EEG mapping in seasonal affective disorder

Decreased Resting-State Alpha Self-Synchronization in Depressive Disorder

Background. Depression disorder has been associated with altered oscillatory brain activity. The common methods to quantify oscillatory activity are Fourier and wavelet transforms. Both methods have difficulties distinguishing synchronized oscillatory activity from nonrhythmic and large-amplitude artifacts. Here we proposed a method called self-synchronization index (SSI) to quantify synchronized oscillatory activities in neural data. The method considers temporal characteristics of neural oscillations, amplitude, and cycles, to estimate the synchronization value for a specific frequency band. Method. The recorded electroencephalography (EEG) data of 45 depressed and 55 healthy individuals were used. The SSI method was applied to each EEG electrode filtered in the alpha frequency band (8-13 Hz). The multiple linear regression model was used to predict depression severity (Beck Depression Inventory-II scores) using alpha SSI values. Results. Patients with severe depression showed a lower alpha SSI than those with moderate depression and healthy controls in all brain regions. Moreover, the alpha SSI values negatively correlated with depression severity in all brain regions. The regression model showed a significant performance of depression severity prediction using alpha SSI. Conclusion. The findings support the SSI measure as a powerful tool for quantifying synchronous oscillatory activity. The data examined in this article support the idea that there is a strong link between the synchronization of alpha oscillatory neural activities and the level of depression. These findings yielded an objective and quantitative depression severity prediction.

Emotional Bias among Individuals at Risk for Seasonal Affective Disorder-An EEG Study during Remission in Summer

Emotional bias in attention and memory is well researched in depression. Patients with depression prioritize processing of negative information over positive input. While there is evidence that emotional bias exists in seasonal affective disorder (SAD) during winter, it is unclear whether such altered cognition exists also during summer. Moreover, it is unclear whether such bias affects attention, memory, or both. In this study, we investigated 110 individuals in summer, 34 of whom reported suffering from low mood during winter, according to the seasonal pattern assessment questionnaire. While the electroencephalogram was recorded, participants learned 60 emotional pictures and subsequently were asked to recognize them in an old/new task. There were no clear group differences in behavioral measures, and no brain response differences in frontal alpha power during learning. During recognition, at 100-300 ms post stimulus individuals with higher seasonality scores exhibited larger alpha power in response to negative as compared to neutral stimuli, while individuals with low seasonality scores exhibited larger alpha power in response to positive as compared to neutral stimuli. While we cannot draw conclusions whether this is an effect of attention or memory, the finding suggests that early cognitive processes are altered already during summer in individuals with increased likelihood to experience SAD during winter. Our data provide evidence for an all-year-round cognitive vulnerability in this population.

Infra-Low-Frequency Neurofeedback Treatment in Dysthymia: A Case Study

Depression is one of the most common mental disorders worldwide. Dysthymia, a long-lasting form of depressive disorder that is also known as persistent depressive disorder (PDD) with pure dysthymic syndrome according to the Diagnostical and Statical Manual of Mental Disorders (DSM-5), is characterised by being difficult to treat. The most prominent therapeutic approaches in treating dysthymia are pharmacotherapy and psychotherapy, but recent studies also demonstrate the success of neurofeedback in treating individuals with depressive disorders. However, infra-low-frequency (ILF) neurofeedback, the main new neurofeedback protocol, lacks empirical evidence, and there is no evidence that it can treat dysthymia. This case report investigates the ILF neurofeedback method in a male patient with dysthymia. After 45 sessions of ILF neurofeedback combined with ILF synchrony, a decrease in symptom severity was found on assessment after treatment, and these results remained consistent at a low level at a 6-month follow-up. Additionally, the patient reported benefits on interpersonal and cognitive levels and in daily life situations. This study should incentivise further investigations into using ILF neurofeedback to treat dysthymia and all variations of depressive disorders.

Yijinjing Qigong intervention shows strong evidence on clinical effectiveness and electroencephalography signal features for early poststroke depression: A randomized, controlled trial

Objective

Although Traditional Chinese Yijinjing Qigong Exercise (YJJQE) as mind-body intervention is popularly used among adults to ameliorate depressive symptoms in China, no randomized controlled trials (RCTs) are available to evaluate the effects of YJJQE in patients with poststroke depression (PSD). This study aims to explore the clinical efficacy and the neurological and psychiatric mechanism in brain network functional connectivity underlying electroencephalography (EEG).

