This study aimed to classify different emotional states by means of EEG-based functional connectivity patterns. Forty young participants viewed film clips that evoked the following emotional states: neutral, positive, or negative. Three connectivity indices, including correlation, coherence, and phase synchronization, were used to estimate brain functional connectivity in EEG signals. Following each film clip, participants were asked to report on their subjective affect. The results indicated that the EEG-based functional connectivity change was significantly different among emotional states. Furthermore, the connectivity pattern was detected by pattern classification analysis using Quadratic Discriminant Analysis. The results indicated that the classification rate was better than chance. We conclude that estimating EEG-based functional connectivity provides a useful tool for studying the relationship between brain activity and emotional states.

Background: Adverse childhood experiences (ACEs) are presumed to influence internalizing and externalizing behaviors that can significantly debilitate long-term biopsychological development in individuals. Psychological resilience has been shown to effectively mediate the relationship between ACEs and negative health outcomes since individuals with low levels of resilience may have difficulty with bouncing back from toxic exposure to ACEs. Thus, the present systematic review and meta-analysis was aimed toward synthesizing current knowledge of the relationship between ACEs and psychological resilience in youths. Methods: A combination of key words relevant to the present study was searched on the PubMed, EMBASE, Scopus, Cochrane, and Google Scholar databases. The results were restricted to English publications and human studies, with subjects ranging between the age of 0 to 35 years. Effect-size measures inclusive of pooled correlation coefficients for correlation analyses and pooled odds ratios for regression analyses, respectively, were calculated using random-effect models to determine the relationship between ACEs and psychological resilience. Results: The searches identified 85 potentially relevant studies. Among them, 76 were excluded due to limited access, irrelevant data, and the fact that the variables of interest were not explicitly measured or disclosed, leaving a final total of nine studies considered valid for the meta-analysis. Findings from correlational meta-analysis (n = 6) revealed a significantly negative association between ACEs and resilience (β = −0.120 [−0.196, −0.043]). The meta-analysis of the studies (n = 3) reporting dichotomous outcomes (ACE ≥ 1 vs. no ACE) indicated that subjects who experienced an ACE were 63% less likely to display high resilience, in comparison to subjects without such experiences. Conclusion: Our results support a negative association between ACEs and psychological resilience and highlight the multiple dimensions that constitute resilience in an ACE-exposure context. These findings may be particularly useful to policy makers and healthcare institutions in terms of helping them devise effective medical interventions and community outreach programs intended to develop resilience in youths, thus reducing health-risk behaviors and negative health outcomes.

To verify if error monitoring, involving detection and remedial actions, is affected by sleep deprivation. Event-related brain potentials (ERPs) and electroencephalogram spectrum during performance of Flanker task were obtained in a withinsubject, counter-balanced, repeated-measures design. Sleep deprivation and data collection were conducted in a laboratory setting. Sixteen young healthy adults (7 women, 18–23 years old) Performance and electroencephalogram data were collected after normal sleep and sleep deprivation. Compared to normal sleep, 1 night of sleep deprivation resulted in slower and more varied reaction times, more response errors and omissions, and impaired posterror adjustments to response accuracy. Concomitantly, 2 error-related ERPs, error-related negativity and Pe, showed reduced amplitude measurements after sleep deprivation. Conversely, conflict monitoring as expressed behaviorally and by the N2 component of the ERP was not attenuated by sleep deprivation. Ten of the sixteen participants maintained similar accuracy levels under both sleep conditions, although they still showed reduced error-related negativity and error positivity amplitude measurements and impaired error remedial actions for accuracy. Electroencephalogram spectral activity at beta and theta frequency bands was related to response correctness on subsequent trials but not related to that of preceding trials under both sleep conditions. One night of sleep deprivation impaired both the error detection and error remedial actions and highlighted the inability to avoid making errors again after erroneous responses were already made. The results showed that a vicious cycle occurred between performance deterioration and impairment of error-remedial mechanisms that inevitably led to making more successive errors.

Resilience is an innate human capacity that holds the key to uncovering why some people rebound after trauma and others never recover. Various theories have debated the mechanisms underlying resilience at the psychological level but have not yet incorporated neurocognitive concepts/findings. In this paper, we put forward the idea that cognitive flexibility moderates how well people adapt to adverse experiences, by shifting attention resources between cognition–emotion regulation and pain perception. We begin with a consensus on definitions and highlight the role of cognitive appraisals in mediating this process. Shared concepts among appraisal theories suggest that cognition–emotion, as well as pain perception, are cognitive mechanisms that underlie how people respond to adversity. Frontal brain circuitry sub-serves control of cognition and emotion, connecting the experience of physical pain. This suggests a substantial overlap between these phenomena. Empirical studies from brain imaging support this notion. We end with a discussion of how the role of the frontal brain network in regulating human resilience, including how the frontal brain network interacts with cognition–emotion–pain perception, can account for cognitive theories and why cognitive flexibilities’ role in these processes can create practical applications, analogous to the resilience process, for the recovery of neural plasticity.

Psychosocial factors, including life satisfaction, resilience, and social support, have been proposed to influence depressive symptom severity in adults because the age of onset of depressive disorders, i.e. adolescence to early adulthood, is associated with various impairments in psychosocial functioning. In this study, a psychosocial model was constructed to verify these relationships to prevent depression. For this study, 370 participants were recruited from the community via poster or online advertisements. They completed several questionnaires to assess depressive symptom severity: the Connor-Davidson Resilience Scale (CD-RISC), Satisfaction with Life Scale (SwLS), Peace of Mind (PoM) scale, Social Support Questionnaire (SSQ), and Beck Depression Inventory (BDI-II). A negative association was found between depressive symptom severity and all other variables, including PoM and CD-RISC scores, life satisfaction, and social support. Such factors can be considered protective against increased depressive symptom severity. In addition, indirect effects of PoM and resilience on the negative association between SwLS scores and depressive symptom severity were observed. Moreover, social support was found to mediate the correlation between PoM and resilience, implying that social support mediates the relationship between state of mind and resilience. The psychosocial model suggested that depressive symptom severity is influenced by internal factors (an individual’s state of mind, subjective view of events and their life) and external factors (including social support).