frontal and temporal. LZC parameters used for PSD recognition possessed more than 85% in specificity, sensitivity and accuracy, suggesting the feasibility of LZC to serve as screening indicators for PSD. Increased slow wave rhythms were found in PSD patients and clearly correlation was confirmed between neuronal complexity and spectral power of the four EEG rhythms.

LIMITATIONS

Lesion location of stroke patients in the study distributed in different brain regions, and most of the PSD patients were mild or moderate in depressive severity.

CONCLUSIONS

Compared with conventional spectral analysis, complexity of neural activity using LZC was more sensitive and stationary in the measurement of abnormal brain activity in PSD patients and may offer a potential approach to facilitate clinical screening of this disease.

Psychomotor retardation is linked to frontal alpha asymmetry in major depression

BACKGROUND

Psychomotor disturbances are a main clinical feature of major depressive disorder (MDD) but little is known about their EEG signature. One of the most replicated EEG findings in MDD is resting frontal asymmetry in the alpha band (FAA), which is thought to be a correlate of withdrawal behavior and reduced approach motivation. The purpose of this study was to assess psychomotor alterations, alpha band power, FAA and investigate the association between them.

METHODS

20 MDD patients and 19 healthy subjects were enrolled. Alpha power and FAA scores were calculated from a resting state EEG. Wrist actigraphy was recorded from the non-dominant arm for 24 h and activity level scores (AL) were extrapolated from the wakeful periods.

RESULTS

MDD patients had a left-lateralized frontal alpha activity and lower AL scores when compared to healthy subjects. A significant correlation was found between mean FAA and AL scores. A negative covariance between power in the lower alpha range and AL scores over the motor cortex bilaterally was detected.

LIMITATIONS

Relatively small sample size. Patients were pharmacologically treated with antidepressants.

CONCLUSIONS

This study replicates the finding of left-lateralized FAA and lower AL scores in MDD patients, and establishes the first evidence of significant correlations between alpha power, FAA scores and measures of motor activity, which may be interpreted as an expression of impaired motivational drive in MDD.

Multimodal approaches to define network oscillations in depression

The renaissance in the use of encephalography-based research methods to probe the pathophysiology of neuropsychiatric disorders is well afoot and continues to advance. Building on the platform of neuroimaging evidence on brain circuit models, magnetoencephalography, scalp electroencephalography, and even invasive electroencephalography are now being used to characterize brain network dysfunctions that underlie major depressive disorder using brain oscillation measurements and associated treatment responses. Such multiple encephalography modalities provide avenues to study pathologic network dynamics with high temporal resolution and over long time courses, opportunities to complement neuroimaging methods and findings, and new approaches to identify quantitative biomarkers that indicate critical targets for brain therapy. Such goals have been facilitated by the ongoing testing of novel invasive neuromodulation therapies, notably, deep brain stimulation, where clinically relevant treatment effects can be monitored at multiple brain sites in a time-locked causal manner. We review key brain rhythms identified in major depressive disorder as foundation for development of putative biomarkers for objectively evaluating neuromodulation success and for guiding deep brain stimulation or other target-based neuromodulation strategies for treatment-resistant depression patients.

Multi-dimensional modulations of α and γ cortical dynamics following mindfulness-based cognitive therapy in Major Depressive Disorder

To illuminate candidate neural working mechanisms of Mindfulness-Based Cognitive Therapy (MBCT) in the treatment of recurrent depressive disorder, parallel to the potential interplays between modulations in electro-cortical dynamics and depressive symptom severity and self-compassionate experience. Linear and nonlinear α and γ EEG oscillatory dynamics were examined concomitant to an affective Go/NoGo paradigm, pre-to-post MBCT or natural wait-list, in 51 recurrent depressive patients. Specific EEG variables investigated were; (1) induced event-related (de-) synchronisation (ERD/ERS), (2) evoked power, and (3) inter-/intra-hemispheric coherence. Secondary clinical measures included depressive severity and experiences of self-compassion. MBCT significantly downregulated α and γ power, reflecting increased cortical excitability. Enhanced α-desynchronisation/ERD was observed for negative material opposed to attenuated α-ERD towards positively valenced stimuli, suggesting activation of neural networks usually hypoactive in depression, related to positive emotion regulation. MBCT-related increase in left-intra-hemispheric α-coherence of the fronto-parietal circuit aligned with these synchronisation dynamics. Ameliorated depressive severity and increased self-compassionate experience pre-to-post MBCT correlated with α-ERD change. The multi-dimensional neural mechanisms of MBCT pertain to task-specific linear and non-linear neural synchronisation and connectivity network dynamics. We propose MBCT-related modulations in differing cortical oscillatory bands have discrete excitatory (enacting positive emotionality) and inhibitory (disengaging from negative material) effects, where mediation in the α and γ bands relates to the former.

