Electroencephalographic Correlates of Suicidal Ideation in the Theta Band

Association of resting-state EEG with suicidality in depressed patients: a systematic review

OBJECTIVE

The incidence of suicide is high among adolescents and young adults, especially those suffering from psychiatric diseases. Because of the reported association between depression and suicidality, exploring suicide risk factors in depressed patients is crucial for the identification of those at high risk and preventing suicide. In recent decades, electroencephalography parameters have been considered for identifying biomarkers of suicide ideation and attempts in depressed patients. This study aimed to review the available literature on resting-state EEG for suicidality in depressed patients.

METHOD

A systematic search was performed in five electronic databases, including APA PsycINFO, Embase, Medline (via PubMed), Scopus, and Web of Science. Papers with full text available in English in which resting-state EEG was evaluated in depressed patients with suicide ideation or suicide attempts compared to a control group of healthy subjects or non-suicidal depressed patients were included. The risk of bias was assessed by using the Newcastle-Ottawa scale.

RESULTS

A total of 4665 references were retrieved from five electronic databases from which eleven studies were included in this systematic review. A meta-analysis was not performed due to the substantial heterogeneity of the studies. Five of the eleven reviewed papers were classified as high-quality, and six had moderate quality.

CONCLUSIONS

According to the included studies in this review, the EEG signals of depressed patients with suicide ideation or suicide attempts may be different from patients with low risk of suicidality or healthy subjects. Connectivity measures sound more promising parameters than the power spectral analysis and EEG asymmetry.

PROTOCOL REGISTRATION

The protocol of this review was registered in PROSPERO (No. CRD42024502056).

EEG oscillations in recent suicide attempters: Assessing responses to positive and negative future imagination tasks

BACKGROUND

Our goal is to uncover Electroencephalography (EEG) power spectrum patterns during imagination tasks in individuals who attempted suicide within the past 1-4 weeks, addressing gaps in understanding the neural correlates of future imagination in suicidal behavior.

METHODS

This case-control study comprised a total of 60 participants, consisting of 47 females and 13 males. The sample comprised three groups: Attempted Suicide + Major Depressive Disorder (SA+MDD), Major Depressive Disorder (MDD), and Healthy Controls (HC). To assess participants' future imagination, a unique approach called the Positive and Negative Future Imagination Task was designed, which involved scenario visualization concurrent with EEG recording. Statistical analyses included ANOVA with post-hoc pairwise comparisons to compare EEG power spectrum between three groups.

RESULTS

It was observed that the SA+MDD group experienced significantly increased theta frequency band in the right frontocentral regions when compared to the MDD group during both positive and negative imagination tasks (P-value < 0.05). Furthermore, increased gamma activity was observed in the SA+MDD group compared to the HC group, predominantly in the right frontocentral areas during both imagination tasks.

CONCLUSION

The results of this study indicate that individuals who have recently attempted suicide exhibit heightened neural activity in the frontocentral regions of the right hemisphere of the brain, specifically in theta and gamma band frequencies, when contemplating both positive and negative aspects of the future. These findings, in the context of behavioral tasks may indicate a decrease in the ability to envision a positive future and an increase in visualizing a negative future.

Electroencephalography-based endogenous phenotype of diagnostic transition from major depressive disorder to bipolar disorder

The neuropathology of mood disorders, including the diagnostic transition from major depressive disorder (MDD) to bipolar disorder (BD), is poorly understood. This study investigated resting-state electroencephalography (EEG) activity in patients with MDD and those whose diagnosis changed from MDD to BD. Among sixty-eight enrolled patients with MDD, the diagnosis of 17 patients converted to BD during the study period. We applied machine learning techniques to differentiate the two groups using sensor- and source-level EEG features. At the sensor level, patients with BD showed higher theta band power at the AF3 channel and low-alpha band power at the FC5 channel compared to patients with MDD. At the source level, patients with BD showed higher theta band activity in the right anterior cingulate and low-alpha band activity in the left parahippocampal gyrus. These four EEG features were selected for discriminating between BD and MDD with the best classification performance showing an accuracy of 80.88%, a sensitivity of 76.47%, and a specificity of 82.35%. Our findings revealed distinct theta and low-alpha band activities in patients with BD and MDD. These differences could potentially serve as candidate neuromarkers for the diagnosis and diagnostic transition between the two distinct mood disorders.

Neural activity during inhibitory control predicts suicidal ideation with machine learning

Suicide is a leading cause of death in the US and worldwide. Current strategies for preventing suicide are often focused on the identification and treatment of risk factors, especially suicidal ideation (SI). Hence, developing data-driven biomarkers of SI may be key for suicide prevention and intervention. Prior attempts at biomarker-based prediction models for SI have primarily used expensive neuroimaging technologies, yet clinically scalable and affordable biomarkers remain elusive. Here, we investigated the classification of SI using machine learning (ML) on a dataset of 76 subjects with and without SI(+/-) (n = 38 each), who completed a neuro-cognitive assessment session synchronized with electroencephalography (EEG). SI+/- groups were matched for age, sex, and mental health symptoms of depression and anxiety. EEG was recorded at rest and while subjects engaged in four cognitive tasks of inhibitory control, interference processing, working memory, and emotion bias. We parsed EEG signals in physiologically relevant theta (4-8 Hz), alpha (8-13 Hz), and beta (13-30 Hz) frequencies and performed cortical source imaging on the neural signals. These data served as SI predictors in ML models. The best ML model was obtained for beta band power during the inhibitory control (IC) task, demonstrating high sensitivity (89%), specificity (98%). Shapley explainer plots further showed top neural predictors as feedback-related power in the visual and posterior default mode networks and response-related power in the ventral attention, fronto-parietal, and sensory-motor networks. We further tested the external validity of the model in an independent clinically depressed sample (n = 35, 12 SI+) that engaged in an adaptive test version of the IC task, demonstrating 50% sensitivity and 61% specificity in this sample. Overall, the study suggests a promising, scalable EEG-based biomarker approach to predict SI that may serve as a target for risk identification and intervention.

