Separating EEG correlates of stress: Cognitive effort, time pressure, and social-evaluative threat

Anandamide Attenuates Neurobehavioral Deficits and EEG Irregularities in the Chronic Sleep Deprivation Rats: The Role of Oxidative Stress and Neuroinflammation

Sleep deprivation increases stress, anxiety, and depression by altering the endocannabinoid system's function. In the present study, we aimed to investigate the anti-anxiety and anti-depressant effects of the endocannabinoid anandamide (AEA) in the chronic sleep deprivation (SD) model in rats. Adult male Wistar rats (200-250 g) were randomly divided into three groups: control + vehicle (Control), chronic sleep deprivation + vehicle (SD), and chronic sleep deprivation + 20 mg/kg AEA (SD + A). The rats were kept in a sleep deprivation device for 18 h (7 to 1 a.m.) daily for 21 days. Open-field (OFT), elevated plus maze, and forced swimming tests (FST) were used to assess anxiety and depression-like behavior. As well as the cortical EEG, CB1R mRNA expression, TNF-α, IL-6, IL-4 levels, and antioxidant activity in the brain were examined following SD induction. AEA administration significantly increased the time spent (p < 0.01), the distance traveled in the central zone (p < 0.001), and the number of climbing (p < 0.05) in the OFT; it also increased the duration and number of entries into the open arms (p < 0.01 and p < 0.05 respectively), and did not reduce immobility time in the FST (p > 0.05), AEA increased CB1R mRNA expression in the anterior and medial parts of the brain (p < 0.01), and IL-4 levels (p < 0.05). AEA also reduced IL-6 and TNF-α (p < 0.05) and modulated cortical EEG. AEA induced anxiolytic-like effects but not anti-depressant effects in the SD model in rats by modulating CB1R mRNA expression, cortical EEG, and inflammatory response.

The Role of Electroencephalogram-Assessed Bandwidth Power in Response to Hypnotic Analgesia

Research supports the efficacy of therapeutic hypnosis for reducing acute and chronic pain. However, little is known about the mechanisms underlying these effects. This paper provides a review of the evidence regarding the role that electroencephalogram-assessed bandwidth power has in identifying who might benefit the most from hypnotic analgesia and how these effects occur. Findings are discussed in terms of the slow wave hypothesis, which posits that brain activity in slower bandwidths (e.g., theta and alpha) can facilitate hypnosis responsivity. Although the extant research is limited by small sample sizes, the findings from this research are generally consistent with the slow wave hypothesis. More research, including and especially studies with larger sample sizes, is needed to confirm these preliminary positive findings.

The impact of internal-generated contextual clues on EFL vocabulary learning: insights from EEG

With the popularity of learning vocabulary online among English as a Foreign Language (EFL) learners today, educators and researchers have been considering ways to enhance the effectiveness of this approach. Prior research has underscored the significance of contextual clues in vocabulary acquisition. However, few studies have compared the context provided by instructional materials and that generated by learners themselves. Hence, this present study sought to explore the impact of internal-generated contextual clues in comparison to those provided by instructional materials on EFL learners' online vocabulary acquisition. A total of 26 university students were enrolled and underwent electroencephalography (EEG). Based on a within-subjects design, all participants learned two groups of vocabulary words through a series of video clips under two conditions: one where the contexts were externally provided and the other where participants themselves generated the contexts. In this regard, participants were tasked with either viewing contextual clues presented on the screen or creating their own contextual clues for word comprehension. EEG signals were recorded during the learning process to explore neural activities, and post-tests were conducted to assess learning performance after each vocabulary learning session. Our behavioral results indicated that comprehending words with internal-generated contextual clues resulted in superior learning performance compared to using context provided by instructional materials. Furthermore, EEG data revealed that learners expended greater cognitive resources and mental effort in semantically integrating the meaning of words when they self-created contextual clues, as evidenced by stronger alpha and beta-band oscillations. Moreover, the stronger alpha-band oscillations and lower inter-subject correlation (ISC) among learners suggested that the generative task of creating context enhanced their top-down attentional control mechanisms and selective visual processing when learning vocabulary from videos. These findings underscored the positive effects of internal-generated contextual clues, indicating that instructors should encourage learners to construct their own contexts in online EFL vocabulary instruction rather than providing pre-defined contexts. Future research should aim to explore the limits and conditions of employing these two types of contextual clues in online EFL vocabulary learning. This could be achieved by manipulating the quality and understandability of contexts and considering learners' language proficiency levels.

