Music-evoked Emotions Research Articles

Music-evoked emotions classification using vision transformer in EEG signals.

The field of electroencephalogram (EEG)-based emotion identification has received significant attention and has been widely utilized in both human-computer interaction and therapeutic settings. The process of manually analyzing electroencephalogram signals is characterized by a significant investment of time and work. While machine learning methods have shown promising results in classifying emotions based on EEG data, the task of extracting distinct characteristics from these signals still poses a considerable difficulty. In this study, we provide a unique deep learning model that incorporates an attention mechanism to effectively extract spatial and temporal information from emotion EEG recordings. The purpose of this model is to address the existing gap in the field. The implementation of emotion EEG classification involves the utilization of a global average pooling layer and a fully linked layer, which are employed to leverage the discernible characteristics. In order to assess the effectiveness of the suggested methodology, we initially gathered a dataset of EEG recordings related to music-induced emotions. Subsequently, we ran comparative tests between the state-of-the-art algorithms and the method given in this study, utilizing this proprietary dataset. Furthermore, a publicly accessible dataset was included in the subsequent comparative trials. The experimental findings provide evidence that the suggested methodology outperforms existing approaches in the categorization of emotion EEG signals, both in binary (positive and negative) and ternary (positive, negative, and neutral) scenarios.

The Emotion-to-Music Mapping Atlas (EMMA): A systematically organized online database of emotionally evocative music excerpts

Selecting appropriate musical stimuli to induce specific emotions represents a recurring challenge in music and emotion research. Most existing stimuli have been categorized according to taxonomies derived from general emotion models (e.g., basic emotions, affective circumplex), have been rated for perceived emotions, and are rarely defined in terms of interrater agreement. To redress these limitations, we present research that served in the development of a new interactive online database, including an initial set of 364 music excerpts from three different genres (classical, pop, and hip/hop) that were rated for felt emotion using the Geneva Emotion Music Scale (GEMS), a music-specific emotion scale. The sample comprised 517 English- and German-speaking participants and each excerpt was rated by an average of 28.76 participants (SD = 7.99). Data analyses focused on research questions that are of particular relevance for musical database development, notably the number of raters required to obtain stable estimates of emotional effects of music and the adequacy of the GEMS as a tool for describing music-evoked emotions across three prominent music genres. Overall, our findings suggest that 10–20 raters are sufficient to obtain stable estimates of emotional effects of music excerpts in most cases, and that the GEMS shows promise as a valid and comprehensive annotation tool for music databases.

Emotions and Psychological Mechanisms of Listening to Music in Cochlear Implant Recipients.

Music is a multidimensional phenomenon and is classified by its arousal properties, emotional quality, and structural characteristics. Although structural features of music (i.e., pitch, timbre, and tempo) and music emotion recognition in cochlear implant (CI) recipients are popular research topics, music-evoked emotions, and related psychological mechanisms that reflect both the individual and social context of music are largely ignored. Understanding the music-evoked emotions (the "what") and related mechanisms (the "why") can help professionals and CI recipients better comprehend the impact of music on CI recipients' daily lives. Therefore, the purpose of this study is to evaluate these aspects in CI recipients and compare their findings to those of normal hearing (NH) controls. This study included 50 CI recipients with diverse auditory experiences who were prelingually deafened (deafened at or before 6 years of age)-early implanted (N = 21), prelingually deafened-late implanted (implanted at or after 12 years of age-N = 13), and postlingually deafened (N = 16) as well as 50 age-matched NH controls. All participants completed the same survey, which included 28 emotions and 10 mechanisms (Brainstem reflex, Rhythmic entrainment, Evaluative Conditioning, Contagion, Visual imagery, Episodic memory, Musical expectancy, Aesthetic judgment, Cognitive appraisal, and Lyrics). Data were presented in detail for CI groups and compared between CI groups and between CI and NH groups. The principal component analysis showed five emotion factors that are explained by 63.4% of the total variance, including anxiety and anger, happiness and pride, sadness and pain, sympathy and tenderness, and serenity and satisfaction in the CI group. Positive emotions such as happiness, tranquility, love, joy, and trust ranked as most often experienced in all groups, whereas negative and complex emotions such as guilt, fear, anger, and anxiety ranked lowest. The CI group ranked lyrics and rhythmic entrainment highest in the emotion mechanism, and there was a statistically significant group difference in the episodic memory mechanism, in which the prelingually deafened, early implanted group scored the lowest. Our findings indicate that music can evoke similar emotions in CI recipients with diverse auditory experiences as it does in NH individuals. However, prelingually deafened and early implanted individuals lack autobiographical memories associated with music, which affects the feelings evoked by music. In addition, the preference for rhythmic entrainment and lyrics as mechanisms of music-elicited emotions suggests that rehabilitation programs should pay particular attention to these cues.

