Frontal EEG Asymmetry of Emotion for the Same Auditory Stimulus

Emotions play an important role in human interaction and decision-making processes. Frontal asymmetry in brain activity is a promising neurophysiological indicator of emotion. Emotions are psychologically explained by the valence-arousal model, but as yet, frontal asymmetry has not been fully explained by this model. In this study, we explored frontal asymmetry of emotions based on the valence-arousal model using the same auditory stimulus. Changes in emotional states using self-report questionnaires were investigated before and after the auditory stimulus. Spectral power and weighted phase lag index were calculated in the delta, theta, alpha, beta, and gamma bands. Phase-amplitude coupling was also measured to explore communication among different frequency bands associated with emotions. After the auditory stimulus, alpha power decreased in both left and right frontal regions and the delta-weighted phase lag index in the left-right regions was increased. However, no frontal asymmetry was identified after the auditory stimulus. Additionally, we explored the brain changes according to the valence-arousal model based on emotional states. After the auditory stimulus, frontal asymmetry of alpha power was clearly observed only for negative valence. This finding was possible because subjective emotions were considered despite listening to the same stimulus. Finally, phase-amplitude coupling identified left-hemisphere dominance after the auditory stimulus, regardless of subjective emotions. These results may help us understand frontal asymmetry associated with emotional mechanisms. In addition, these findings can be used directly in the brain-computer interface to improve emotion recognition performance for real-world practical applications.

[1]  John T. Cacioppo,et al.  Comment: Laterality and Evaluative Bivalence: A Neuroevolutionary Perspective , 2011 .

[2]  Seong-Whan Lee,et al.  Possible Effect of Binaural Beat Combined With Autonomous Sensory Meridian Response for Inducing Sleep , 2019, Front. Hum. Neurosci..

[3]  Jonathan R. Zadra,et al.  Emotion and perception: the role of affective information. , 2011, Wiley interdisciplinary reviews. Cognitive science.

[4]  Gerard J. Fogarty,et al.  Construct Validity of the Profile of Mood States , 2003 .

[5]  K. Hong,et al.  Decoding four different sound-categories in the auditory cortex using functional near-infrared spectroscopy , 2016, Hearing Research.

[6]  Massimiliano Palmiero,et al.  Frontal EEG Asymmetry of Mood: A Mini-Review , 2017, Front. Behav. Neurosci..

[7]  Yuji Mizuno,et al.  Neural dynamics in motor preparation: From phase-mediated global computation to amplitude-mediated local computation , 2015, NeuroImage.

[8]  Alamgir Hossan,et al.  A smart system for driver's fatigue detection, remote notification and semi-automatic parking of vehicles to prevent road accidents , 2016, 2016 International Conference on Medical Engineering, Health Informatics and Technology (MediTec).

[9]  Soraia M. Alarcão,et al.  Emotions Recognition Using EEG Signals: A Survey , 2019, IEEE Transactions on Affective Computing.

[10]  Ying Zeng,et al.  EEG Based Emotion Recognition by Combining Functional Connectivity Network and Local Activations , 2019, IEEE Transactions on Biomedical Engineering.

[11]  Hyoung Joong Kim,et al.  A High-Security EEG-Based Login System with RSVP Stimuli and Dry Electrodes , 2016, IEEE Transactions on Information Forensics and Security.

[12]  Yvonne Höller,et al.  Individual brain-frequency responses to self-selected music. , 2012, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[13]  Deborah A Hall,et al.  Auditory Pathways: Are ‘What’ and ‘Where’ Appropriate? , 2003, Current Biology.

[14]  Dinggang Shen,et al.  Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification , 2017, Human brain mapping.

[15]  Ranjan Sengupta,et al.  Study on Brain Dynamics by Non Linear Analysis of Music Induced EEG Signals , 2016 .

[16]  N. Pop-Jordanova,et al.  Inter- and Intra-Hemispheric EEG Coherence Study in Adults with Neuropsychiatric Disorders , 2018, Prilozi.

[17]  Seong-Whan Lee,et al.  Network Properties in Transitions of Consciousness during Propofol-induced Sedation , 2017, Scientific Reports.

[18]  Avinash Tandle,et al.  Estimation of valence of emotion from musically stimulated EEG using frontal theta asymmetry , 2016, 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD).

[19]  M. A. Kramer,et al.  Assessment of cross-frequency coupling with confidence using generalized linear models , 2013, Journal of Neuroscience Methods.

[20]  L. Trainor,et al.  Frontal brain electrical activity (EEG) distinguishes valence and intensity of musical emotions , 2001 .

[21]  Siamac Fazli,et al.  Subject-dependent classification for robust idle state detection using multi-modal neuroimaging and data-fusion techniques in BCI , 2015, Pattern Recognit..

[22]  Nikolaos A. Laskaris,et al.  Towards the bio-personalization of music recommendation systems: A single-sensor EEG biomarker of subjective music preference , 2016, Inf. Sci..

