Association Between Frontal Alpha Asymmetry With Cognitive Symptoms, Depression Severity, and Insomnia

Objective: Previous studies have compared depressive episodes between bipolar disorder (BD) and major depressive disorder (MDD) using quantitative electroencephalogram (QEEG); however, there are no distinct discriminating feature between them. Here, we used QEEG to directly compare the alpha asymmetry and absolute power of each band between patients with BD and MDD.Methods: Fifty in-patients with major depressive episodes between 2019 and 2021 were retrospectively enrolled. Self-reported questionnaires including the Beck Depression Inventory (BDI), Korean version of the Childhood Trauma Questionnaire, and Adult Attention-Deficit/Hyperactivity Disorder Self Report Scale (ASRS) were used to evaluate the symptoms. The absolute power of QEEG delta, theta, alpha, beta, high beta waves, and the Z-scores of frontal alpha asymmetry were collected. A t-test and Pearson’s correlation test were conducted using these data and based on these results, an analysis of covariance was conducted.Results: There were no significant differences between MDD and BD in QEEG power or alpha asymmetry. Patients with severe depression (BDI ≥29) had higher alpha power at FP1 (p=0.037), FP2 (p=0.028), F3 (p=0.047), F4 (p=0.016), and higher right frontal alpha asymmetry at F3–F4 (p=0.039). Adult patients with features consistent with ADHD (ASRS ≥4) had higher right frontal alpha asymmetry at F3–F4 (p=0.046). Patients with insomnia had higher left frontal alpha asymmetry at F3–F4 (p=0.003).Conclusion: QEEG limited the differential diagnosis of MDD and BD. However, frontal alpha asymmetry did exist in depression and affected cognitive impairment, insomnia, and depression severity in particular. Future studies with improved methodologies are needed for a better comparison.

Automatic Clustering of Students by Level of Situational Interest Based on Their EEG Features

The usage of physiological measures in detecting student’s interest is often said to improve the weakness of psychological measures by decreasing the susceptibility of subjective bias. The existing methods, especially EEG-based, use classification, which needs a predefined class and complex computational to analyze. However, the predefined classes are mostly based on subjective measurement (e.g., questionnaires). This work proposed a new scheme to automatically cluster the students by the level of situational interest (SI) during learning-based lessons on their electroencephalography (EEG) features. The formed clusters are then used as ground truth for classification purposes. A simultaneous recording of EEG was performed on 30 students while attending a lecture in a real classroom. The frontal mean delta and alpha power as well as the frontal alpha asymmetry metric served as the input for k-means and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithms. Using the collected data, 29 models were trained within nine domain classifiers, then the classifiers with the highest performance were selected. We validated all the models through 10-fold cross-validation. The high SI group was clustered to students having lower frontal mean delta and alpha power together with negative Frontal Alpha Asymmetry (FAA). It was found that k-means performed better by giving the maximum performance assessment parameters of 100% in clustering the students into three groups: high SI, medium SI and low SI. The findings show that the DBSCAN had reduced the performance to cluster dataset without the outlier. The findings of this study give a promising option to cluster the students by their SI level, as well as address the drawbacks of the existing methods, which use subjective measures.

Emotion Regulation Choice in Internet Addiction: Less Reappraisal, Lower Frontal Alpha Asymmetry

Individuals with internet addiction (IA) show difficulties in emotion regulation. However, they could effectively employ emotion regulation strategies when instructed. We speculate that this discrepancy might be caused by maladaptive emotion regulation choices. Recent studies indicated that decreased activity of the left frontal cortex could be a neural marker of reappraisal use. To address this problem, individuals with IA ( n = 17, IA group) and healthy individuals ( n = 23, healthy control [HC] group) were required to choose an emotion regulation strategy between reappraisal and distraction to regulate their emotions varying in emotional intensity and valence. We also compared the resting state frontal alpha asymmetry (FAA) of these 2 groups. The results replicated more choices of reappraisal in low- versus high-intensity emotional contexts across groups. More importantly, the IA group chose reappraisal less frequently compared with the HC group, irrespective of emotional intensity. Furthermore, we found individuals with IA have lower FAA than healthy controls, and FAA shows a positive correlation with the use of reappraisal. These findings suggest that IA alters individuals’ patterns of emotion regulation choice and impairs frontal activities, causing difficulties in emotion regulation.

