Predisposing Variations in Fear-Related Brain Networks Prospectively Predict Fearful Feelings during the 2019 Coronavirus (COVID-19) Pandemic

Effectiveness of repetitive transcranial magnetic stimulation for insomnia disorder on fear memory extinction: study protocol for a randomised controlled trial

BACKGROUND

Fear memory extinction is closely related to insomnia. Repetitive transcranial magnetic stimulation (rTMS) is safe and effective for treating insomnia disorder (ID), and it has been shown to be an efficient method for modulating fear extinction. However, whether rTMS can improve fear extinction memory in ID patients remains to be studied. In this study, we specifically aim to (1) show that 1 Hz rTMS stimulation could improve fear extinction memory in ID patients and (2) examine whether changes in sleep mediate this impact.

METHODS AND DESIGN

We propose a parallel group randomised controlled trial of 62 ID participants who meet the inclusion criteria. Participants will be assigned to a real rTMS group or a sham rTMS group. The allocation ratio will be 1:1, with 31 subjects in each group. Interventions will be administered five times per week over a 4-week period. The assessments will take place at baseline (week 0), post-intervention (week 4), and 8-week follow-up (week 8). The primary outcome measure of this study will be the mean change in the Pittsburgh Sleep Quality Index (PSQI) scores from baseline to post-intervention at week 4. The secondary outcome measures include the mean change in skin conductance response (SCR), fear expectation during fear extinction, Insomnia Severity Index (ISI), Zung Self-Rating Anxiety Scale (SAS), and the Zung Self-Rating Depression Scale (SDS).

DISCUSSION

This study will be the first examination of the impact of rTMS on fear memory extinction in ID patients.

TRIAL REGISTRATION

Chinese Clinical Trials Register ChiCTR2300076097. Registered on 25 September 2021.

Transdiagnostic Fear and Anxiety: Prospective Prediction Using the No-Threat, Predictable Threat, and Unpredictable Threat Task

Background

Fear and anxiety are distinct dimensions of psychopathology that may be characterized by differences in dimensional threat reactivity. Heightened response to predictable threat is hypothesized to underlie fear symptomatology, whereas increased response to unpredictable threat may underlie anxiety. Despite widespread acceptance of this model, these purported associations have rarely been tested, and the prognostic value of predictable and unpredictable threat responding is unclear. Here we examined multilevel indicators of predictable and unpredictable threat response as cross-sectional correlates and prospective predictors of transdiagnostic fear and anxiety.

Methods

Fifty-two individuals with varying levels of internalizing psychopathology (31 female) performed the no-threat, predictable threat, and unpredictable threat task. Transdiagnostic fear and anxiety were assessed at baseline (time 1) and approximately 1.5 years later (time 2). We used event-related potential, the stimulus-preceding negativity, as a measure of threat anticipation and startle eyeblink as a measure of defensive reactivity during the no-threat, predictable threat, and unpredictable threat task. These probes were assessed as cross-sectional correlates and prospective predictors of fear and anxiety.

Results

Participants with larger time 1 stimulus-preceding negativities to predictable threat were characterized by greater time 1 fear. Larger time 1 stimulus-preceding negativities to unpredictable threat were associated with greater increases in time 2 anxiety. Heightened time 1 startle to predictable threat predicted larger increases in time 2 fear.

Conclusions

Results validate predictable and unpredictable threat responding as dimensional correlates of transdiagnostic fear versus anxiety and suggest that psychophysiological measures of predictable and unpredictable threat response hold promise as prospective predictors of trajectories of fear and anxiety.

Risk of insomnia during COVID-19: effects of depression and brain functional connectivity

Normal sleepers may be at risk for insomnia during COVID-19. Identifying psychological factors and neural markers that predict their insomnia risk, as well as investigating possible courses of insomnia development, could lead to more precise targeted interventions for insomnia during similar public health emergencies. Insomnia severity index of 306 participants before and during COVID-19 were employed to determine the development of insomnia, while pre-COVID-19 psychometric and resting-state fMRI data were used to explore corresponding psychological and neural markers of insomnia development. Normal sleepers as a group reported a significant increase in insomnia symptoms after COVID-19 outbreak (F = 4.618, P = 0.0102, df = 2, 609.9). Depression was found to significantly contribute to worse insomnia (β = 0.066, P = 0.024). Subsequent analysis found that functional connectivity between the precentral gyrus and middle/inferior temporal gyrus mediated the association between pre-COVID-19 depression and insomnia symptoms during COVID-19. Cluster analysis identified that postoutbreak insomnia symptoms followed 3 courses (lessened, slightly worsened, and developed into mild insomnia), and pre-COVID-19 depression symptoms and functional connectivities predicted these courses. Timely identification and treatment of at-risk individuals may help avoid the development of insomnia in the face of future health-care emergencies, such as those arising from COVID-19 variants.