[23]  N. P. Guhan Seshadri,et al.  Music induced emotion using wavelet packet decomposition - An EEG study , 2018, Biomed. Signal Process. Control..

[24]  Bryan Paton,et al.  Emotional Responses to Music: Shifts in Frontal Brain Asymmetry Mark Periods of Musical Change , 2017, Front. Psychol..

[25]  R. E. Wheeler,et al.  Frontal brain asymmetry and emotional reactivity: a biological substrate of affective style. , 2007, Psychophysiology.

[26]  J. Russell A circumplex model of affect. , 1980 .

[27]  Bahar Güntekin,et al.  The modulation of delta responses in the interaction of brightness and emotion. , 2017, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[28]  Hairul Anuar Hashim,et al.  Factorial Validation of Malaysian Adapted Brunel Mood Scale in an Adolescent Sample , 2010, Asian journal of sports medicine.

[29]  Sanqing Hu,et al.  Brain Effective Connectivity Analysis from EEG for Positive and Negative Emotion , 2017, ICONIP.

[30]  Aneta Brzezicka,et al.  Frontal EEG alpha band asymmetry as a predictor of reasoning deficiency in depressed people , 2017, Cognition & emotion.

[31]  Selin Aviyente,et al.  Time-Frequency Based Phase-Amplitude Coupling Measure For Neuronal Oscillations , 2019, Scientific Reports.

[32]  Diana Adler,et al.  Using Multivariate Statistics , 2016 .

[33]  J. Fell,et al.  Cross-frequency coupling supports multi-item working memory in the human hippocampus , 2010, Proceedings of the National Academy of Sciences.

[34]  Yuan-Pin Lin,et al.  EEG-Based Emotion Recognition in Music Listening , 2010, IEEE Transactions on Biomedical Engineering.

[35]  Yodchanan Wongsawat,et al.  A Novel Insight of Effects of a 3-Hz Binaural Beat on Sleep Stages During Sleep , 2018, Front. Hum. Neurosci..

[36]  Kalyana Chakravarthy Veluvolu,et al.  Identification of emotion associated brain functional network with phase locking value , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[37]  Sahar Moghimi,et al.  Toward automatic detection of brain responses to emotional music through analysis of EEG effective connectivity , 2016, Comput. Hum. Behav..

[38]  Shamsul Sahibuddin,et al.  Exploratory Factor Analysis ; Concepts and Theory , 2014 .

[39]  Charles Spence,et al.  Sensory determinants of the autonomous sensory meridian response (ASMR): understanding the triggers , 2017, PeerJ.

[40]  Erol Başar,et al.  Affective pictures processing is reflected by an increased long-distance EEG connectivity , 2017, Cognitive Neurodynamics.

[41]  H. Merckelbach,et al.  The validity of individual frontal alpha asymmetry EEG neurofeedback. , 2016, Social cognitive and affective neuroscience.

[42]  Mehrdad Nourani,et al.  Nonlinear dimension reduction for EEG-based epileptic seizure detection , 2016, 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI).

[43]  Philip A. Gable,et al.  Affective motivational direction drives asymmetric frontal hemisphere activation , 2014, Experimental Brain Research.

[44]  Michael X Cohen,et al.  Assessing transient cross-frequency coupling in EEG data , 2008, Journal of Neuroscience Methods.

[45]  Guangyuan Liu,et al.  Effects of Negative Stimulation After Exercise on Frontal Asymmetry in Unregular Exercisers , 2019, IOP Conference Series: Materials Science and Engineering.

[46]  Leontios J. Hadjileontiadis,et al.  Toward an EEG-Based Recognition of Music Liking Using Time-Frequency Analysis , 2012, IEEE Transactions on Biomedical Engineering.

[47]  Ting Li,et al.  Emotion Recognition and Dynamic Functional Connectivity Analysis Based on EEG , 2019, IEEE Access.

[48]  Humaira Nisar,et al.  The Effect of Music on Human Brain; Frequency Domain and Time Series Analysis Using Electroencephalogram , 2018, IEEE Access.

[49]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[50]  B. Geethanjali,et al.  Music-Induced Brain Functional Connectivity Using EEG Sensors: A Study on Indian Music , 2019, IEEE Sensors Journal.

[51]  M. Whittington,et al.  Gamma and beta frequency oscillations in response to novel auditory stimuli: A comparison of human electroencephalogram (EEG) data with in vitro models. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[52]  Ian Daly,et al.  Neural correlates of emotional responses to music: An EEG study , 2014, Neuroscience Letters.

[53]  Noor Ul Hadi,et al.  An Easy Approach to Exploratory Factor Analysis: Marketing Perspective , 2016 .

[54]  Yasar Dasdemir,et al.  Analysis of functional brain connections for positive–negative emotions using phase locking value , 2017, Cognitive Neurodynamics.

[55]  Wolfgang Rosenstiel,et al.  EEG Responses to Auditory Stimuli for Automatic Affect Recognition , 2016, Front. Neurosci..