Identifying unique subgroups in suicide risks among psychiatric outpatients

BACKGROUND

The presence of psychiatric disorders is widely recognized as one of the primary risk factors for suicide. A significant proportion of individuals receiving outpatient psychiatric treatment exhibit varying degrees of suicidal behaviors, which may range from mild suicidal ideations to overt suicide attempts. This study aims to elucidate the transdiagnostic symptom dimensions and associated suicidal features among psychiatric outpatients.

METHODS

The study enrolled patients who attended the psychiatry outpatient clinic at a tertiary hospital in South Korea (n = 1, 849, age range = 18-81; 61% women). A data-driven classification methodology was employed, incorporating a broad spectrum of clinical symptoms, to delineate distinctive subgroups among psychiatric outpatients exhibiting suicidality (n = 1189). A reference group of patients without suicidality (n = 660) was included for comparative purposes to ascertain cluster-specific sociodemographic, suicide-related, and psychiatric characteristics.

RESULTS

Psychiatric outpatients with suicidality (n = 1189) were subdivided into three distinctive clusters: the low-suicide risk cluster (Cluster 1), the high-suicide risk externalizing cluster (Cluster 2), and the high-suicide risk internalizing cluster (Cluster 3). Relative to the reference group (n = 660), each cluster exhibited distinct attributes pertaining to suicide-related characteristics and clinical symptoms, covering domains such as anxiety, externalizing and internalizing behaviors, and feelings of hopelessness. Cluster 1, identified as the low-suicide risk group, exhibited less frequent suicidal ideation, planning, and multiple attempts. In the high-suicide risk groups, Cluster 2 displayed pronounced externalizing symptoms, whereas Cluster 3 was primarily defined by internalizing and hopelessness symptoms. Bipolar disorders were most common in Cluster 2, while depressive disorders were predominant in Cluster 3.

DISCUSSION

Our findings suggest the possibility of differentiating psychiatric outpatients into distinct, clinically relevant subgroups predicated on their suicide risk. This research potentially paves the way for personalizing interventions and preventive strategies that address cluster-specific characteristics, thereby mitigating suicide-related mortality among psychiatric outpatients.

EEG wakefulness regulation in transdiagnostic patients after a recent suicide attempt

OBJECTIVE

Decades of research have not yet produced statistically reliable predictors of preparatory behavior eventually leading to suicide attempts or deaths by suicide. As the nature of suicidal behavior is complex, it is best investigated in a transdiagnostic approach, while assessing objective markers, as proposed by the Research Domain Criteria (Cuthbert, 2013).

METHODS

A 15-min resting-state EEG was recorded in 45 healthy controls, and 49 transdiagnostic in-patients with a recent (<6 months) suicide attempt. Brain arousal regulation in eyes-closed condition was assessed with the Vigilance Algorithm Leipzig (VIGALL) (Sander et al., 2015).

RESULTS

A significant incline of median vigilance and vigilance slope was observed in patients within the first 3-min of the EEG recording. Additionally, a significant positive correlation of self-reported suicidal ideation with the vigilance slope over 15-min recording time, as well as a significant negative correlation with EEG vigilance stage A1 during the first 3-min was found.

CONCLUSIONS

Transdiagnostic patients with a recent suicide attempt show a distinct vigilance regulation pattern. Further studies including a control group consisting of patients without life-time suicide attempts are needed to increase the clinical utility of the findings.

SIGNIFICANCE

These findings might serve as potential objective markers of suicidal behavior.

Decreased beta 1 (12-15 Hertz) power modulates the transfer of suicidal ideation to suicide in major depressive disorder

BACKGROUND

Suicide prevention for major depressive disorder (MDD) is a worldwide challenge, especially for suicide attempt (SA). Viewing suicide as a state rather than a lifetime event provided new perspectives on suicide research.

OBJECTIVE

This study aimed to verify and complement SAs biomarkers of MDD with a recent SA sample.

METHODS

This study included 189 participants (60 healthy controls; 47 MDD patients with non-suicide (MDD-NSs), 40 MDD patients with suicide ideation (MDD-SIs) and 42 MDD patients with SA (MDD-SAs)). MDD patients with an acute SA time was determined to be within 1 week since the last SA. SUICIDALITY Part in MINI was applied to evaluate suicidality. Absolute powers in 14 frequency bands were extracted from subject's resting-state electroencephalography data and compared within four groups. The relationship among suicidality, the number of SA and powers in significant frequency bands were investigated.

RESULTS

MDD-SIs had increased powers in delta, theta, alpha and beta band on the right frontocentral channels compared to MDD-NSs, while MDD-SAs had decreased powers in delta, beta and gamma bands on widely the right frontocentral and parietooccipital channels compared to MDD-SIs. Beta 1 power was the lowest in MDD-SAs and was modulated by the number of SA. The correlation between suicidality and beta 1 power was negative in MDD-SAs and positive in MDD-SIs.

CONCLUSION

Reduced beta 1 (12-15 Hz) power could be essential in promoting suicidal behaviour in MDD. Research on recent SA samples contributes to a better understanding of suicide mechanisms and preventing suicidal behaviour in MDD.

