ArticleFrontiers in behavioral neuroscience2018
Frontal EEG Asymmetry and Middle Line Power Difference in Discrete Emotions.
Article in Frontiers in behavioral neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Review of Deep Learning Techniques for EEG-Based Emotion Recognition: Models, Methods, and Datasets.F1000Research · 2025Pooled it
- Electroencephalogram-Based Analysis of Monomodal and Multimodal Interaction in Mixed Reality Games.Sensors (Basel, Switzerland) · 2026Article
- Acute response and neurophysiological mechanisms of mindfulness meditation in emotional eating.Journal of eating disorders · 2026Article
- Neurophysiological features in women with antenatal depressive symptoms: a resting-state quantitative electroencephalography study.European archives of psychiatry and clinical neuroscience · 2026Article
- Psychophysiological and Neurobiological Responses to Deception and Emotional Stimuli: A Pilot Study on the Interplay of Personality Traits and Perceived Stress.Brain sciences · 2025Article
- Domain-generalized Deep Learning for Improved Subject-independent Emotion Recognition Based on Electroencephalography.Experimental neurobiology · 2025Article
- Prefrontal Internal Event-Driven Analysis of Dynamical Electroencephalographic Biomarkers in Depression During Emotional Auditory Task.CNS neuroscience & therapeutics · 2025Article
- The differential effects of dynamic, static, and combined activities in forest bathing on health outcomes by gender in older adults: evidence from a national forest park trial.Frontiers in psychology · 2025Article
- An EEG-based analysis of the effects of different music genres on driving stress.Frontiers in human neuroscience · 2025Article
- Review
- Graph theoretical brain connectivity measures to investigate neural correlates of music rhythms associated with fear and anger.Cognitive neurodynamics · 2024Article
- Frontal P300 asymmetry and congruence judgment: Retroactive switching is impaired during school day mornings in female adolescents.Current research in neurobiology · 2024Article
- Differential roles of brain oscillations in numerical processing: evidence from resting-state EEG and mental number line.Frontiers in human neuroscience · 2024Article
- Impact of negative links on the structural balance of brain functional network during emotion processing.Scientific reports · 2023Article
- Tactile estimation of hedonic and sensory properties during active touch: An electroencephalography study.The European journal of neuroscience · 2023Article
- Intermediate effects of mindfulness practice on the brain activity of college students: An EEG study.IBRO neuroscience reports · 2023Article
- Dynamic segregation and integration of brain functional networks associated with emotional arousal.iScience · 2023Article
- Walk the plank! Using mobile electroencephalography to investigate emotional lateralization of immersive fear in virtual reality.Royal Society open science · 2023Article
- eSEE-d: Emotional State Estimation Based on Eye-Tracking Dataset.Brain sciences · 2023Article
- An Efficient Machine Learning-Based Emotional Valence Recognition Approach Towards Wearable EEG.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A traditional model of emotion cannot explain the differences in brain activities between two discrete emotions that are similar in the valence-arousal coordinate space. The current study elicited two positive emotions (amusement and tenderness) and two negative emotions (anger and fear) that are similar in both valence and arousal dimensions to examine the differences in brain activities in these emotional states. Frontal electroencephalographic (EEG) asymmetry and midline power in three bands (theta, alpha and beta) were measured when participants watched affective film excerpts. Significant differences were detected between tenderness and amusement on FP1/FP2 theta asymmetry, F3/F4 theta and alpha asymmetry. Significant differences between anger and fear on FP1/FP2 theta asymmetry and F3/F4 alpha asymmetry were also observed. For midline power, midline theta power could distinguish two negative emotions, while midline alpha and beta power could effectively differentiate two positive emotions. Liking and dominance were also related to EEG features. Stepwise multiple linear regression results revealed that frontal alpha and theta asymmetry could predict the subjective feelings of two positive and two negative emotions in different patterns. The binary classification accuracy, which used EEG frontal asymmetry and midline power as features and support vector machine (SVM) as classifiers, was as high as 64.52% for tenderness and amusement and 78.79% for anger and fear. The classification accuracy was improved after adding these features to other features extracted across the scalp. These findings indicate that frontal EEG asymmetry and midline power might have the potential to recognize discrete emotions that are similar in the valence-arousal coordinate space.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.