Materials and methods

A total of 60 patients, diagnosed with mild PSD, were randomly (1:1) assigned to YJJQE group (n = 30) and control group of routine segmental rehabilitation training group (n = 30) for a 60-min exercise session once a day for 3 weeks. All outcome measures were collected at baseline and 3-weeks ending intervention. The primary outcome was the 24-item Hamilton Depression Scale (HAMD-24) score, evaluation at more time points for 1 month of follow-up. The secondary outcomes were EEG data in four frequency domains (δ, θ, α, and β), global efficiency (GE), local efficiency (LE), GE/LE curve [areas under the curve (AUC)], Phase Lag Index (PLI), (HAMD-24) Score and EEG correlation analysis.

Results

All patients showed no significant differences in baseline data. After 3 weeks and 1 month of follow-up, the YJJQE group demonstrated significant decreasing changes compared to the control group on the HAMD-24 scores (p < 0.001). Furthermore, the YJJQE group also showed a significant reduction in θ wave, and an increase in both GE and LE. Compared to the control group, the YJJQE Qigong group showed significantly greater functional connectivity in the δ, θ, and β frequency bands in the brain network of the degree of phase synchronization (p < 0.001). HAMD-24 Score and EEG correlation analysis negative correlation in the Qigong group θ wave (p < 0.001).

Conclusion

Our findings demonstrated that YJJQE is estimated to effectively alleviate the depressed mood of patients with PSD by promoting the efficiency in information transmission of network functional connectivity and its integration ability in different brain regions. Therefore, the YJJQE would be useful as a non-pharmacological treatment to prevent PSD.

Clinical trial registration

[http://www.chictr.org.cn/showproj.aspx?proj=55789], identifier [ChiCTR2000035588].

EEG-responses to mood induction interact with seasonality and age

The EEG is suggested as a potential diagnostic and prognostic biomarker for seasonal affective disorder (SAD). As a pre-clinical form of SAD, seasonality is operationalized as seasonal variation in mood, appetite, weight, sleep, energy, and socializing. Importantly, both EEG biomarkers and seasonality interact with age. Inducing sad mood to assess cognitive vulnerability was suggested to improve the predictive value of summer assessments for winter depression. However, no EEG studies have been conducted on induced sad mood in relation to seasonality, and no studies so far have controlled for age. We recorded EEG and calculated bandpower in 114 participants during rest and during induced sad mood in summer. Participants were grouped by age and based on a seasonality score as obtained with the seasonal pattern assessment questionnaire (SPAQ). Participants with high seasonality scores showed significantly larger changes in EEG power from rest to sad mood induction, specifically in the alpha frequency range (p = 0.027), compared to participants with low seasonality scores. Furthermore, seasonality interacted significantly with age (p < 0.001), with lower activity in individuals with high seasonality scores that were older than 50 years but the opposite pattern in individuals up to 50 years. Effects of sad mood induction on brain activity are related to seasonality and can therefore be consider as potential predicting biomarkers for SAD. Future studies should control for age as a confounding factor, and more studies are needed to elaborate on the characteristics of EEG biomarkers in participants above 50 years.

Predictability of Seasonal Mood Fluctuations Based on Self-Report Questionnaires and EEG Biomarkers in a Non-clinical Sample

Induced by decreasing light, people affected by seasonal mood fluctuations may suffer from low energy, have low interest in activities, experience changes in weight, insomnia, difficulties in concentration, depression, and suicidal thoughts. Few studies have been conducted in search for biological predictors of seasonal mood fluctuations in the brain, such as EEG oscillations. A sample of 64 participants was examined with questionnaires and electroencephalography in summer. In winter, a follow-up survey was recorded and participants were grouped into those with at least mild (N = 18) and at least moderate (N = 11) mood decline and those without self-reported depressive symptoms both in summer and in winter (N = 46). A support vector machine was trained to predict mood decline by either EEG biomarkers alone, questionnaire data from baseline alone, or a combination of the two. Leave-one-out-cross validation with lasso regularization was used with logistic regression to fit a model. The accuracy for classification for at least mild/moderate mood decline was 77/82% for questionnaire data, 72/82% for EEG alone, and 81/86% for EEG combined with questionnaire data. Self-report data was more conclusive than EEG biomarkers recorded in summer for prediction of worsening of depressive symptoms in winter but it is advantageous to combine EEG with psychological assessment to boost predictive performance.

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.

Increased functional connectivity within alpha and theta frequency bands in dysphoria: A resting-state EEG study

BACKGROUND

The understanding of neurophysiological correlates underlying the risk of developing depression may have a significant impact on its early and objective identification. Research has identified abnormal resting-state electroencephalography (EEG) power and functional connectivity patterns in major depression. However, the entity of dysfunctional EEG dynamics in dysphoria is yet unknown.