Frontal EEG Asymmetry as a Promising Marker of Depression Vulnerability: Summary and Methodological Considerations

Frontal EEG asymmetry is a promising neurophysiological marker of depression risk. It predicts emotional response and negative affect hours to years later. Yet, inconsistencies in the literature may be due to differing methodological approaches between research groups. Within the past two years, a number of studies have shown this line of research may be strengthened by augmenting resting assessments with emotionally evocative tasks, utilizing optimal recording montages, and taking an integrative neuroscience approach that links frontal asymmetry to other indices of neural function. This review will focus on recent work in frontal asymmetry and depression with a particular focus on promising future directions and methodological considerations that may increase consistency between research groups.

Frontal brain asymmetry in adult attention-deficit/hyperactivity disorder (ADHD): extending the motivational dysfunction hypothesis

OBJECTIVE

Attention-deficit/hyperactivity disorder (ADHD) involves motivational dysfunction, characterized by excessive behavioral approach tendencies. Frontal brain asymmetry in the alpha band (8-13 Hz) in resting-state electroencephalogram (EEG) represents a neural correlate of global motivational tendencies, and abnormal asymmetry, indicating elevated approach motivation, was observed in pediatric and adult patients. To date, the relation between ADHD symptoms, depression and alpha asymmetry, its temporal metric properties and putative gender-specificity remain to be explored.

METHODS

Adult ADHD patients (n=52) participated in two resting-state EEG recordings, two weeks apart. Asymmetry measures were aggregated across recordings to increase trait specificity. Putative region-specific associations between asymmetry, ADHD symptoms and depression, its gender-specificity and test-retest reliability were examined.

RESULTS

ADHD symptoms were associated with approach-related asymmetry (stronger relative right-frontal alpha power). Approach-related asymmetry was pronounced in females, and also associated with depression. The latter association was mediated by ADHD symptoms. Test-retest reliability was sufficient.

CONCLUSIONS

The association between reliably assessable alpha asymmetry and ADHD symptoms supports the motivational dysfunction hypothesis. ADHD symptoms mediating an atypical association between asymmetry and depression may be attributed to depression arising secondary to ADHD. Gender-specific findings require replication.

SIGNIFICANCE

Frontal alpha asymmetry may represent a new reliable marker of ADHD symptoms.

EEG biomarkers in major depressive disorder: discriminative power and prediction of treatment response

Major depressive disorder (MDD) has high population prevalence and is associated with substantial impact on quality of life, not least due to an unsatisfactory time span of sometimes several weeks from initiation of treatment to clinical response. Therefore extensive research focused on the identification of cost-effective and widely available electroencephalogram (EEG)-based biomarkers that not only allow distinguishing between patients and healthy controls but also have predictive value for treatment response for a variety of treatments. In this comprehensive overview on EEG research on MDD, biomarkers that are either assessed at baseline or during the early course of treatment and are helpful in discriminating patients from healthy controls and assist in predicting treatment outcome are reviewed, covering recent decades up to now. Reviewed markers include quantitative EEG (QEEG) measures, connectivity measures, EEG vigilance-based measures, sleep-EEG-related measures and event-related potentials (ERPs). Further, the value and limitations of these different markers are discussed. Finally, the need for integrated models of brain function and the necessity for standardized procedures in EEG biomarker research are highlighted to enhance future research in this field.

Decreased interhemispheric coordination in treatment-resistant depression: a resting-state fMRI study

Background

Previous studies have demonstrated that patients with treatment-resistant depression (TRD) and treatment-sensitive depression (TSD) differed at neural level. However, it remains unclear if these two subtypes of depression differ in the interhemispheric coordination. This study was undertaken for two purposes: (1) to explore the differences in interhemispheric coordination between these two subtypes by using the voxel-mirrored homotopic connectivity (VMHC) method; and (2) to determine if the difference of interhemispheric coordination can be used as a biomarker(s) to differentiate TRD from both TSD and healthy subjects (HS).

Methods

Twenty-three patients with TRD, 22 with TSD, and 19 HS participated in the study. Data of these participants were analyzed with the VMHC and seed-based functional connectivity (FC) approaches.

