Cyberbullying is an increasingly problematic psychosocial health risk, particularly in youth. Electroencephalography (EEG) is commonly utilized to investigate the potential effects of social behaviors on brain activity. Hence, the current paper provides a systematic review of EEG-related studies that have addressed cyberbullying-like behaviors. Initial searches from 4 databases returned 1150 unique articles, which were screened according to PRISMA guidelines. The 29 articles remaining after full text screening investigated online social exclusion, a method of cyberbullying. Across these studies, there was evidence of links between social exclusion and abnormalities in a range of event related potential (ERP) and EEG measures representative of deviance detection (“N2” ERP), response to detection (“P3” ERP), emotional attention (“late slow wave” ERP) and emotional regulation (“frontal theta” EEG). Meta-analysis demonstrated increased P3 and late slow wave amplitudes in response to social exclusion, as well as increases in frontal-medial theta power, particularly in child and adolescent samples. However, many studies had small sample sizes, and lacked longitudinal insight into the effects of recurrent ostracism on brain function. Future research should explore the effects of a broader range of cyberbullying behaviors on psychophysiology longitudinally, particularly in vulnerable populations such as adolescents.
Background
Ketamine has considerable therapeutic potential in alleviating major depressive disorder (MDD) and chronic suicidality. However, the clinical diagnosis of neuropsychiatric disorders requires more robust diagnostic criteria. Electroencephalography (EEG) has shown promise in classifying depressive and suicidal patients from healthy individuals. The present study aimed to identify changes in the spectral properties of EEG in patients with MDD and chronic suicidality after completing the 6-week Oral Ketamine Trial on Suicidality (OKTOS) with follow-up occurring 4 weeks after final ketamine treatment and determine associations between EEG spectral output and clinical symptoms.
Methods
Participants (N=25) had 4-minutes eyes closed resting state EEG recorded at frontal, temporal, centro-parietal, and occipital regions. Spectral analysis was performed with Welch’s power spectrum density method, and the power of four distinct frequency bands was analysed – theta, alpha, low-beta, and high-beta. Correlation analyses between changes in clinical symptoms and spectral power were done using Spearman’s ranked correlation.
Results
Between pre- and post-treatment, only centro-parietal alpha power decreased. Between post-treatment and follow-up, centro-parietal alpha increased again in addition to increases in temporal alpha, centro-parietal and temporal theta, occipital low-beta, and decreases in occipital theta and temporal low-beta. Additionally, the decrease of occipital theta positively correlated with clinical subscales for depression and stress.
Conclusions
EEG spectral analysis revealed significant changes in theta, alpha, and low-beta frequency bands. Alpha band showed initial changes after treatment; however, this trended back towards baseline levels after the treatment cessation. In contrast, theta and low-beta showed significant power changes only after the treatment had ended.
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