Analysis of EEG features and study of automatic classification in first-episode and drug-naïve patients with major depressive disorder

BACKGROUND

Major depressive disorder (MDD) has a high incidence and an unknown mechanism. There are no objective and sensitive indicators for clinical diagnosis.

OBJECTIVE

This study explored specific electrophysiological indicators and their role in the clinical diagnosis of MDD using machine learning.

METHODS

Forty first-episode and drug-naïve patients with MDD and forty healthy controls (HCs) were recruited. EEG data were collected from all subjects in the resting state with eyes closed for 10 min. The severity of MDD was assessed by the Hamilton Depression Rating Scale (HAMD-17). Machine learning analysis was used to identify the patients with MDD.

RESULTS

Compared to the HC group, the relative power of the low delta and theta bands was significantly higher in the right occipital region, and the relative power of the alpha band in the entire posterior occipital region was significantly lower in the MDD group. In the MDD group, the alpha band scalp functional connectivity was overall lower, while the scalp functional connectivity in the gamma band was significantly higher than that in the HC group. In the feature set of the relative power of the ROI in each band, the highest accuracy of 88.2% was achieved using the KNN classifier while using PCA feature selection. In the explanatory model using SHAP values, the top-ranking influence feature is the relative power of the alpha band in the left parietal region.

CONCLUSIONS

Our findings reveal that the abnormal EEG neural oscillations may reflect an imbalance of excitation, inhibition and hyperactivity in the cerebral cortex in first-episode and drug-naïve patients with MDD. The relative power of the alpha band in the left parietal region is expected to be an objective electrophysiological indicator of MDD.

Evidence for Altered Electroencephalography Coherence in Depressed Adolescents with Suicidal Ideation and Behaviors

Introduction: Major depressive disorder (MDD) is a primary risk factor for suicide, which is one of the leading causes of death among adolescents worldwide. Understanding the heterogeneity of suicidality in adolescents with MDD is critical for suicide prevention and intervention discovery. Quantitative electroencephalography (EEG) is a promising tool to address the knowledge gaps related to the neurophysiological characteristics of depression and suicidality. This study sought to examine resting-state EEG coherence differences in adolescents with MDD and suicidal ideation (SI)/behaviors (SB) and healthy controls (HC) to assess the utility of coherence as a biomarker of suicide. Methods: Twenty-six adolescents with MDD who were hospitalized for suicidality and 30 HC were recruited. The clinical sample was divided into SI (n = 9) and SB (n = 19) subgroups. Eyes closed resting-state EEG were recorded, and coherence was calculated. Depression severity and suicidality were assessed with the Children's Depression Rating Scale Revised and the Columbia Suicide Severity Rating Scale, respectively. Results: There were intrahemispheric differences in the right hemisphere across multiple electrode pairs. Delta, alpha, and beta coherence were higher in the SB group over the right prefrontofrontal and left parietooccipital electrode pairs, while alpha coherence was higher in the HC group over the right centroparietal electrode pair. There were no significant differences between HC and SI groups in any electrode pair. Conclusions: Patients with recent SB showed increased coherence in right frontal regions compared with patients with SI, suggesting altered cognitive states between those with SB and SI. These findings may have implications for suicide prevention in adolescents and could serve as useful biomarkers in clinical settings, but larger studies are needed to confirm the results.

The Link between Suicidality and Electroencephalography Asymmetry: A Systematic Review and Meta-analysis

As one of the leading causes of death globally, suicide has been researched extensively to better understand factors that confer risk or resilience for suicidality. Promising areas of the literature have focused on brain-based factors that might indicate susceptibility to suicide. Some studies have investigated the link between electroencephalography (EEG) asymmetry, referring to differences in electrical activity in the brain from the left to right hemisphere, and suicidality. The present study is a comprehensive review and meta-analysis of the literature to see if certain patterns in EEG asymmetry serve as a diathesis for suicidal thoughts and behaviors. The results of the current investigation found that EEG asymmetry was not systematically related to suicide based on the literature reviewed. While the present review does not rule out all brain-based factors, the findings suggest that EEG asymmetry may not be a biomarker for suicidality.

Biobehavioral mechanisms underlying testosterone and mood relationships in peripubertal female adolescents

The pubertal transition is characterized by pronounced sex hormone fluctuation, refinement of affective neural circuitry, and an increased risk of depression in female adolescents. Sex hormones, including testosterone, exert modulatory effects on frontal-limbic brain networks and are associated with emotion dysregulation and depressive symptoms. Weekly changes in hormones predict affective symptoms in peripubertal female adolescents, particularly in the context of stress; however, the biobehavioral mechanisms underlying hormone change and mood relationships during the pubertal transition have yet to be determined and was the objective of the present study. Forty-three peripubertal female adolescents (ages 11-14) collected 8-weekly salivary hormone (estrone, testosterone) samples and mood assessments to evaluate hormone-mood relationships, followed by a biobehavioral testing session with psychosocial stress and EEG. Within-person correlations between weekly hormone changes and corresponding mood were performed to determine individual differences in mood sensitivity to weekly hormone change. Increased frontal theta activity indexing emotion reactivity, reduced cortisol reactivity, and reduced vagal efficiency predicted the strength of the relationship between testosterone and mood. Further, testosterone-sensitivity strength was associated with the enhancement of negative affect following stress testing. Results identify divergent frontal theta and stress responses as potential biobehavioral mechanisms underlying mood sensitivity to peripubertal testosterone fluctuation.