METHODS

32-channel EEG was recorded in 26 female individuals with dysphoria and in 38 age-matched, female healthy controls. EEG power spectra and alpha asymmetry in frontal and posterior channels were calculated in a 4-minute resting condition. An EEG functional connectivity analysis was conducted through phase locking values, particularly mean phase coherence.

RESULTS

While individuals with dysphoria did not differ from controls in EEG spectra and asymmetry, they exhibited dysfunctional brain connectivity. Particularly, in the theta band (4-8 Hz), participants with dysphoria showed increased connectivity between right frontal and central areas and right temporal and left occipital areas. Moreover, in the alpha band (8-12 Hz), dysphoria was associated with increased connectivity between right and left prefrontal cortex and between frontal and central-occipital areas bilaterally.

LIMITATIONS

All participants belonged to the female gender and were relatively young. Mean phase coherence did not allow to compute the causal and directional relation between brain areas.

CONCLUSIONS

An increased EEG functional connectivity in the theta and alpha bands characterizes dysphoria. These patterns may be associated with the excessive self-focus and ruminative thinking that typifies depressive symptoms. EEG connectivity patterns may represent a promising measure to identify individuals with a higher risk of developing depression.

Low β2 Main Peak Frequency in the Electroencephalogram Signs Vulnerability to Depression

Objective: After an intense and repeated stress some rats become vulnerable to depression. This state is characterized by persistent low serum BDNF concentration. Our objective was to determine whether electrophysiological markers can sign vulnerability to depression. Methods: Forty-three Sprague Dawley rats were recorded with supradural electrodes above hippocampus and connected to wireless EEG transmitters. Twenty-nine animals experienced four daily social defeats (SD) followed by 1 month recovery. After SD, 14 rats had persistent low serum BDNF level and were considered as vulnerable (V) while the 15 others were considered as non-vulnerable (NV). EEG signals were analyzed during active waking before SD (Baseline), just after SD (Post-Stress) and 1 month after SD (Recovery). Results: We found that V animals are characterized by higher high θ and α spectral relative powers and lower β2 main peak frequency before SD. These differences are maintained at Post-Stress and Recovery for α spectral relative powers and β2 main peak frequency. Using ROC analysis, we show that low β2 main peak frequency assessed during Baseline is a good predictor of the future state of vulnerability to depression. Conclusion: Given the straightforwardness of EEG recordings, these results open the way to prospective studies in humans aiming to identify population at-risk for depression.

Neurophysiologic Correlates of Post-stroke Mood and Emotional Control

OBJECTIVE

Emotional disturbance is a common complication of stroke significantly affecting functional recovery and quality of life. Identifying relevant neurophysiologic markers associated with post-stroke emotional disturbance may lead to a better understanding of this disabling condition, guiding the diagnosis, development of new interventions and the assessments of treatment response.

METHODS

Thirty-five subjects with chronic stroke were enrolled in this study. The emotion sub-domain of Stroke Impact Scale (SIS-Emotion) was used to assess post-stroke mood and emotional control. The relation between SIS-Emotion and neurophysiologic measures was assessed by using covariance mapping and univariate linear regression. Multivariate analyses were conducted to identify and adjust for potential confounders. Neurophysiologic measures included power asymmetry and coherence assessed by electroencephalography (EEG); and motor threshold, intracortical inhibition (ICI) and intracortical facilitation (ICF) measured by transcranial magnetic stimulation (TMS).

RESULTS

Lower scores on SIS-Emotion was associated with (1) frontal EEG power asymmetry in alpha and beta bands, (2) central EEG power asymmetry in alpha and theta bands, and (3) lower inter-hemispheric coherence over frontal and central areas in alpha band. SIS-Emotion also correlated with higher ICF and MT in the unlesioned hemisphere as measured by TMS.

CONCLUSIONS

To our knowledge, this is the first study using EEG and TMS to index neurophysiologic changes associated with post-stroke mood and emotional control. Our results suggest that inter-hemispheric imbalance measured by EEG power and coherence, as well as an increased ICF in the unlesioned hemisphere measured by TMS might be relevant markers associated with post-stroke mood and emotional control which can guide future studies investigating new diagnostic and treatment modalities in stroke rehabilitation.

