Laterality of an EEG anxiety disorder biomarker largely follows handedness

Effectiveness of Neurofeedback-Assisted and Conventional 6-Week Web-Based Mindfulness Interventions on Mental Health of Chinese Nursing Students: Randomized Controlled Trial

BACKGROUND

Nursing students experience disproportionately high rates of mental health challenges, underscoring the urgent need for innovative, scalable interventions. Web-based mindfulness programs, and more recently, neurofeedback-enhanced approaches, present potentially promising avenues for addressing this critical issue.

OBJECTIVE

This study aimed to explore the effectiveness of the neurofeedback-assisted online mindfulness intervention (NAOM) and the conventional online mindfulness intervention (COM) in reducing mental health symptoms among Chinese nursing students.

METHODS

A 3-armed randomized controlled trial was conducted among 147 nursing students in Beijing, China, using a 6-week web-based mindfulness program. Participants received NAOM, COM, or general mental health education across 6 weeks. Electroencephalogram and validated tools such as the Patient Health Questionnaire and the Generalized Anxiety Disorder Questionnaire were used to primarily assess symptoms of depression and anxiety at baseline, immediately after the intervention, and at 1 and 3 months after the intervention. Generalized estimating equations were used to evaluate the effects of intervention and time.

RESULTS

A total of 155 participants enrolled in the study, and 147 finished all assessments. Significant reductions in the symptoms of depression, anxiety, and fatigue were observed in the NAOM (mean difference [MD]=-3.330, Cohen d=0.926, P<.001; MD=-3.468, Cohen d=1.091, P<.001; MD=-2.620, Cohen d=0.743, P<.001, respectively) and the COM (MD=-1.875, Cohen d=0.490, P=.03; MD=-1.750, Cohen d=0.486, P=.02; MD=-2.229, Cohen d=0.629, P=.01, respectively) groups compared with the control group at postintervention assessment. Moreover, the NAOM group showed significantly better effects than the COM group in alleviating depressive symptoms (MD=-1.455; Cohen d=0.492; P=.04) and anxiety symptoms (MD=-1.718; Cohen d=0.670; P=.04) and improving the level of mindfulness (MD=-3.765; Cohen d=1.245; P<.001) at the postintervention assessment. However, no significant difference except for the anxiety symptoms was observed across the 3 groups at the 1- and 3-month follow-ups.

CONCLUSIONS

This 6-week web-based mindfulness intervention, both conventional and neurofeedback-assisted, effectively alleviated mental health problems in the short term among nursing students. The addition of neurofeedback demonstrated greater short-term benefits; however, but these effects were not sustained over the long term. Future research should focus on long-term interventions using a more robust methodological approach.

TRIAL REGISTRATION

Chinese Clinical Trial Registry (ChiCTR) ChiCTR2400080314; https://www.chictr.org.cn/bin/project/edit?pid=211845.

Frontal localisation of a theory-based anxiety disorder biomarker - Goal conflict specific rhythmicity

PURPOSE

Anxiety disorders are a major global issue. Diagnosis via symptoms, not biological causes, delivers poor treatment outcomes. Our frontal EEG biomarker, Goal Conflict Specific Rhythmicity (GCSR; 4-12 Hz), developed from our long-standing detailed neuropsychological theory of anxiety processes, is reduced by all chemical types of selective anxiolytic and is high in cases across a range of currently diagnosed anxiety disorders.

METHODS

We assessed frontal sources of GCSR, recording scalp EEG at either low resolution (Experiment 1, 32 channels, University of Otago, ♀:33, ♂:16) or high resolution (Experiment 2, 128 channels, University of Auckland, ♀:10, ♂:8) in healthy participants performing a Stop Signal Task to generate GCSR as previously.

PRINCIPAL RESULTS

sLORETA demonstrated GCSR sources consistently in the right inferior frontal gyrus and, more strongly but less consistently, medial frontal gyrus. Variation was consistent with that of stopping in the same Stop Signal Task, depending on task demands.