The cognitive characteristics of music-evoked autobiographical memories: Evidence from a systematic review of clinical investigations.

In healthy adults, autobiographical memories (AMs) evoked by music appear to have unique cognitive characteristics that set them apart from AMs evoked by other cues. If this is the case, we might expect music cues to alleviate AM deficits in clinical disorders. This systematic review examines music-evoked autobiographical memories (MEAMs) in clinical populations, focusing on cognitive characteristics, and whether MEAMs differ from AMs evoked by other stimuli. We identified 15 studies featuring participants with Alzheimer's disease (AD), behavioral variant - Frontotemporal dementia (bv-FTD), acquired brain damage, and depression. We found that music evokes AMs in these disorders, and that familiar music was more likely to evoke AMs. Compared with healthy controls, AD participants had a relative advantage for MEAMs over picture-evoked AMs. People with damage to the medial prefrontal cortex showed preserved access to MEAMs in terms of frequency, but a relative disadvantage regarding the episodic richness for MEAMs, but not for memories cued by pictures, compared to controls. Participants with bv-FTD had fewer AMs evoked after both music and pictures than healthy controls. Across conditions, MEAMs were generally specific and retrieved fast, suggesting little retrieval effort. MEAMs were also positive, except in depression, where as many negative as positive AMs were produced. These findings suggest several underlying cognitive and affective mechanisms of MEAMs, including anxiety reduction, increased fluency, music-evoked emotions, reminiscence, and involuntary retrieval, and that these might be moderated by musical abilities and memory for music. In conclusion, MEAMs appear to be relatively well preserved, especially in AD. This article is categorized under: Psychology > Memory.

Musical emotions affect memory for emotional pictures

Music is widely known for its ability to evoke emotions. However, assessing specific music-evoked emotions other than through verbal self-reports has proven difficult. In the present study, we explored whether mood-congruency effects could be used as indirect measures of specific music-evoked emotions. First, participants listened to 15 music excerpts chosen to induce different emotions; after each excerpt, they were required to look at four different pictures. The pictures could either: (1) convey an emotion congruent with that conveyed by the music (i.e., congruent pictures); (2) convey a different emotion than that of the music, or convey no emotion (i.e., incongruent pictures). Second, participants completed a recognition task that included new pictures as well as already seen congruent and incongruent pictures. From previous findings about mood-congruency effects, we hypothesized that if music evokes a given emotion, this would facilitate memorization of pictures that convey the same emotion. Results revealed that accuracy in the recognition task was indeed higher for emotionally congruent pictures than for emotionally incongruent ones. The results suggest that music-evoked emotions have an influence on subsequent cognitive processing of emotional stimuli, suggesting a role of mood-congruency based recall tasks as non-verbal methods for the identification of specific music-evoked emotions.

Enhancing Emotion Recognition Using Region-Specific Electroencephalogram Data and Dynamic Functional Connectivity.