A resting state EEG study on depressed persons with suicidal ideation

Background

Major Depressive Disorder (MDD) is a psychiatric illness that is often associated with potentially life-threatening physiological changes and increased risk for suicidal behavior. Electroencephalography (EEG) research suggests an association between depression and specific frequency imbalances in the frontal brain region. Further, while recently developed technology has been proposed to simplify EEG data acquisition, more research is still needed to support its use in patients with MDD.

Methods

Using the 14-channel EMOTIV EPOC cap, we recorded resting state EEG from 15 MDD patients with and MDD persons with suicidal ideation (SI) vs. 12 healthy controls (HC) to investigate putative power spectral density (PSD) between-group differences at the F3 and F4 electrode sites. Specifically, we explored 1) between-group alpha power asymmetries (AA), 2) between-group differences in delta, theta, alpha and beta power, 3) between PSD data and the scores in the Beck's Depression Inventory-II (BDI-II), Beck's Anxiety Inventory (BAI), Reasons for Living Inventory (RFL), and Self-Disgust Questionnaire (SDS).

Results

When compared to HC, patients had higher scores on the BAI (p = 0.0018), BDI-II (p = 0.0001) or SDS (p = 0.0142) scale and lower scores in the RFL (p = 0.0006) scale. The PSD analysis revealed no between-group difference or correlation with questionnaire scores for any of the measures considered.

Conclusions

The present study could not confirm previous research suggesting frequency-specific anomalies in depressed persons with SI but might suggest that frontal EEG imbalances reflect greater anxiety and negative self-referencing. Future studies should confirm these findings in a larger population sample.

Resting State EEG Correlates of Suicide Ideation and Suicide Attempt

Suicide is a global phenomenon that impacts individuals, families, and communities from all income groups and all regions worldwide. While it can be prevented if personalized interventions are implemented, more objective and reliable diagnostic methods are needed to complement interview-based risk assessments. In this context, electroencephalography (EEG) might play a key role. We systematically reviewed EEG resting state studies of adults with suicide ideation (SI) or with a history of suicide attempts (SAs). After searching for relevant studies using the PubMed and Web of Science databases, we applied the PRISMA method to exclude duplicates and studies that did not match our inclusion criteria. The selection process yielded seven studies, which suggest that imbalances in frontal and left temporal brain regions might reflect abnormal activation and correlate with psychological distress. Furthermore, asymmetrical activation in frontal and posterior cortical regions was detected in high-risk depressed persons, although the pattern in the frontal region was inverted in non-depressed persons. The literature reviewed suggests that SI and SA may be driven by separate neural circuits and that high-risk persons can be found within non-depressed populations. More research is needed to develop intelligent algorithms for the automated detection of high-risk EEG anomalies in the general population.

Low global frontal brain activity is associated with non-planned or impulsive suicide attempts. A preliminary study

BACKGROUND

Suicide prevention is limited by the frequent non-planned or impulsive nature of suicidal behavior. For instance, 25-62 % of suicide attempts, occur within 30 min of the onset of suicidal ideation. We aimed to examine frontal brain activity in depressed patients following a suicide attempt and its relationship with the duration of the suicidal process.

METHODS

We recruited 35 adult patients within three days of a suicide attempt of at least moderate lethality. Duration of the suicidal process was recorded in a semi-structured interview, including suicide contemplation (time from onset of suicidal ideation to decision to kill oneself) and suicide action intervals (time from the decision to kill oneself to suicide attempt). Resting state EEG data from AF7, AF8, TP9 and TP10 leads was collected with a portable MUSE 2 headband system. The average frequency values throughout a 5-minute portable EEG recording were extracted for delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-30 Hz) waves.

RESULTS

Delta (r = 0.450, p = 0.021) and theta power (r = 0.395, p = 0.044) were positively correlated with the duration of the suicide action interval. There were no significant correlations of the suicide contemplation interval with clinical or EEG measures. Patients with suicide action interval shorter than 30 min showed lower delta power (U = 113, p = 0.049) compared with those with longer duration.

CONCLUSIONS

Lower theta and delta activity may reflect hindered cognitive control and inhibition in impulsive suicide attempters. Portable EEG may provide a valuable tool for clinical research and in the management of acutely suicidal patients.

Retrospective analysis of quantitative electroencephalography changes in a dissimulating patient after dying by suicide: A single case report

We present the case of a 49-year-old man who was diagnosed with depressive disorder, with the first episode having a strong reactive factor. He was involuntarily admitted to a psychiatric hospital after a failed attempt at taking his own life, where he responded to psychotherapy and antidepressant therapy, as evidenced by a &gt;60% reduction in his MADRS total score. He was discharged after 10 days of treatment, denied having suicidal ideations, and was motivated to follow the recommended outpatient care. The risk for suicide during hospitalization was also assessed using suicide risk assessment tools and psychological assessments, including projective tests. The patient underwent a follow-up examination with an outpatient psychiatrist on the 7th day after discharge, during which the suicide risk assessment tool was administered. The results indicated no acute suicide risk or worsening of depressive symptoms. On the 10th day after discharge, the patient took his own life by jumping out of the window of his flat. We believe that the patient had dissimulated his symptoms and possessed suicidal ideations, which were not detected despite repeated examinations specifically designed to assess suicidality and depression symptoms. We retrospectively analyzed his quantitative electroencephalography (QEEG) records to evaluate the change in prefrontal theta cordance as a potentially promising biomarker of suicidality, given the inconclusive results of studies published to date. An increase in prefrontal theta cordance value was found after the first week of antidepressant therapy and psychotherapy in contrast to the expected decrease due to the fading of depressive symptoms. As demonstrated by the provided case study, we hypothesized that prefrontal theta cordance may be an EEG indicator of a higher risk of non-responsive depression and suicidality despite therapeutic improvement.