MAJOR CONCLUSIONS

The sources of GCSR are consistent with our theory that hippocampal output receives goal information, detects conflict, and returns a negative biasing signal to the areas encoding goals in the current task. They match the variation in the control of stopping when response urgency changes. GCSR appears to index a biological type of anxiety unlike any current diagnosis and should help improve accuracy of diagnosis - anchored to actions of selective anxiolytic drugs. This task-related frontal "theta" rhythmicity provides proof-of-concept for further development of our theory of the neuropsychology of anxiety in direct human tests.

Is lack of goal-conflict-specific rhythmicity a biomarker for treatment resistance in generalised anxiety but not social anxiety or major depression?

BACKGROUND

Anxiety and depression cause major detriment to the patient, family, and society - particularly in treatment-resistant (TR) cases, which are highly prevalent. TR prevalence may be due to current diagnoses being based not on biological measures but on symptom lists that suffer from clinical subjectivity, variation in symptom presentation, and comorbidity.

AIMS

Goal-conflict-specific rhythmicity (GCSR) measured using the Stop-Signal Task (SST) may provide the first neural biomarker for an anxiety process and disorder. This GCSR has been validated with selective drugs for anxiety. So, we proposed that GCSR could differ between TR and non-TR individuals and do so differently between those diagnoses normally sensitive to selective anxiolytics and those not.

METHODS

We recorded electroencephalograms (EEG) from 20 TR participants (4 GAD, 5 SAD and 11 MDD) and 24 non-TR participants (4 GAD, 5 SAD and 15 Comorbid GAD/MDD (GMD)) while they performed the SST.

RESULTS

There was significant positive GCSR in all groups except the GAD-TR group. GAD-TR lacked GCSR in the low-frequency range. However, TR had little effect in SAD or MDD/GMD populations with apparent increases not decreases.

CONCLUSIONS

Overall, these results suggest that GAD may occur in two forms: one resulting from excessive GCSR and so being drug sensitive, and the other resulting from some other mechanism and so being TR. In SAD and MDD groups, heightened GCSR could be a consequence rather than the cause, driven by mechanisms that are normally more sensitive to non-selective panicolytic antidepressants.

Brain optimization with additional study time: potential brain differences between high- and low-performance college students

This study investigates potential differences in brain function among high-, average-, and low-performance college students using electroencephalography (EEG). We hypothesize that the increased academic engagement of high-performance students will lead to discernible EEG variations due to the brain's structural plasticity. 61 third-year college students from identical majors were divided into high-performance (n = 20), average-performance (n = 21), and low-performance (n = 20) groups based on their academic achievements. We conducted three EEG experiments: resting state, Sternberg working memory task, and Raven progressive matrix task. Comprehensive analyses of the EEG data from the three experiments focused on power spectral density (PSD) and functional connectivity, with coherence (COH) employed as our primary metric for the latter. The results showed that in all experiments, there were no differences in working memory ability and IQ scores among the groups, and there were no significant differences in the power spectral densities of the delta, theta, alpha1, alpha2, beta, and gamma bands among the groups. Notably, on the Raven test, compared to their high-performing peers, low-performing students showed enhanced functional connectivity in the alpha 1 (8-9 Hz) band that connects the frontal and occipital lobes. We explored three potential explanations for this phenomenon: fatigue, anxiety, and greater cognitive effort required for problem-solving due to inefficient self-regulation and increased susceptibility to distraction. In essence, these insights not only deepen our understanding of the neural basis that anchors academic ability, but also hold promise in guiding interventions that address students' diverse academic needs.

Handedness and anxiety: a review

Handedness is a core phenotype in clinical laterality research and several different disorders such as schizophrenia and autism spectrum disorders have been linked to a higher prevalence of non-right-handedness. Moreover, subclinical personality traits like schizotypy have been linked to a higher prevalence of non-right-handedness. The association with handedness is poorly understood for generalized anxiety disorder and specific phobias, as well as for state and trait anxiety and fear of specific stimuli in nonclinical samples. Therefore, we performed a narrative review of studies investigating handedness in anxiety disorders patients and studies that compared anxiety scores between different handedness groups. Unlike schizophrenia and autism spectrum disorders, there seems to be no strong association between anxiety disorders and handedness in adult patients, except for specific phobias. Studies often had small sample sizes and therefore a high risk to report spurious findings. Similar findings were reported in most non-clinical studies. Importantly, familial handedness affects phobia risk and antenatal maternal anxiety increased the probability of mixed-handedness. This suggests that a transgenerational, developmental perspective is essential to better understand the complex interrelations between handedness and anxiety. Familial and especially maternal handedness and anxiety disorders should be integrated into future studies on handedness and anxiety whenever possible.

