ArticleCognitive neurodynamics2017
Analysis of functional brain connections for positive-negative emotions using phase locking value.
Article in Cognitive neurodynamics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Efficiency of Repetitive Transcranial Direct Current Stimulation of the Dorsolateral Prefrontal Cortex in Disorders of Consciousness: A Randomized Sham-Controlled Study.Neural plasticity · 2019Trial
- An automated extraction of spectral-temporal and spatial-temporal features of EEG for emotion detection.Brain informatics · 2025Article
- High gamma EEG responses to emotional stimuli in virtual reality: insights from local activation and distributed characteristics.Frontiers in human neuroscience · 2025Article
- Neural decoding and feature selection methods for closed-loop control of avoidance behavior.Journal of neural engineering · 2024Article
- EEG Dataset for the Recognition of Different Emotions Induced in Voice-User Interaction.Scientific data · 2024Article
- Neural Decoding and Feature Selection Techniques for Closed-Loop Control of Defensive Behavior.bioRxiv : the preprint server for biology · 2024Article
- Research on Brain Networks of Human Balance Based on Phase Estimation Synchronization.Brain sciences · 2024Article
- Exploring brain network oscillations during seizures in drug-naïve patients with juvenile absence epilepsy.Frontiers in neurology · 2024Article
- Impact of negative links on the structural balance of brain functional network during emotion processing.Scientific reports · 2023Article
- A study on the combination of functional connection features and Riemannian manifold in EEG emotion recognition.Frontiers in neuroscience · 2023Article
- Relations between family cohesion and adolescent-parent's neural synchrony in response to emotional stimulations.Behavioral and brain functions : BBF · 2022Article
- Dynamic Functional Connectivity of Emotion Processing in Beta Band with Naturalistic Emotion Stimuli.Brain sciences · 2022Article
- LEDPatNet19: Automated Emotion Recognition Model based on Nonlinear LED Pattern Feature Extraction Function using EEG Signals.Cognitive neurodynamics · 2022Article
- Functional neuronal networks reveal emotional processing differences in children with ADHD.Cognitive neurodynamics · 2022Article
- EEG-FCV: An EEG-Based Functional Connectivity Visualization Framework for Cognitive State Evaluation.Frontiers in psychiatry · 2022Article
- Fusion of EEG-Based Activation, Spatial, and Connection Patterns for Fear Emotion Recognition.Computational intelligence and neuroscience · 2022Article
- Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG.Scientific reports · 2021Article
- Emotional Information in News Reporting on Audience Cognitive Processing in the Age of Posttruth: An Electroencephalogram and Functional Connectivity Approach.Frontiers in psychology · 2021Article
- A novel facial attractiveness evaluation system based on face shape, facial structure features and skin.Cognitive neurodynamics · 2020Article
- The late parietal event-related potential component is hierarchically sensitive to chunk tightness during chunk decomposition.Cognitive neurodynamics · 2020Article
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3 authors.
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Abstract
In this study, we investigate the brain networks during positive and negative emotions for different types of stimulus (audio only, video only and audio + video) in [Formula: see text], and [Formula: see text] bands in terms of phase locking value, a nonlinear method to study functional connectivity. Results show notable hemispheric lateralization as phase synchronization values between channels are significant and high in right hemisphere for all emotions. Left frontal electrodes are also found to have control over emotion in terms of functional connectivity. Besides significant inter-hemisphere phase locking values are observed between left and right frontal regions, specifically between left anterior frontal and right mid-frontal, inferior-frontal and anterior frontal regions; and also between left and right mid frontal regions. ANOVA analysis for stimulus types show that stimulus types are not separable for emotions having high valence. PLV values are significantly different only for negative emotions or neutral emotions between audio only/video only and audio only/audio + video stimuli. Finding no significant difference between video only and audio + video stimuli is interesting and might be interpreted as that video content is the most effective part of a stimulus.
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