The reality of virtual reality

Virtual reality (VR) has become a popular tool for investigating human behavior and brain functions. Nevertheless, it is unclear whether VR constitutes an actual form of reality or is more like an advanced simulation. Determining the nature of VR has been mostly achieved by self-reported presence measurements, defined as the feeling of being submerged in the experience. However, subjective measurements might be prone to bias and, most importantly, do not allow for a comparison with real-life experiences. Here, we show that real-life and VR height exposures using 3D-360° videos are mostly indistinguishable on a psychophysiological level (EEG and HRV), while both differ from a conventional 2D laboratory setting. Using a fire truck, three groups of participants experienced a real-life (N = 25), a virtual (N = 24), or a 2D laboratory (N = 25) height exposure. Behavioral and psychophysiological results suggest that identical exogenous and endogenous cognitive as well as emotional mechanisms are deployed to process the real-life and virtual experience. Specifically, alpha- and theta-band oscillations in line with heart rate variability, indexing vigilance, and anxiety were barely indistinguishable between those two conditions, while they differed significantly from the laboratory setup. Sensory processing, as reflected by beta-band oscillations, exhibits a different pattern for all conditions, indicating further room for improving VR on a haptic level. In conclusion, the study shows that contemporary photorealistic VR setups are technologically capable of mimicking reality, thus paving the way for the investigation of real-world cognitive and emotional processes under controlled laboratory conditions. For a video summary, see https://youtu.be/fPIrIajpfiA.

Fusion of pain avoidance and the contingent negative variation induced by punitive condition predict suicide ideation in a college population

This study examined behavioral and ERP features involved in pain processing as predictors of suicide ideation. Twenty-seven depressed undergraduates with high suicide ideation (HSI), 23 depressed undergraduates with low suicide ideation (LSI), and 32 healthy controls (HCs) completed the clinical Scales. The amplitudes of LPP, P2, P3, CNV, FRN, power in the beta, theta, and delta bands in the SAID task were multimodal EEG features. A machine learning algorithm known as support vector machine was used to select optimal feature sets for predicting pain avoidance, depression, and suicide ideation. The accuracy of suicide ideation classification was significantly higher for multimodal features (78.16%) which pain avoidance ranked the first and the CNV ranked the fifth than a single ERP feature model (66.62%). Pain avoidance emerged as the most optimal feature of suicide ideation classification than depression. And the CNV elicited by punitive cues may be a biomarker in suicide ideation. Pain avoidance and its related EEG components may improve the efficacy of suicide ideation classification as compared to depression.

[EEG correlates of suicidal intentions in depressive patients who survived and have not been ill with COVID-19]

OBJECTIVE

To search for EEG correlates of suicidal intentions in young depressive patients who survived and have not been ill with COVID-19.

MATERIAL AND METHODS

We studied 46 female patients, aged 16-25 years, with depressive disorders who had previously had a mild or asymptomatic coronavirus infection («COVID» group) and 40 female patients with depressive disorders matched in age, syndromic structure of disorders and the initial severity of depression to patients of the «COVID» group but who are known not to have COVID-19 («non-COVID» group). The severity of suicidal intentions was assessed by the number of points of item 3 of HDRS-17. In all patients, pre-treatment multichannel background EEG was recorded with spectral power analysis in narrow frequency sub-bands.

RESULTS

In patients of the «COVID» group, the mean number of points of item 3 of HDRS-17 was slightly higher (at the trend level) than in the «non-COVID» group (2.1±1.5 and 1.8±1.6 points, respectively), and positively correlated (p<0.05) with the spectral power values of theta2 (6-8 Hz) and delta (2-4 Hz) EEG sub-bands. In the «non-COVID» group, the severity of suicidal intentions positively correlated (p<0.05) with the values of the spectral power of alpha2 (9-11 Hz) EEG sub-band.

CONCLUSION

Suicidal intentions increased in depressive patients survived from COVID-19, and their severity is associated with EEG signs of a reduced functional state of the cerebral cortex.

Magnetoencephalography biomarkers of suicide attempt history and antidepressant response to ketamine in treatment-resistant major depression

BACKGROUND

This study examined magnetoencephalographic (MEG) correlates of suicidal ideation (SI) and suicide attempt history in patients with treatment-resistant major depression (TRD) at baseline and following subanesthetic-dose ketamine infusion.

METHODS

Twenty-nine drug-free TRD patients (12 suicide attempters/17 non-attempters) participated in a crossover randomized trial of ketamine. MEG data were collected during an attentional dot probe task with emotional face stimuli at baseline and several hours post-ketamine infusion. Synthetic aperture magnetometry was used to project source power in the theta, alpha, beta, and gamma frequencies for angry-neutral, happy-neutral, and neutral-neutral face pairings during a one-second peristimulus period. Mixed models were used to test for clinical, behavioral, and electrophysiological effects of group, emotion, session, and SI score.

RESULTS

Ketamine significantly reduced SI and depression across the sample. Post-ketamine, attempters had improved accuracy and non-attempters had reduced accuracy on the task. SI was positively associated with gamma power in regions of the frontal and parietal cortices across groups. In an extended amygdala-hippocampal region, attempters differed significantly in their emotional reactivity to angry versus happy faces as indexed by theta power differences, irrespective of drug. Ketamine significantly reduced the association between alpha power and SI for angry compared with happy faces in a fronto-insular/anterior cingulate region important for regulating sensory attentiveness.

LIMITATIONS

Limitations include a small sample size of attempters.