Electrophysiological correlates of bilateral and unilateral repetitive transcranial magnetic stimulation in patients with bipolar depression

Repetitive transcranial magnetic stimulation (rTMS) has been demonstrated to have efficacy in the treatment of unipolar depression but limited research has explored the efficacy of rTMS in bipolar depression. Therefore, we conducted a comparative clinical trial evaluating clinical responses to prefrontal bilateral and unilateral rTMS in patients suffering from bipolar depression. We hypothesized that, 1) the response to the treatment would be associated with a decrease in the frequency of beta waves, 2) bilateral stimulation of the cortex would bring about more extensive changes in brain activity than unilateral stimulation, and 3) bilateral stimulation is more effective than unilateral. Thirty patients with bipolar depression were divided into two groups. Bilateral Group (n=15) who received rTMS in the left DLPFC (10Hz) and right DLPFC (1-Hz), and unilateral group (n=15) who received the stimulation only in the right DLPFC (1-Hz) during 20 treatment sessions. The proportion of responders in the bilateral stimulation group was significantly higher than that in the unilateral group [80% versus 47%]. The remission rate was 40% in the bilateral group and 40% in the unilateral group (not significant). In the responders to bilateral rTMS treatment, a significant reduction of alpha1-2, beta 1-3, and gamma frequencies were observed in medial and superior frontal and cingulate gyrus . Responders to the unilateral treatment showed decrease of gamma frequency in postcentral gyrus, precuneus, superior and inferior parietal lobule, Cuneus and angular gyrus. In conclusion, we found that bilateral stimulation was more effective than the unilateral stimulation and evidence that beta frequency activity could possibly be used as a marker for response to rTMS.

The oft-neglected role of parietal EEG asymmetry and risk for major depressive disorder

Relatively less right parietal activity may reflect reduced arousal and signify risk for major depressive disorder (MDD). Inconsistent findings with parietal electroencephalographic (EEG) asymmetry, however, suggest issues such as anxiety comorbidity and sex differences have yet to be resolved. Resting parietal EEG asymmetry was assessed in 306 individuals (31% male) with (n=143) and without (n=163) a DSM-IV diagnosis of lifetime MDD and no comorbid anxiety disorders. Past MDD+ women displayed relatively less right parietal activity than current MDD+ and MDD- women, replicating prior work. Recent caffeine intake, an index of arousal, moderated the relationship between depression and EEG asymmetry for women and men. Findings suggest that sex differences and arousal should be examined in studies of depression and regional brain activity.

EEG topography and tomography (LORETA) in diagnosis and pharmacotherapy of depression

Earlier investigations suggested an involvement of the right hemisphere and the left prefrontal cortex (PFC) in the pathogenesis of depression. This paper presents our own electroencephalographic (EEG) topography and low-resolution brain electromagnetic tomography (LORETA) data obtained in unmedicated depressed patients, and the effects of two representative drugs of non-sedative and sedative antidepressants, i.e., citalopram (CIT) and imipramine (IMI), as compared with placebo in normal subjects. Sixty female menopausal syndrome patients with the diagnosis of a depressive episode without psychotic symptoms as well as 30 healthy controls were investigated. Concerning the effects of antidepressants, normal healthy subjects received single oral doses of 20 mg CIT, 75 mg IMI and placebo p.o. A 3-min vigilance-controlled EEG and a 4-min resting EEG was recorded pre- and post-drug administration and analyzed by means of EEG mapping and LORETA. In the EEG mapping, depressed patients demonstrated a decrease in absolute power in all frequency bands, an augmentation of relative delta/theta and beta and a decrease in alpha activity as well as a slowing of the delta/theta centroid and an acceleration of the alpha and beta centroid, which suggests vigilance decrements. In the alpha asymmetry index, they showed right frontal hyper- and left frontal hypoactivation correlated with the Hamilton Depression Score (HAMD). LORETA predominantly revealed decreased power in the theta and alpha-1 frequency band. Negative correlations between theta power and the HAMD were observed in the ventro-medial PFC, the bilateral rostral anterior cingulate cortex (ACC) and the left insular cortex; between alpha-1 power and the HAMD in the right PFC. In the EEG mapping of antidepressants, 20 mg CIT showed mainly activating, 75 mg IMI partly sedative properties. LORETA revealed that CIT increased alpha-2, beta-1, beta-2 and beta-3 power more over the right than over the left hemisphere. However, also a left temporal and frontal delta increase was observed. In conclusion, EEG topography and tomography of depressed menopausal patients demonstrated a right frontal hyper- and left frontal hypoactivation in the alpha asymmetry index as well as a vigilance decrease, with a right-hemispheric preponderance. Within antidepressants at least 2 subtypes may be distinguished from the electrophysiological point of view, a non-sedative and a sedative. LORETA identifies cerebral generators responsible for the pathogenesis of depression as well as for the mode of action of antidepressants.