Who Benefits the Most From Different Psychological Chronic Pain Treatments? An Exploratory Analysis of Treatment Moderators

Different psychological chronic pain treatments benefit some individuals more than others. Understanding the factors that are associated with treatment response-especially when those factors differ between treatments-may inform more effective patient-treatment matching. This study aimed to identify variables that moderate treatment response to 4 psychological pain interventions in a sample of adults with low back pain or chronic pain associated with multiple sclerosis, spinal cord injury, acquired amputation, or muscular dystrophy (N = 173). The current study presents the results from secondary exploratory analyses using data from a randomized controlled clinical trial which compared the effects of 4 sessions of cognitive therapy (CT), hypnosis focused on pain reduction (HYP), hypnosis focused on changing pain-related cognitions and beliefs (HYP-CT), and a pain education control condition (ED). The analyses tested the effects of 7 potential treatment moderators. Measures of primary (pain intensity) and secondary (pain interference, depression severity) outcome domains were administered before and after the pain treatments, and potential moderators (catastrophizing, hypnotizability, and electroencephalogram (EEG)-assessed oscillation power across five bandwidths) were assessed at pre-treatment. Moderator effects were tested fitting regression analyses to pre- to post-treatment changes in the three outcome variables. The study findings, while preliminary, support the premise that pre-treatment measures of hypnotizability and EEG brain activity predict who is more (or less) likely to respond to different psychological pain treatments. If additional research replicates the findings, it may be possible to better match patients to their more individually suitable treatment, ultimately improving pain treatment outcomes. PERSPECTIVE: Pre-treatment measures of hypnotizability and EEG-assessed brain activity predicted who was more (or less) likely to respond to different psychological pain treatments. If these findings are replicated in future studies, they could inform the development of patient-treatment matching algorithms.

Effects of acute psychosocial stress on source level EEG power and functional connectivity measures

The usage of EEG to uncover the influence of psychosocial stressors (PSSs) on neural activity has gained significant attention throughout recent years, but the results are often troubled by confounding stressor types. To investigate the effect of PSSs alone on neural activity, we employed a paradigm where participants are exposed to negative peer comparison as PSS, while other possible stressors are kept constant, and compared this with a condition where participants received neutral feedback. We analyzed commonly used sensor level EEG indices (frontal theta, alpha, and beta power) and further investigated whether source level power and functional connectivity (i.e., the temporal dependence between spatially seperated brain regions) measures, which have to our knowledge not yet been used, are more sensitive to PSSs than sensor level-derived EEG measures. Our results show that on sensor level, no significant frontal power changes are present (all p's > 0.16), indicating that sensor level frontal power measures are not sensitive enough to be affected by only PSSs. On source level, we find increased alpha power (indicative of decreased cortical activity) in the left- and right precuneus and right posterior cingulate cortex (all p's < 0.03) and increased functional connectivity between the left- and right precuneus (p < 0.001), indicating that acute, trial based PSSs lead to decreased precuneus/PCC activity, and possibly indicates a temporary disruption in the self-referential neural processes of an individual.

Capacity of Autonomous Sensory Meridian Response on the Reduction of Mental Stress

In a social environment, various types of stress can be overwhelming. Humans frequently encounter these stressful situations in social life. Stress is divided into physical stress and mental stress; the latter is induced by heavy mental workloads and has become a huge social problem, leading to mental disorders and possibly suicide in the worst scenario. Investigations into monitoring mental stress and reducing stressful conditions are, therefore, important for its prevention. In the present study, we focused on autonomous sensory meridian response (ASMR) sound, which is known to improve the human mental condition through its comforting and relaxing effects. We investigated the effect of ASMR on the mental workload induced by mental tasks by the evaluation of EEG activation patterns in normal subjects. Our results showed a significant decrease in alpha-band activity and a significant increase in gamma (high beta)-band activity under the induction of mental workload by mental tasks compared to the resting condition. When applying ASMR sound, alpha- and gamma-band activity under the induction of mental workload by mental tasks was restored to the level of the resting condition. In conclusion, these results indicate that ASMR sound reduces the mental stress induced by mental workload.

EEG Evaluation of Stress Exposure on Healthcare Workers During COVID-19 Emergency: Not Just an Impression

Psychological distress among healthcare professionals, although already a common condition, was exacerbated by the COVID-19 pandemic. This effect has been generally self-reported or assessed through questionnaires. We aimed to identify potential abnormalities in the electrical activity of the brain of healthcare workers, operating in different roles during the pandemic. Cortical activity, cognitive performances, sleep, and burnout were evaluated two times in 20 COVID-19 frontline operators (FLCO, median age 29.5 years) and 20 operators who worked in COVID-19-free units (CFO, median 32 years): immediately after the outbreak of the pandemic (first session) and almost 6 months later (second session). FLCO showed higher theta relative power over the entire scalp (FLCO = 19.4%; CFO = 13.9%; p = 0.04) and lower peak alpha frequency of electrodes F7 (FLCO = 10.4 Hz; CFO = 10.87 Hz; p = 0.017) and F8 (FLCO = 10.47 Hz; CFO = 10.87 Hz; p = 0.017) in the first session. FLCO parietal interhemispheric coherence of theta (FLCO I = 0.607; FLCO II = 0.478; p = 0.025) and alpha (FLCO I = 0.578; FLCO II = 0.478; p = 0.007) rhythms decreased over time. FLCO also showed lower scores in the global cognitive assessment test (FLCO = 22.72 points; CFO = 25.56; p = 0.006) during the first session. The quantitative evaluation of the cortical activity might therefore reveal early signs of changes secondary to stress exposure in healthcare professionals, suggesting the implementation of measures to prevent serious social and professional consequences.