CONCLUSIONS

The findings highlight key differences in band-limited power between attempters and non-attempters and reinforce previous findings that ketamine has distinct response properties in patients with a suicide history.

Are sick people really more impulsive?: Investigating inflammation-driven impulsivity

In both animals and humans, inflammatory stimuli - especially infections and endotoxin injections - cause "sickness behaviors," including lethargy, malaise, and low mood. An emerging line of research asserts that inflammation may provoke present-focused decision making and impulsivity. The current article assesses that claim in the context of the broader literature - including preclinical models and clinical interventions. This literature presents three challenges to purported inflammation-impulsivity link that have not been addressed to date: (1) the nebulous and imprecise definition of impulsivity; (2) reverse causality; and (3) a lack of causal evidence. These challenges point to ways in which future research designs can improve upon the extant literature to further explore the ostensible relationship between inflammation and impulsivity.

A dimensional approach to affective disorder: The relations between Scl-90 subdimensions and QEEG parameters

OBJECTIVES

QEEG reflects neuronal activity directly rather than using indirect parameters, such as blood deoxygenation and glucose utilization, as in fMRI and PET. The correlation between QEEG spectral power density and Symptom Check List-90-R may help identify biomarkers pertaining to brain function, associated with affective disorder symptoms. This study aims at determining whether there is a relation between QEEG spectral power density and Symptom Check List-90-R symptom scores in affective disorders.

METHODS

This study evaluates 363 patients who were referred for the initial application and diagnosed with affective disorders according to DSM-V, with QEEG and Scl-90-R. Spectral power density was calculated for the 18 electrodes representing brain regions.

RESULTS

Somatization scores were found to be correlated with Pz and O1 theta, O1 and O2 high beta. Whereas FP1 delta activities were correlated with anxiety, F3, F4, and Pz theta were correlated with obsession scores. Interpersonal sensitivity scores were found to be correlated with F4 delta, P3, T5, P4, T6 alpha and T5, and T6 theta activities. While depression scores were correlated with P3 and T4 delta, as well as T4 theta, there was a correlation between anger and F4, as well as T4 alpha and F8 high beta activities. Paranoia scores are correlated with FP1, F7, T6 and F8 theta, T5 and F8 delta, and O2 high beta activities.

CONCLUSIONS

According to our results, anxiety, obsession, interpersonal sensitivity, depression, anger, and paranoia are related to some spectral powers of QEEG. Delta-beta coupling seems to be a neural biomarker for affective dysregulation.

Theta oscillations: A rhythm difference comparison between major depressive disorder and anxiety disorder

BACKGROUND

Due to substantial comorbidities of major depressive disorder (MDD) and anxiety disorder (AN), these two disorders must be distinguished. Accurate identification and diagnosis facilitate effective and prompt treatment. EEG biomarkers are a potential research hotspot for neuropsychiatric diseases. The purpose of this study was to investigate the differences in EEG power spectrum at theta oscillations between patients with MDD and patients with AN.

METHODS

Spectral analysis was used to study 66 patients with MDD and 43 patients with AN. Participants wore 16-lead EEG caps to measure resting EEG signals. The EEG power spectrum was measured using the fast Fourier transform. Independent samples t-test was used to analyze the EEG power values of the two groups, and p < 0.05 was statistically significant.

RESULTS

EEG power spectrum of the MDD group significantly differed from the AN group in the theta oscillation on 4-7 Hz at eight electrode points at F3, O2, T3, P3, P4, FP1, FP2, and F8.

CONCLUSION

Participants with anxiety demonstrated reduced power in the prefrontal cortex, left temporal lobe, and right occipital regions. Confirmed by further studies, theta oscillations could be another biomarker that distinguishes MDD from AN.

Spontaneous transient states of fronto-temporal and default-mode networks altered by suicide attempt in major depressive disorder

Major depressive disorder (MDD) is associated with increased suicidality, and it's still challenging to identify suicide in clinical practice. Although suicide attempt (SA) is the most relevant precursor with multiple functional abnormalities reported from neuroimaging studies, little is known about how the spontaneous transient activated patterns organize and coordinate brain networks underlying SA. Thus, we obtained resting-state magnetoencephalography data for two MDD subgroups of 44 non-suicide patients and 34 suicide-attempted patients, together with 49 matched health-controls. For the source-space signals, Hidden Markov Model (HMM) helped to capture the sub-second dynamic activity via a hidden sequence of finite number of states. Temporal parameters and spectral activation were acquired for each state and then compared between groups. Here, HMM states characterized the spatiotemporal signatures of eight networks. The activity of suicide attempters switches more frequently into the fronto-temporal network, as the time spent occupancy of fronto-temporal state is increased and interval time is decreased compared with the non-suicide patients. Moreover, these changes are significantly correlated with Nurses' Global Assessment of Suicide Risk scores. Suicide attempters also exhibit increased state-wise activations in the theta band (4-8 Hz) in the posterior default mode network centered on posterior cingulate cortex, which can't be detected in the static spectral analysis. These alternations may disturb the time allocations of cognitive control regulations and cause inflexible decision making to SA. As the better sensitivity of dynamic study in reflecting SA diathesis than the static is validated, dynamic stability could serve as a potential neuronal marker for SA.