Comparison of Electroencephalogram Power Spectrum Characteristics of Left and Right Dragon Boat Athletes after 1 km of Rowing

Purpose: This study aimed to detect differences in post-exercise brain activity between the left and right paddlers due to exercise by analyzing the resting-state electroencephalogram (EEG) power spectrum before and after exercise. Methods: Twenty-one right paddlers and twenty-two left paddlers completed a 1 km all-out test on a dragon boat ergometer, and their heart rate and exercise time were recorded. EEG signals were collected from superficial brain layers before and after exercise; then, the EEG power spectrum was extracted and compared in different frequency bands. In addition, the degree of lateralization in each brain region was assessed by the asymmetry index. Results: There was no significant difference in the power spectrum values and asymmetry indices between the left and right paddlers before rowing (p ˃ 0.05). However, after rowing, the left-paddlers group had significantly higher spectral power values in θ and α bands than the right-paddlers group (p < 0.05), and brain lateralization in both groups of athletes occurred mainly in the ipsilateral hemisphere of the frontal and central regions. Conclusion: The 1 km of rowing induced more brain activation in the left paddlers, and both left and right paddlers showed functional aggregation of hemispheric lateralization.

Behavioral Analysis of EEG Signals in Loss-Gain Decision-Making Experiments

Extraction and analysis of the EEG (electroencephalograph) information features generated during behavioral decision-making can provide a better understanding of the state of mind. Previous studies have focused more on the brainwave features after behavioral decision-making. In fact, the EEG before decision-making is more worthy of our attention. In this study, we introduce a new index based on the reaction time of subjects before decision-making, called the Prestimulus Time (PT), which have important reference value for the study of cognitive function, neurological diseases, and other fields. In our experiments, we use a wearable EEG feature signal acquisition device and a systematic reward and punishment experiment to obtain the EEG features before and after behavioral decision-making. The experimental results show that the EEG generated after behavioral decision due to loss is more intense than that generated by gain in the medial frontal cortex (MFC). In addition, different characteristics of EEG signals are generated prior to behavioral decisions because people have different expectations of the outcome. It will produce more significant negative-polarity event-related potential (ERP) in the forebrain area when the humans are optimistic about the outcomes.

Right frontal anxiolytic-sensitive EEG 'theta' rhythm in the stop-signal task is a theory-based anxiety disorder biomarker

Psychiatric diagnoses currently rely on a patient’s presenting symptoms or signs, lacking much-needed theory-based biomarkers. Our neuropsychological theory of anxiety, recently supported by human imaging, is founded on a longstanding, reliable, rodent ‘theta’ brain rhythm model of human clinical anxiolytic drug action. We have now developed a human scalp EEG homolog—goal-conflict-specific rhythmicity (GCSR), i.e., EEG rhythmicity specific to a balanced conflict between goals (e.g., approach-avoidance). Critically, GCSR is consistently reduced by different classes of anxiolytic drug and correlates with clinically-relevant trait anxiety scores (STAI-T). Here we show elevated GCSR in student volunteers divided, after testing, on their STAI-T scores into low, medium, and high (typical of clinical anxiety) groups. We then tested anxiety disorder patients (meeting diagnostic criteria) and similar controls recruited separately from the community. The patient group had higher average GCSR than their controls—with a mixture of high and low GCSR that varied with, but cut across, conventional disorder diagnosis. Consequently, GCSR scores should provide the first theoretically-based biomarker that could help diagnose, and so redefine, a psychiatric disorder.