[56]  Sophie K. Scott,et al.  The structural neuroanatomy of music emotion recognition: Evidence from frontotemporal lobar degeneration , 2011, NeuroImage.

[57]  Isabelle Peretz,et al.  Towards a Neurobiology of Musical Emotions , 1993 .

[58]  Ankoor S. Shah,et al.  An oscillatory hierarchy controlling neuronal excitability and stimulus processing in the auditory cortex. , 2005, Journal of neurophysiology.

[59]  Kristen A. Lindquist,et al.  The brain basis of emotion: A meta-analytic review , 2012, Behavioral and Brain Sciences.

[60]  Mark Hallett,et al.  Reorganization of brain functional small‐world networks during finger movements , 2012, Human brain mapping.

[61]  Simon Hanslmayr,et al.  Resting frontal EEG alpha-asymmetry predicts the evaluation of affective musical stimuli , 2009, Neuroscience Letters.

[62]  Michael Tangermann,et al.  Eyes-Closed Increases the Usability of Brain-Computer Interfaces Based on Auditory Event-Related Potentials , 2018, Front. Hum. Neurosci..

[63]  Peter C. Terry,et al.  Identification and Description of Novel Mood Profile Clusters , 2017, Front. Psychol..

[64]  Yasuhiro Haruta,et al.  Lateralized Theta Wave Connectivity and Language Performance in 2- to 5-Year-Old Children , 2011, The Journal of Neuroscience.

[65]  Andrew M Lane,et al.  Mood changes following golf among senior recreational players. , 2005, Journal of sports science & medicine.

[66]  G. Mashour,et al.  Neurophysiological Correlates of Sevoflurane-induced Unconsciousness , 2015, Anesthesiology.

[67]  H. Kaiser A second generation little jiffy , 1970 .

[68]  Seong-Whan Lee,et al.  Connectivity differences between consciousness and unconsciousness in non-rapid eye movement sleep: a TMS–EEG study , 2019, Scientific Reports.

[69]  Sook-Lei Liew,et al.  Calculating the Laterality Index Using FSL for Stroke Neuroimaging Data , 2016 .

[70]  Ruoyu Du,et al.  Power spectral performance analysis of EEG during emotional auditory experiment , 2014, 2014 International Conference on Audio, Language and Image Processing.

[71]  Bor-Shyh Lin,et al.  Emotion recognition of EEG underlying favourite music by support vector machine , 2013, 2013 1st International Conference on Orange Technologies (ICOT).

[72]  M. Bartlett A Note on the Multiplying Factors for Various χ2 Approximations , 1954 .

[73]  Antonia Thelen,et al.  Neural mechanisms of mental fatigue elicited by sustained auditory processing , 2017, Neuropsychologia.

[74]  Yan Ge,et al.  Frontal EEG Asymmetry and Middle Line Power Difference in Discrete Emotions , 2018, Front. Behav. Neurosci..

[75]  C. Izard Emotion theory and research: highlights, unanswered questions, and emerging issues. , 2009, Annual review of psychology.

[76]  Jie Li,et al.  Explore the Brain Response to Naturalistic and Continuous Music Using EEG Phase Characteristics , 2016, ICIC.

[77]  Yodchanan Wongsawat,et al.  Brain Responses to a 6-Hz Binaural Beat: Effects on General Theta Rhythm and Frontal Midline Theta Activity , 2017, Front. Neurosci..

[78]  M. Balconi,et al.  The Use of Hyperscanning to Investigate the Role of Social, Affective, and Informative Gestures in Non-Verbal Communication. Electrophysiological (EEG) and Inter-Brain Connectivity Evidence , 2020, Brain sciences.

[79]  Reza Khosrowabadi,et al.  Alteration of perceived emotion and brain functional connectivity by changing the musical rhythmic pattern , 2019, Experimental Brain Research.

[80]  Lutz Jäncke,et al.  Time course of EEG oscillations during repeated listening of a well-known aria , 2015, Front. Hum. Neurosci..

[81]  Ian Daly,et al.  Electroencephalography reflects the activity of sub-cortical brain regions during approach-withdrawal behaviour while listening to music , 2019, Scientific Reports.

[82]  Seong-Whan Lee,et al.  Changes of Functional and Effective Connectivity in Smoking Replenishment on Deprived Heavy Smokers: A Resting-State fMRI Study , 2013, PloS one.

[83]  Haifeng Li,et al.  Music-evoked emotion recognition based on cognitive principles inspired EEG temporal and spectral features , 2018, Int. J. Mach. Learn. Cybern..

[84]  Faramarz GHARAGOZLOU,et al.  Detecting Driver Mental Fatigue Based on EEG Alpha Power Changes during Simulated Driving , 2015, Iranian journal of public health.

[85]  Fabio Babiloni,et al.  Assessment of driving fatigue based on intra/inter-region phase synchronization , 2017, Neurocomputing.

[86]  Zhongmin Wang,et al.  Phase-Locking Value Based Graph Convolutional Neural Networks for Emotion Recognition , 2019, IEEE Access.