Differences of EEG Frequency and Spatial Parameters in Depressive Female Adolescents With Suicidal Attempts and Non-suicidal Self-injuries

Background. Both non-suicidal self-injuries (NSSIs) and suicidal attempts (SAs) in adolescence represent significant risk factors for consequent suicide, but neurophysiological markers and predictors of these two forms of auto-aggressive behavior have been studied insufficiently. Objective. The aim of the study was to identify the differences of electroencephalographic (EEG) frequency and spatial parameters between depressive female adolescents with solely NSSI, and with combined NSSI + SA behavior in their history. Methods. The study included 45 female depressive in-patients aged 16-25 years. Baseline resting EEG spectral power, asymmetry, and coherence were analyzed in 8 narrow frequency sub-bands. Results. In the NSSI + SA subgroup (n = 24), the spectral power of parietal-occipital alpha-2 (9-11 Hz) was higher than in the NSSI subgroup, its focus was localized in the right hemisphere, and alpha-3 (11-13 Hz) spectral power was higher than alpha-1 (8-9 Hz). In the NSSI subgroup (n = 21) alpha-1 spectral power was higher than alpha-3, and foci of alpha-2 and alpha-3 were localized in the left hemisphere. EEG coherence was also higher in the NSSI + SA subgroup than in the NSSI subgroup, especially in frontal-central-parietal regions. Conclusions. The spatial distribution of the EEG frequency components in the NSSI + SA subgroup reflects the greater activation of the left hemisphere that is more typical for the EEG of individuals with an increased risk for suicide. In the NSSI subgroup, the right hemisphere is relatively more activated, and EEG coherence is lower, which is more typical for EEG in depressive disorders. The results obtained suggested the use of EEG to clarify the degree of suicidal risk in depressive female adolescents with NSSI.

Abnormal brain activity in fronto-central regions in mental disorders with suicide: An EEG Study

Suicide is a global health problem, and early and accurate identification of suicide attempt individuals has very important clinical significance. Thus the exploration of neurobiological mechanisms underlying suicidal behavior is crucial for systematically preventing suicide. However, the neurophysiological biomarkers for identifying affective disorders with suicidal attempt are remain unknown. Here, we recruited 28 patients with mental disorders from Tianjin Anding Hospital, and the subjects were divided into suicide attempt group (SA=14) and non suicide attempt group (NSA=14) according to whether they had attempted suicide. We also recruited 14 healthy subjects matched with age and sex ratio as healthy control group (HC=14). By recording the electroencephalogram(EEG) data of 60 electrodes in resting state for eight minutes (four minutes with open eyes and four minutes with close eyes), the absolute power of five frequency bands( delta(0.5-4Hz), theta(4-8Hz), alpha(8-13Hz), beta (13-30Hz), gamma(30-65Hz)) were analyzed to explore the changes of brain rhythm. And then the Modulation index (MI) was calculated to quantify the intensity of phase amplitude coupling (PAC) between different frequency bands in different brain regions, so as to observe the mechanism of neuronal synchronization in different frequency bands. We found that the absolute power of SA group was significantly higher than NSA group and HC group in delta (P<0.05), beta (P<0.05) and gamma (P<0.05) bands. The PAC strength between beta and gamma was calculated and it showed that the PAC strength of SA group was significantly weaker than NSA group in fronto-central regions, indicating that decreased synchronization between neurons could bring about brain function impairment. These findings suggest that the brain electrical activity in the fronto-central regions of the SA group may be damaged, which may lead to an increased suicidal risk in mental disoders. The EEG activity in delta, beta, gamma band and PAC in fronto-central regions may be used as a potential clinical biomarker for preventing suicide.

An EEG signature of suicidal behavior in female patients with major depressive disorder? A non-replication

INTRODUCTION

A recent study showed hypoactivity in the beta/gamma band in female suicide ideators and suicide attempters diagnosed with depression, relative to a low-risk group. The current study aimed to conceptually replicate these results.

METHODS

In the iSPOT-D sub-sample (n = 402), suicide ideators and low-risk individuals were identified. Confining analyses to females only, differences between low-risk individuals and suicide ideators were tested for using the electroencephalogram (EEG) frequency bands SMR (Sensori-Motor-Rhythm; 12-15 Hz), beta (14.5-30 Hz), beta I (14.5-20 Hz), beta II (20-25 Hz), beta III (25-30 Hz), gamma I (31-49 Hz) using LORETA-software.

RESULTS

None of the tested frequency bands showed to be significantly different between suicide ideators and low-risk individuals.

CONCLUSIONS

The current study could not conceptually replicate the earlier published results. Several reasons could explain this non-replication, among which possible electromyographic (EMG) contamination in the beta/gamma band in the original study.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT00693849. URL: http://clinicaltrials.gov/ct2/show/NCT00693849.

Multilayer MEG functional connectivity as a potential marker for suicidal thoughts in major depressive disorder

Major depressive disorder (MDD) is highly heterogeneous in its clinical presentation. The present exploratory study used magnetoencephalography (MEG) to investigate electrophysiological intrinsic connectivity differences between healthy volunteers and unmedicated participants with treatment-resistant MDD. The study examined canonical frequency bands from delta through gamma. In addition to group comparisons, correlational studies were conducted to determine whether connectivity was related to five symptom factors: depressed mood, tension, negative cognition, suicidal thoughts, and amotivation. The MDD and healthy volunteer groups did not differ significantly at baseline when corrected across all frequencies and clusters, although evidence of generalized slowing in MDD was observed. Notably, however, electrophysiological connectivity was strongly related to suicidal thoughts, particularly as coupling of low frequency power fluctuations (delta and theta) with alpha and beta power. This analysis revealed hub areas underlying this symptom cluster, including left hippocampus, left anterior insula, and bilateral dorsolateral prefrontal cortex. No other symptom cluster demonstrated a relationship with neurophysiological connectivity, suggesting a specificity to these results as markers of suicidal ideation.