Recognizing the emotional states of humans through EEG signals are of great significance to the progress of human-computer interaction. The present study aimed to perform automatic recognition of music-evoked emotions through region-specific information and dynamic functional connectivity of EEG signals and a deep learning neural network. EEG signals of 15 healthy volunteers were collected when different emotions (high-valence-arousal vs. low-valence-arousal) were induced by a musical experimental paradigm. Then a sequential backward selection algorithm combining with deep neural network called Xception was proposed to evaluate the effect of different channel combinations on emotion recognition. In addition, we also assessed whether dynamic functional network of frontal cortex, constructed through different trial number, may affect the performance of emotion cognition. Results showed that the binary classification accuracy based on all 30 channels was 70.19%, the accuracy based on all channels located in the frontal region was 71.05%, and the accuracy based on the best channel combination in the frontal region was 76.84%. In addition, we found that the classification performance increased as longer temporal functional network of frontal cortex was constructed as input features. In sum, emotions induced by different musical stimuli can be recognized by our proposed approach though region-specific EEG signals and time-varying functional network of frontal cortex. Our findings could provide a new perspective for the development of EEG-based emotional recognition systems and advance our understanding of the neural mechanism underlying emotion processing.

Mind-Wandering during Personal Music Listening in Everyday Life: Music-Evoked Emotions Predict Thought Valence.

Research has shown that mind-wandering, negative mood, and poor wellbeing are closely related, stressing the importance of exploring contexts or tools that can stimulate positive thoughts and images. While music represents a promising option, work on this topic is still scarce with only a few studies published, mainly featuring laboratory or online music listening tasks. Here, I used the experience sampling method for the first time to capture mind-wandering during personal music listening in everyday life, aiming to test for the capacity of music to facilitate beneficial styles of mind-wandering and to explore its experiential characteristics. Twenty-six participants used a smart-phone application that collected reports of thought, mood, and emotion during music listening or other daily-life activities over 10 days. The application was linked to a music playlist, specifically assembled to induce positive and relaxing emotions. Results showed that mind-wandering evoked during music and non-music contexts had overall similar characteristics, although some minor differences were also observed. Most importantly, music-evoked emotions predicted thought valence, thereby indicating music as an effective tool to regulate thoughts via emotion. These findings have important applications for music listening in daily life as well as for the use of music in health interventions.

What makes music memorable? Relationships between acoustic musical features and music-evoked emotions and memories in older adults

Music has a unique capacity to evoke both strong emotions and vivid autobiographical memories. Previous music information retrieval (MIR) studies have shown that the emotional experience of music is influenced by a combination of musical features, including tonal, rhythmic, and loudness features. Here, our aim was to explore the relationship between music-evoked emotions and music-evoked memories and how musical features (derived with MIR) can predict them both. Healthy older adults (N = 113, age ≥ 60 years) participated in a listening task in which they rated a total of 140 song excerpts comprising folk songs and popular songs from 1950s to 1980s on five domains measuring the emotional (valence, arousal, emotional intensity) and memory (familiarity, autobiographical salience) experience of the songs. A set of 24 musical features were extracted from the songs using computational MIR methods. Principal component analyses were applied to reduce multicollinearity, resulting in six core musical components, which were then used to predict the behavioural ratings in multiple regression analyses. All correlations between behavioural ratings were positive and ranged from moderate to very high (r = 0.46-0.92). Emotional intensity showed the highest correlation to both autobiographical salience and familiarity. In the MIR data, three musical components measuring salience of the musical pulse (Pulse strength), relative strength of high harmonics (Brightness), and fluctuation in the frequencies between 200-800 Hz (Low-mid) predicted both music-evoked emotions and memories. Emotional intensity (and valence to a lesser extent) mediated the predictive effect of the musical components on music-evoked memories. The results suggest that music-evoked emotions are strongly related to music-evoked memories in healthy older adults and that both music-evoked emotions and memories are predicted by the same core musical features.

Wait For It

Previous brain-related studies on music-evoked emotions have relied on listening to long music segments, which may reduce the precision of correlating emotional cues to specific brain areas. Break routines in electronic dance music (EDM) are emotive but short music moments containing three passages: breakdown, build-up, and drop. Within build-ups music features increase to peak moments prior to highly expected drop passages and peak-pleasurable emotions when these expectations are fulfilled. The neural correlates of peak-pleasurable emotions (such as excitement) in the short seconds of build-up and drop passages in EDM break routines are therefore good candidates to study brain correlates of emotion. Thirty-six participants listened to break routines while undergoing continuous EEG. Source reconstruction of EEG epochs for one second of build-up and of drop passages showed that pre- and post-central gyri and precuneus were more active during build-ups, and the inferior frontal gyrus (IFG) and middle frontal gyrus (MFG) were more active within drop passages. Importantly, IFG and MFG activity showed a correlation with ratings of subjective excitement during drop passages. The results suggest expectation is important in inducing peak-pleasurable experiences and brain activity changes within seconds of reported feelings of excitement during EDM break routines.