Validating the wearable MUSE headset for EEG spectral analysis and Frontal Alpha Asymmetry

EEG power spectral density (PSD), the individual alpha frequency (IAF) and the frontal alpha asymmetry (FAA) are all EEG spectral measures that have been widely used to evaluate cognitive and attentional processes in experimental and clinical settings, and that can be used for real-world applications (e.g., remote EEG monitoring, brain-computer interfaces, neurofeedback, neuromodulation, etc.). Potential applications remain limited by the high cost, low mobility, and long preparation times associated with high-density EEG recording systems. Low-density wearable systems address these issues and can increase access to larger and diversified samples. The present study tested whether a low-cost, 4-channel wearable EEG system (the MUSE) could be used to quickly measure continuous EEG data, yielding similar frequency components compared to research a grade EEG system (the 64-channel BIOSEMI Active Two). We compare the spectral measures from MUSE EEG data referenced to mastoids to those from BIOSEMI EEG data with two different references for validation. A minimal amount of data was deliberately collected to test the feasibility for real-world applications (EEG setup and data collection being completed in under 5 min). We show that the MUSE can be used to examine power spectral density (PSD) in all frequency bands, the individual alpha frequency (IAF; i.e., peak alpha frequency and alpha center of gravity), and frontal alpha asymmetry. Furthermore, we observed satisfying internal consistency reliability in alpha power and asymmetry measures recorded with the MUSE. Estimating asymmetry on PAF and CoG frequencies did not yield significant advantages relative to the traditional method (whole alpha band). These findings should advance human neurophysiological monitoring using wearable neurotechnologies in large participant samples and increase the feasibility of their implementation in real-world settings.

Frontal Alpha Asymmetry: a potential biomarker of approach-withdrawal motivation towards pain.

Pain-related catastrophising is a maladaptive coping strategy known to have a strong influence on clinical pain outcomes and treatment efficacy. Mounting evidence suggests catastrophising is associated with resting-state EEG frontal alpha asymmetry (FAA) patterns reflective of greater relative right frontal activity, thought to underly withdrawal motivation and negative affect. Notwithstanding, knowledge on the neurophysiological basis of catastrophising remains limited. The present study aims to investigate whether such relationship occurs in the situational context of experimental pain, and how FAA is modulated by pain and placebo treatment. 35 participants completed the Pain Catastrophising Scale (PCS) questionnaire prior to EEG recordings during cold pressor test (CPT)-induced tonic pain with or without prior application of placebo cream. There was a negative correlation between FAA and PCS-subscale helplessness scores, but not rumination or magnification, during the pre-placebo CPT condition. Moreover, FAA scores were shown to increase significantly in response to pain, indicative of greater relative left frontal activity that relates to approach-oriented behaviours. Placebo treatment elicited a decrease in FAA in low helplessness scorers, but no significant effects in individuals scoring above the mean on PCS-helplessness. These findings suggest that, during painful events, FAA may reflect the motivational drive to obtain reward of pain relief, which may be diminished in individuals who are prone to feel helpless about their pain. This study provides valuable insights into biomarkers of pain-related catastrophising and prospects of identifying promising targets of brain-based therapies for chronic pain management.

Frontal Alpha Asymmetry in Posttraumatic Stress Disorder: Group Differences Among Individuals With and Without PTSD During an Inhibitory Control Task

The current study examined frontal alpha asymmetry (FAA) as a marker of approach- and avoidance-related prefrontal activity in participants with and without trauma exposure and posttraumatic stress disorder (PTSD). We investigated FAA in an inhibitory control paradigm (threatening vs nonthreatening cues) under 2 levels of cognitive demand (baseline: images constant within a block of trials; vs filtering: images varied randomly within a block) in 3 groups of participants: individuals with PTSD ( n = 16), exposed to trauma but without PTSD ( n = 14), and a control group without PTSD or trauma exposure ( n = 15). Under low demand (baseline), both PTSD and trauma-exposed participants exhibited significantly greater relative left than right frontal brain activity (approach) to threatening than to nonthreatening images. Under high demand (filtering), no FAA differences were found between threatening and nonthreatening images, but PTSD participants revealed more relative left than right FAA, whereas trauma-exposed participants showed reduced left relative right FAA. In all conditions, healthy controls exhibited reduced left relative to right FAA and no differences between threatening and nonthreatening images. Study findings suggest dysfunctional prefrontal mechanisms of emotion regulation in PTSD, but adaptive prefrontal regulation in trauma-exposed individuals without PTSD.

The Level of Self-Esteem May Influence the Effect of Positive Self-Statements. An EEG Alpha Asymmetry Pilot Study

(1) Background: Affirmative statements are widely recognized as a reliable tool that enhances personal resources to manage life demands, including stress-coping and emotional adaptability. However, recent data suggest that contrary effects can be obtained regarding the global self-esteem level. The current study focused on an approach for recognizing affirmation-induced responses in electroencephalographic (EEG) alpha asymmetry. (2) Methods: EEG data were collected from a total of 45 males (16–20 years) on a baseline condition and compared to EEG data produced when listening to positive self-statements, regarding self-esteem as a covariate. (3) Results: The study revealed relative left-frontal alpha asymmetry, indicating an approach-related motivational state, and right alpha asymmetry in parieto-temporal regions, indicating lower anxiety. This increased with higher self-esteem scores, with a more prominent moderation effect in experimental conditions. These results support and extend previous reports suggesting an adverse effect of positive self-statements for people with lower global self-esteem. (4) Conclusions: Positive self-statements may produce a differing physiological effect regarding an individual’s global self-esteem level, with an adverse effect for people with lower self-esteem scores. These data highlight the need to consider differentiation of psychological approaches between people with higher and lower self-esteem levels.