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.

Magnetoencephalographic Correlates of Suicidal Ideation in Major Depression

BACKGROUND

Defining the neurobiological underpinnings of suicidal ideation (SI) is crucial to improving our understanding of suicide. This study used magnetoencephalographic gamma power as a surrogate marker for population-level excitation-inhibition balance to explore the underlying neurobiology of SI and depression. In addition, effects of pharmacological intervention with ketamine, which has been shown to rapidly reduce SI and depression, were assessed.

METHODS

Data were obtained from 29 drug-free patients with major depressive disorder who participated in an experiment comparing subanesthetic ketamine (0.5 mg/kg) with a placebo saline infusion. Magnetoencephalographic recordings were collected at baseline and after ketamine and placebo infusions. During scanning, patients rested with their eyes closed. SI and depression were assessed, and a linear mixed-effects model was used to identify brain regions where gamma power and both SI and depression were associated. Two regions of the salience network (anterior insula, anterior cingulate) were then probed using dynamic causal modeling to test for ketamine effects.

RESULTS

Clinically, patients showed significantly reduced SI and depression after ketamine administration. In addition, distinct regions in the anterior insula were found to be associated with SI compared with depression. In modeling of insula-anterior cingulate connectivity, ketamine lowered the membrane capacitance for superficial pyramidal cells. Finally, connectivity between the insula and anterior cingulate was associated with improvements in depression symptoms.

CONCLUSIONS

These findings suggest that the anterior insula plays a key role in SI, perhaps via its role in salience detection. In addition, transient changes in superficial pyramidal cell membrane capacitance and subsequent increases in cortical excitability might be a mechanism through which ketamine improves SI.

Exploratory Analysis of Behavioral Impulsivity, Pro-inflammatory Cytokines, and Resting-State Frontal EEG Activity Associated With Non-suicidal Self-Injury in Patients With Mood Disorder

Introduction: Non-suicidal self-injury (NSSI) is a rapidly increasing mental health problem that requires more clinical attention. In this study, we aimed to explore the biobehavioral markers of NSSI in participants with mood disorders. Methods: A total of 45 participants with mood disorders (bipolar I, II, and major depressive disorder) were included in the study. Behavioral impulsivity was measured using the immediate memory task (IMT)/delayed memory task (DMT) and the go-no-go (GNG) tests. Plasma levels of tumor necrosis factor-α (TNF-α), interleukin 1 beta (IL-1 β), and interleukin 6 (IL-6) and resting-state quantitative electroencephalography (qEEG) were measured. Results: The NSSI group had shorter GNG reaction time (GNG-RT) and higher TNF-α levels compared to the non-NSSI group. TNF-α was positively correlated with frontal theta power. In addition, GNG-RT showed a significant positive association with frontal alpha activity. Conclusion: NSSI in mood disorders was associated with increased behavioral impulsivity and greater inflammation. Increased pro-inflammatory cytokines were associated with frontal theta power. Increased inflammation might change major neurotransmitter metabolism, which eventually affects frontal function and decreases response inhibition. Further studies to explore their causal relationship are warranted.

High-Gamma: A biological marker for suicide attempt in patients with depression

BACKGROUND

Quantitative EEG (qEEG) analysis can be used to evaluate brain correlates of human psychology in all aspects. As the gamma oscillations of qEEG rhythms are related to depression, and particularly to treatment resistance, they may also be related to suicidality.

AIM

The present study aimed to identify the neural correlates of suicidal ideation and suicide attempt in depression using qEEG, based on the hypothesis that gamma rhythm in patients with depression would be higher in patients with suicidal ideation and suicide attempt.

METHOD

qEEG were recorded in 533 participants (276 female). Groups were divided into the following: Non-suicidal (n = 218), Suicide Ideation (n = 211), Suicide Attempt (n = 74), and control (n = 30).

RESULTS

High-gamma power at the F4, Fz, C4, Cz, O2, F8, T5 and T6 regions was significantly higher in the Suicide Ideation than the other groups.

CONCLUSION

If confirmed by further studies, high-gamma rhythm has the potential to be used as a biomarker for screening suicidality.

Resting State Electroencephalography and Sports-Related Concussion: A Systematic Review

Sports-related concussion is associated with a range of short-term functional deficits that are commonly thought to recover within a two-week post-injury period for most, but certainly not all, persons. Resting state electroencephalography (rs-EEG) may prove to be an affordable, accessible, and sensitive method of assessing severity of brain injury and rate of recovery after a concussion. This article presents a systematic review of rs-EEG in sports-related concussion. A systematic review of articles published in the English language, up to June 2017, was retrieved via PsychINFO, Medline, Medline In Process, Embase, SportDiscus, CINAHL, and Cochrane Library, Reviews, and Trials. The following key words were used for database searches: electroencephalography, quantitative electroencephalography, qEEG, cranio-cerebral trauma, mild traumatic brain injury, mTBI, traumatic brain injury, brain concussion, concussion, brain damage, sport, athletic, and athlete. Observational, cohort, correlational, cross-sectional, and longitudinal studies were all included in the current review. Sixteen articles met inclusion criteria, which included data on 504 athletes and 367 controls. All 16 articles reported some abnormality in rs-EEG activity after a concussion; however, the cortical rhythms that were affected varied. Despite substantial methodological and analytical differences across the 16 studies, the current review suggests that rs-EEG may provide a reliable technique to identify persistent functional changes in athletes after a concussion. Because of the varied approaches, however, considerable work is needed to establish a systematic methodology to assess its efficacy as a marker of return-to-play.