Functional Brain Connectivity Prior to the COVID-19 Outbreak Moderates the Effects of Coping and Perceived Stress on Mental Health Changes: A First Year of COVID-19 Pandemic Follow-up Study

BACKGROUND

The COVID-19 pandemic provides a unique opportunity to investigate the psychological impact of a global major adverse situation. Our aim was to examine, in a longitudinal prospective study, the demographic, psychological, and neurobiological factors associated with interindividual differences in resilience to the mental health impact of the pandemic.

METHODS

We included 2023 healthy participants (age: 54.32 ± 7.18 years, 65.69% female) from the Barcelona Brain Health Initiative cohort. A linear mixed model was used to characterize the change in anxiety and depression symptoms based on data collected both pre-pandemic and during the pandemic. During the pandemic, psychological variables assessing individual differences in perceived stress and coping strategies were obtained. In addition, in a subsample (n = 433, age 53.02 ± 7.04 years, 46.88% female) with pre-pandemic resting-state functional magnetic resonance imaging available, the system segregation of networks was calculated. Multivariate linear models were fitted to test associations between COVID-19-related changes in mental health and demographics, psychological features, and brain network status.

RESULTS

The whole sample showed a general increase in anxiety and depressive symptoms after the pandemic onset, and both age and sex were independent predictors. Coping strategies attenuated the impact of perceived stress on mental health. The system segregation of the frontoparietal control and default mode networks were found to modulate the impact of perceived stress on mental health.

CONCLUSIONS

Preventive strategies targeting the promotion of mental health at the individual level during similar adverse events in the future should consider intervening on sociodemographic and psychological factors as well as their interplay with neurobiological substrates.

The Relation Between the Power of Prefrontal Gamma in Rest-state EEG Under Normal Sleep and Reactive Aggression Behaviour After Sleep Deprivation

Whether sleep deprivation affects aggressive behaviour is still under debate. The present study examined the influence of individual differences in reactive aggressive behaviour after sleep deprivation and preliminarily explored an electrophysiological marker to identify individuals with more aggressive behaviour after sleep deprivation. Thirty participants performed the Taylor Aggression Paradigm task under two sleep conditions: normal sleep (NS, one night of regular sleep) and total sleep deprivation (SD, 30 h of wakefulness), and 5-minute resting-state electroencephalogram (EEG) acquisition was completed under the NS condition. The results found that although sleep deprivation did not have significant effects on aggressive behaviour in the overall analysis, the participants can be classified as an increased group (n = 16) and a no-increased group (n = 14) by different changes in the two sleep conditions (SD-NS). In addition, prefrontal gamma (γ) power was significantly lower in the increased group than in the no-increased group, which may reflect the difference in ability on inhibition. Furthermore, more critical is that γ power was significantly negatively correlated with change in the reactive aggressive behaviour. These results indicate that the effect of SD on reactive aggression varies between individuals, and prefrontal γ power may be an effective electrophysiological marker for identifying people at risk of aggressive behaviour after SD.

A Predictive Model of Pandemic Disaster Fear Caused by Coronavirus (COVID-19): Implications for Decision-Makers

This paper presents quantitative research results regarding a predictive model of pandemic disaster fear caused by the coronavirus disease (COVİD-19). The aim of this paper was to establish the level and impact of certain demographic and socioeconomic characteristics on pandemic disaster fear caused by the coronavirus (COVID-19). The research was conducted using a questionnaire that was provided and then collected online for 1226 respondents during May 2021. A closed, five-point Likert scale was used to create the structured questionnaire. The first section of the questionnaire included research questions about the participants' socioeconomic and demographic characteristics, while the second section included issue questions about fear caused by COVID-19. The results of multivariate regression analyses showed the most important predictor for fear of COVID-19 to be gender, followed by age and education level. Furthermore, the results of t-tests showed statistically significant differences between men and women in terms of different aspects of pandemic disaster fear caused by the coronavirus disease. Our results have several significant public health implications. Women who were more educated and knowledgeable, married, and older, reported a greater fear of the outbreak at various levels. Decision-makers can use these findings to identify better strategic opportunities for pandemic disaster risk management.