Results

Compared to the TSD group, the TRD group showed significantly lower VMHC values in the calcarine cortex, fusiform gyrus, hippocampus, superior temporal gyrus, middle cingulum, and precentral gyrus. Lower VMHC values were also observed in the TRD group in the calcarine cortex relative to the HS group. However, the TSD group had no significant change in VMHC value in any brain region compared to the HS group. Receiver operating characteristic curves (ROC) analysis revealed that the VMHC values in the calcarine cortex had discriminatory function distinguishing patients with TRD from patients with TSD as well as those participants in the HS group.

Conclusions

Lower VMHC values of patients with TRD relative to those with TSD and those in the HS group in the calcarine cortex appeared to be a unique feature for patients with TRD and it may be used as an imaging biomarker to separate patients with TRD from those with TSD or HS.

α Power, α asymmetry and anterior cingulate cortex activity in depressed males and females

Left fronto-cortical hypoactivity, thought to reflect reduced activity in approach-related systems, and right parietal hypoactivity, associated with emotional under-arousal, have been noted in major depressive disorder (MDD). Altered theta activity in the anterior cingulate cortex (ACC) has also been associated with the disorder. We assessed resting frontal and parietal alpha asymmetry and power in non-medicated MDD (N = 53; 29 females) and control (N = 43; 23 females) individuals. Theta activity was examined using standardized low-resolution electromagnetic tomography (sLORETA) in the ACC [BA24ab and BA32 comprising the rostral ACC and BA25/subgenual (sg) ACC]. The MDD group, and particularly depressed males, displayed increased overall frontal and parietal alpha power and left midfrontal hypoactivity (alpha(2)-indexed). They also exhibited increased sgACC theta(2) activity. MDD females had increased right parietal activity, suggesting increased emotive arousal. Thus, unmedicated depressed adults were characterized by lower activity in regions implicated in approach/positive affective tendencies as well as diffuse cortical hypoarousal, though sex specific modulations emerged. Altered theta in the sgACC may reflect emotion regulation abnormalities in MDD.

Neural expression of nicotine's antidepressant properties during tryptophan depletion: an EEG study in healthy volunteers at risk for depression

Nicotine amelioration of serotonergically mediated mood dysregulation may contribute to the comorbidity between cigarette smoking and depression, a disorder which is associated with aberrant activation and hemispheric asymmetry in frontal and posterior cortical regions. This randomized, double-blind study in 20 healthy volunteers with a positive family history of depression examined the effects of transdermal nicotine on mood and EEG changes accompanying transient reductions in serotonin induced by acute tryptophan depletion (ATD). Increased self-ratings of depressed mood and elevation in left frontal high alpha power (decreased activation) were evidenced with ATD (vs. balanced mixture) in participants treated with the placebo but not the nicotine treated group. Nicotine alone increased vigor and posterior high alpha bilaterally, and during ATD it prevented the reduction in left frontal high alpha that was evident in the placebo patch group. These findings indicate that in depression prone individuals, nicotine acts to stabilize the mood lowering and associated frontal functional asymmetry elicited by an acute decrease in brain serotonin.

The altered cortical connectivity during spatial search for facial expressions in major depressive disorder

To characterize the altered directed connectivity within a distributed cortical network, as is associated with the impaired attention modulation involved in the manifestation of mood disorder in depression, short-window partial directed coherence (PDC) combining with the event-related brain potentials (ERPs) was applied in this study. ERPs were recorded from 13 normal subjects and 12 depressed patients during visual search for facial expressions. The evoked N2 component of ERPs by responding to all neutral faces (F(1,22)=5.51, P<0.05) and the positive face was reduced in the depressed patients as compared to the normal subjects (F(1,22)=5.71, P<0.05), while the evoked N2 component by detecting the negative face showed no significant between-group effect (F(1,22)=2.10, P=0.16). The reduced N2 amplitude reflected deficits in effortful attentional modulation in depression. Obtained PDC values within the N2 time-window (150-300 ms post stimulus) showed weaker intra-frontal and intra-central directed interactions and enhanced occipital information output when responding to all neutral faces in depression relative to those in the normal group. Few decreased intra-frontal directed interactions were observed when detecting the emotional face in depression. The altered cortical directed connectivity contributed to the impairment occurring in the effortful attention modulation in depression. Our findings supported that the impaired attention modulation processing in depression was associated with the altered cortical connectivity.