Investigating How Auditory and Visual Stimuli Promote Recovery After Stress With Potential Applications for Workplace Stress and Burnout: Protocol for a Randomized Trial

Background

Work-related stress is one of the top sources of stress amongst working adults. Relaxation rooms are one organizational strategy being used to reduce workplace stress. Amongst healthcare workers, relaxation rooms have been shown to improve perceived stress levels after 15 min of use. However, few studies have examined physiological and cognitive changes after stress, which may inform why relaxation rooms reduce perceived stress. Understanding the biological mechanisms governing why perceived stress improves when using a relaxation room could lead to more effective strategies to address workplace stress.

Objective

The purpose of this research study is to understand how physiological measures, cognitive performance, and perceived stress change after acute stress and whether certain sensory features of a relaxation room are more effective at promoting recovery from stress.

Methods

80 healthy adults will perform a stress induction task (Trier Social Stress Test, TSST) to evaluate how physiological and cognitive responses after stress are affected by sensory features of a relaxation room. After the stress induction task, participants will recover for 40 min in a MindBreaks™ relaxation room containing auditory and visual stimuli designed to promote relaxation. Participants will be randomized into four cohorts to experience auditory and visual stimuli; auditory stimuli; visual stimuli; or no stimuli in the room. Measures of heart rate and neural activity will be continuously monitored using wearable devices. Participants will perform working memory assessments and rate their perceived stress levels throughout the experiment. These measures will be compared before and after the stress induction task to determine how different sensory stimuli affect the rate at which individuals recover.

Results

Recruitment started in December 2021 and will continue until December 2022 or until enrollment is completed. Final data collection and subsequent analysis are anticipated by December 2022. We expect all trial results will be available by early 2023.

Discussion

Findings will provide data and information about which sensory features of a relaxation room are most effective at promoting recovery after acute stress. This information will be useful in determining how these features might be effective at creating individualized and organizational strategies for mitigating the effects of workplace stress.

Stress Classification Using Brain Signals Based on LSTM Network

The early diagnosis of stress symptoms is essential for preventing various mental disorder such as depression. Electroencephalography (EEG) signals are frequently employed in stress detection research and are both inexpensive and noninvasive modality. This paper proposes a stress classification system by utilizing an EEG signal. EEG signals from thirty-five volunteers were analysed which were acquired using four EEG sensors using a commercially available 4-electrode Muse EEG headband. Four movie clips were chosen as stress elicitation material. Two clips were selected to induce stress as it contains emotionally inductive scenes. The other two clips were chosen that do not induce stress as it has many comedy scenes. The recorded signals were then used to build the stress classification model. We compared the Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) for classifying stress and nonstress group. The maximum classification accuracy of 93.17% was achieved using two-layer LSTM architecture.

The modulation of salience and central executive networks by acute stress in healthy males: An EEG microstates study

EEG microstate analysis involves the examination of topographies of the scalp potential fields to indicate the temporal dynamics of resting-state networks on a millisecond time scale, through which we can investigate the subsecond brain dynamics of stress in individuals. The present study implemented the EEG microstate method to explore the temporal dynamic changes of the large-scale brain networks induced by acute stress. The participants (n = 51) were randomly exposed to a stress condition (n = 25) (induced by Trier Social Stress Test, TSST) or a control condition (n = 26). Two 4-min blocks of resting EEG data were recorded before and after the stress/control test to reflect the stress effect on temporal dynamics of EEG microstates. The results showed that the stress group had larger occurrences and coverage of microstate class C during the post-test session than during the pre-test session. This pattern was reversed in the control group. Further, the microstate class C showed positive correlations with negative affect and perceived stress levels following acute stress. The transition probability between the microstates C and D was larger during the post-test session than during the pre-test session in the stress group, but not different in the control group. In addition, the microstate pairs C and D were positively correlated with negative affect and perceived stress levels. The proportion and sequence of EEG microstates class C and D reflected deviations of salience and executive functions following acute stress. We further proposed that the coordination between salience and executive functions was promoted by acute stress.

A Review on Mental Stress Assessment Methods Using EEG Signals

Mental stress is one of the serious factors that lead to many health problems. Scientists and physicians have developed various tools to assess the level of mental stress in its early stages. Several neuroimaging tools have been proposed in the literature to assess mental stress in the workplace. Electroencephalogram (EEG) signal is one important candidate because it contains rich information about mental states and condition. In this paper, we review the existing EEG signal analysis methods on the assessment of mental stress. The review highlights the critical differences between the research findings and argues that variations of the data analysis methods contribute to several contradictory results. The variations in results could be due to various factors including lack of standardized protocol, the brain region of interest, stressor type, experiment duration, proper EEG processing, feature extraction mechanism, and type of classifier. Therefore, the significant part related to mental stress recognition is choosing the most appropriate features. In particular, a complex and diverse range of EEG features, including time-varying, functional, and dynamic brain connections, requires integration of various methods to understand their associations with mental stress. Accordingly, the review suggests fusing the cortical activations with the connectivity network measures and deep learning approaches to improve the accuracy of mental stress level assessment.