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

Abstract

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.

Profile of childhood trauma subtypes associated with self-injurious thoughts and behaviors.

“…This further supported a distinction between people with NSSI, SI, SA, or co-occurrence of STBs. While previous studies already found a distinction between people with SA only and both NSSI + SI in terms of brain functioning (Iznak et al, 2021), cognitive styles (Wolff et al, 2013), and psychiatric prognosis (Bjureberg et al, 2022), our results further indicated a difference between the developmental risks and potential mechanisms underlying all these complex profiles of STBs.…”

“…Moreover, Victor and Klonsky (2014) found that adolescents with higher frequency and numbers of NSSI methods also show more violent manners of SAs in adolescents, indicating the importance of identifying risk factors predicting both individual STBs and the co-occurrence of multiple STBs. In line with this, several studies have found differences between people with SA and people with NSSI + SA in brain functioning (Iznak et al, 2021), cognitive styles (Wolff et al, 2013), and psychiatric prognosis (Bjureberg et al, 2022). This indicated more complex dynamic interactions between single STBs and the co-occurrence of STBs.…”

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

“…The reason false alarms exist is that the data collected could not give a full view of high-suicide-risk students. False alarms remind us to include more aim indicators in data collection, such as impulsivity, near-infrared spectroscopy (NIRS), electroencephalogram (EEG), and some genetic indices ( Lutz et al, 2017 ; Hirose et al, 2018 ; Costanza et al, 2021 ; Iznak et al, 2021 ; Koenig et al, 2021 ). Lifetime SA was significantly associated with both higher impulsivity and higher aggression ( Costanza et al, 2021 ).…”

Feedback Processing as it Relates to Suicidal Ideation and Behavior Using a Time-Frequency Approach

“…For alpha, the activity appears to begin approximately 500 ms post-feedback. Given previous work (Iznak et al, 2021) and current findings, alpha activation was evaluated at POZ. The alpha PCA accounted for 64.89% of the variance.…”

“…Even fewer studies have examined high-frequency (HF) measures, such as alpha, beta-1, beta-2, and gamma related to suicide and/or feedback processing. One study measured an increase in alpha spectral power in the parieto-occipital area for those with suicidal attempts compared to those with non-suicidal self-injuries (Iznak et al, 2021). In another, non-suicidal depressed patients displayed decreased beta and low gamma activity in the frontal regions (Benschop et al, 2019).…”