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

Non-suicidal Self-injury and Quantified Electroencephalogram in Adolescents and Young Adults with Depression

Objective

: This study investigated the association between non-suicidal self-injury (NSSI) and quantified electroencephalogram (QEEG) in patients with depression. We aimed to identify clinical features of NSSI and differences in QEEG findings.

Methods

: This retrospective study used the medical records of 52 inpatients with major depressive episodes, aged from 15 to 30. The patients were categorized according to their history of NSSI. Their main diagnosis and sex were also considered. To evaluate clinical symptoms, self-reported scales were used. The absolute power and the Z-scores of various waves were included.

Results

: NSSI was associated with suicidal ideations (p = 0.001) and trauma history (p = 0.014). In the binary logistic regression analysis, the Z-score of absolute alpha power was higher on the FP2 node (p = 0.029), lower on the F4 node (p = 0.029) in the NSSI group. The absolute high beta power in the NSSI group was higher on the FP2 and the F3 node, but lower on the F7 and F8 node. Patients with NSSI showed higher Z-score of the absolute delta power at the FP2 node (p = 0.044). The absolute gamma power was higher on the FP2 (p = 0.012) and the F3 node (0.043), lower on the FP1 (p = 0.019) and the F7 node (0.018) in the NSSI group. The absolute high gamma power at the FP2 (p = 0.017) and F8 nodes (p = 0.045) were higher in the NSSI group.

Conclusion

: Patients with NSSI may have clinical features distinct from those of patients without NSSI. QEEG results have shown some differences, although it is less applicable due to some limitations.

Abnormal fractional amplitude of low-frequency fluctuations and regional homogeneity in major depressive disorder with non-suicidal self-injury

OBJECTIVE

We conducted this resting-state functional magnetic resonance imaging (rsfMRI) study to characterize changes in regional homogeneity (ReHo) or fractional amplitude of low-frequency fluctuations (fALFF) in young adult patients with major depressive disorder (MDD), with or without non-suicidal self-injury (NSSI).

METHODS

We recruited 54 MDD patients with NSSI (MDD/NSSI), 68 MDD patients without NSSI, which is referred to as simple MDD (sMDD), and 66 matched healthy controls (HCs). A combination of fALFF and ReHo analyses was conducted. The effects of NSSI on the brain and their relationship to clinical variables were examined in this study.

RESULTS

MDD/NSSI patients have decreased fALFF in the right superior frontal gyrus (SFG) and the right inferior parietal lobe (IPL), decreased ReHo in the right SFG and the right middle temporal gyrus (MTG) and the left middle occipital gyrus (MOG). fALFF and ReHo values of the right SFG are positively correlated. The ReHo values of the right SFG and the number of recent self-injuries are positively correlated; the fALFF values of the right SFG are negatively correlated with NSSI severity.

CONCLUSIONS

There is a difference in brain activity between MDD/NSSI and sMDD, which may serve as an important physiological marker to determine the risk of self-injury and suicide.

SIGNIFICANCE

Abnormal brain activity in patients with NSSI may provide new perspectives and significant implications on the severity of MDD patients and the prevention of self-injury and suicide.

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.

Functions of nonsuicidal self-injurious behavior in Russian patients with suicidal ideation

Introduction

Nonsuicidal self-injurious behavior (NSSI) is an important risk factor for future suicide attempts. Previous research has identified a number of motivations for engaging in NSSI. The aim of the present study was to translate the Inventory of Statements About Self-Injury (ISAS) into Russian and then to evaluate its psychometric properties in a sample of patients with non-psychotic mental disorders and suicidal ideation (SI). Other aims were to determine the prevalence of specific NSSI functions in this population and to assess the relationship between different NSSI functions and clinical and psychological parameters.

Participants and methods

The study was conducted at the largest center for non-psychotic mental disorders in Moscow. All admitted patients with both NSSI and SI completed the Russian version of the ISAS-II, underwent the Self-Injurious Thoughts and Behaviors Interview, and completed the Personality Inventory for DSM-5 and ICD-11 Brief Form Plus-Modified, the Beck Depression Inventory, and the State-Trait Anxiety Inventory.

Results

A total of 614 patients were included in the study. 543 (88.4%) patients were assigned female at birth with a mean age of 24.86 (7.86) years. Factor analysis supported a two-factor structure (Intrapersonal and Interpersonal) of the Russian version of the ISAS-II, but in contrast to the original study, the "Marking distress" function loaded more strongly on the Interpersonal factor. In people with non-psychotic mental disorders and SI, Interpersonal functions of NSSI are associated with more severe depressive symptoms (r = 0.34), 12 months history of NSSI (r = 0.30), higher number of NSSI methods (r = 0.41), likelihood of future NSSI (r = 0.35) and psychoticism (r = 0.32).

Conclusion

The Russian version of the ISAS-II is a valid and reliable instrument for assessing NSSI functions in a population at high risk for suicide attempts. Interpersonal functions are associated with a number of unpleasant clinical and psychological features.

EEG source functional connectivity in patients after a recent suicide attempt

OBJECTIVE

Electroencephalogram (EEG) based frequency measures within the alpha frequency range (AFR), including functional connectivity, show potential in assessing the underlying pathophysiology of depression and suicide-related outcomes. We investigated the association between AFR connectivity, suicidal thoughts and behaviors, and depression in a transdiagnostic sample of patients after a recent suicide attempt (SA).

METHODS

Lagged source-based measures of linear and nonlinear whole-brain connectivity within the standard AFR ([sAFR], 8-12 Hz) and the individually referenced AFR (iAFR) were applied to 70 15-minute resting-state EEGs from patients after a SA and 70 age- and gender-matched healthy controls (HC). Hypotheses were tested using network-based statistics and multiple regression models.

RESULTS

Results showed no significant differences between patients after a SA and HC in any of the assessed connectivity modalities. However, a subgroup analysis revealed significantly increased nonlinear connectivity within the sAFR for patients after a SA with a depressive disorder or episode ([DD], n = 53) compared to matched HC. Furthermore, a multiple regression model, including significant main effects for group and global nonlinear connectivity within the sAFR outperformed all other models in explaining variance in depressive symptom severity.

CONCLUSIONS

Our study further supports the importance of the AFR in pathomechanisms of suicidality and depression. The iAFR does not seem to improve validity of phase-based connectivity.

SIGNIFICANCE

Our results implicate distinct neurophysiological patterns in suicidal subgroups. Exploring the potential of these patterns for treatment stratification might advance targeted interventions for suicidal thoughts and behaviors.

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.

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.

College students’ screening early warning factors in identification of suicide risk

This study aimed to explore the main influencing factors of suicide risk among Chinese students and establish an early warning model to provide interventions for high-risk students. We conducted surveys of students in their first and third years from a cohort study at Jining Medical College. Logistic regression models were used to screen the early warning factors, and four machine learning models were used to establish early warning models. There were 8 factors related to suicide risk that were eventually obtained through screening, including age, having a rough father, and CES-D, OHQ, ASLEC-4, BFI-Neuroticism, BFI-Openness, and MMC-AF-C scores. A random forest model with SMOTE was adopted, and it verified that these 8 early warning signs, for suicide risk can effectively predict suicide risk within 2 years with an AUC score of 0.947. Among the factors, we constructed a model that indicated that different personality traits affected suicide risk by different paths. Moreover, the factors obtained by screening can be used to identify college students in the same year with a high risk of suicide, with an AUC score that reached 0.953. Based on this study, we suggested some interventions to prevent students going high suicide risk.