Association study of theta EEG asymmetry and brain-derived neurotrophic factor gene variants in childhood-onset mood disorder

BACKGROUND

Childhood-onset mood disorders (COMD) include various serious, disabling psychiatric conditions that are heterogeneous in presentation and etiology. Because intermediate phenotypes may help to identify genetic contributors to COMD, we tested for an association between variants in the brain-derived neurotrophic factor (BDNF) gene and theta EEG asymmetry, both of which have been independently implicated in affective disorders.

METHODS

Theta EEG asymmetry measures were calculated for a total of 191 individuals with COMD and 93 controls, who were also genotyped at seven BDNF single-nucleotide polymorphism (SNPs), two intergenic flanking SNPs, and one SNP in the lin-7 homolog C (Caenorhabditis elegans) (LIN7C) gene.

RESULTS

Adjusting for sex and ethnicity in linear models of asymmetry scores at ten brain regions, significant genotype and genotype-by-ethnicity interactions were observed for marker Val66Met in two parietal (P3/4 and P7/8) regions in the depressed group only.

CONCLUSIONS

Our results suggest that the functional Val66Met polymorphism affects theta EEG asymmetry in parietal brain regions specifically in individuals with COMD.

Perceptual Asymmetry for Chimeric Faces and Winter Disturbances in Mood and Behavior

Abstract. Different affective disturbances are related to brain activity, and, thus, to perceptual bias in very specific ways ( Keller et al., 2000 ). During the winter months, approximately 90% of people report lowered levels of mood and increased levels of anxiety to varying degrees (e.g., Magnusson, 2000 ). The current study examines the relationship between such winter mood disturbances and perceptual asymmetry on the chimeric-face task using a nonclinical sample (38 males and 92 females). Because of the suggested influence of symbolic light on cognitive processing of seasonal depressives ( Bouhuys, Meesters, Jansen, & Bloem, 1994 ), chimeric faces were presented on both symbolic bright and dark backgrounds. Face processing demonstrated the expected left hemifacial perceptual bias. However, the magnitude of individuals' perceptual bias bore no relation to subjectively reported seasonality, depressed mood, or anxiety. This was regardless of whether the faces were displayed on symbolic bright or dark backgrounds. Methodological factors must be considered. However, results are discussed in terms of the importance of clarifying the distinct nature of the psychological and neurobiological profile associated with winter disturbances in mood, and the possible influences of symbolic light on cognitive processing.

Advances in quantitative electroencephalogram analysis methods

Quantitative electroencephalogram (qEEG) plays a significant role in EEG-based clinical diagnosis and studies of brain function. In past decades, various qEEG methods have been extensively studied. This article provides a detailed review of the advances in this field. qEEG methods are generally classified into linear and nonlinear approaches. The traditional qEEG approach is based on spectrum analysis, which hypothesizes that the EEG is a stationary process. EEG signals are nonstationary and nonlinear, especially in some pathological conditions. Various time-frequency representations and time-dependent measures have been proposed to address those transient and irregular events in EEG. With regard to the nonlinearity of EEG, higher order statistics and chaotic measures have been put forward. In characterizing the interactions across the cerebral cortex, an information theory-based measure such as mutual information is applied. To improve the spatial resolution, qEEG analysis has also been combined with medical imaging technology (e.g., CT, MR, and PET). With these advances, qEEG plays a very important role in basic research and clinical studies of brain injury, neurological disorders, epilepsy, sleep studies and consciousness, and brain function.

Source distribution of neuromagnetic slow wave activity in schizophrenic and depressive patients

OBJECTIVE

Focal slow waves in the delta and theta frequency range frequently appear in psychopathological conditions. Due to their focal nature they can be localized by dipole modeling. We previously reported regional clustering of slow waves in temporal and parietal cortex of schizophrenic patients whereas such activity is largely absent in normals. Here we examine, to what extent distribution of slow wave generators differentiates schizophrenic from depressive syndromes.

METHODS

The regional densities of generators of focal slow waves were determined during resting conditions in patients with DSM-IV diagnoses of schizophrenia (N=25) and depression (N=27) and in 18 healthy controls.

RESULTS

Schizophrenic patients demonstrated accentuated temporal and parietal delta and theta dipole clustering, when compared to both the control and the depressive sample. In contrast, depressive patients had reduced frontal and prefrontal delta and theta dipole density relative to both schizophrenics and controls. This pattern was not related to age. Men generally displayed somewhat higher slow wave activity than women. For the areas of most pronounced slow wave deviances activity within each group was related to symptom scores: higher left-temporal slow wave activity was associated with hallucinations in schizophrenics, suppression of left-prefrontal slow wave activity correlated with depression scores.

CONCLUSIONS

Results suggest that slow wave distribution may assist in differentially diagnosing psychopathological conditions.