Decoding Music-Evoked Emotions in the Auditory and Motor Cortex.

Music can induce strong subjective experience of emotions, but it is debated whether these responses engage the same neural circuits as emotions elicited by biologically significant events. We examined the functional neural basis of music-induced emotions in a large sample (n = 102) of subjects who listened to emotionally engaging (happy, sad, fearful, and tender) pieces of instrumental music while their hemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI). Ratings of the four categorical emotions and liking were used to predict hemodynamic responses in general linear model (GLM) analysis of the fMRI data. Multivariate pattern analysis (MVPA) was used to reveal discrete neural signatures of the four categories of music-induced emotions. To map neural circuits governing non-musical emotions, the subjects were scanned while viewing short emotionally evocative film clips. The GLM revealed that most emotions were associated with activity in the auditory, somatosensory, and motor cortices, cingulate gyrus, insula, and precuneus. Fear and liking also engaged the amygdala. In contrast, the film clips strongly activated limbic and cortical regions implicated in emotional processing. MVPA revealed that activity in the auditory cortex and primary motor cortices reliably discriminated the emotion categories. Our results indicate that different music-induced basic emotions have distinct representations in regions supporting auditory processing, motor control, and interoception but do not strongly rely on limbic and medial prefrontal regions critical for emotions with survival value.

A coordinate-based meta-analysis of music-evoked emotions

Since the publication of the first neuroscience study investigating emotion with music about two decades ago, the number of functional neuroimaging studies published on this topic has increased each year. This research interest is in part due to the ubiquity of music across cultures, and to music's power to evoke a diverse range of intensely felt emotions. To support a better understanding of the brain correlates of music-evoked emotions this article reports a coordinate-based meta-analysis of neuroimaging studies (n = 47 studies with n = 944 subjects). The studies employed a range of diverse experimental approaches (e.g., using music to evoke joy, sadness, fear, tension, frissons, surprise, unpleasantness, or feelings of beauty). The results of an activation likelihood estimation (ALE) indicate large clusters in a range of structures, including amygdala, anterior hippocampus, auditory cortex, and numerous structures of the reward network (ventral and dorsal striatum, anterior cingulate cortex, orbitofrontal cortex, secondary somatosensory cortex). The results underline the rewarding nature of music, the role of the auditory cortex as an emotional hub, and the role of the hippocampus in attachment-related emotions and social bonding.

Emotions of music listening in Finland and in India: Comparison of an individualistic and a collectivistic culture

Music is appreciated for emotional reasons across cultures, but knowledge on the cross-cultural similarities and differences of music-evoked emotions is still sparse. The current study compared music-evoked emotions in Finland and in India, contextualizing them within the perceived psychological functionality of music in an individualistic versus collectivistic culture. Participants ( N = 230) answered an online survey on music-evoked emotions and related personal meanings. A mixed-method approach using factor analysis and qualitative content analysis was used to identify the concepts for cross-cultural comparison. Results show that both cultures value music for positive emotional experiences, but the prevalence of more detailed emotional nuances and underlying meanings is distinctively different. The highest-scoring emotion factor for Finns was Power-Empowerment while for Indians it was Peaceful-Transcendence. For Finns, the personal relevance of music was distinctively related to self-enhancement, self-reflective insights, and self-expression, while for Indians the relevance was particularly related to using music as a mood management tool for reaching positive, relaxed, and motivated affective states. Both cultures found music important for experiencing social connection. The results partly reflect the individualistic-collectivistic dimensionality of cultures and emphasize the relevance of contextualizing music psychological knowledge of music-evoked emotions in individuals’ culturally bound meaning-making processes.

Music-Evoked Reward and Emotion: Relative Strengths and Response to Intervention of People With ASD.

This review presents research findings showing that music is a unique domain to assess perception, reward, emotion, and associated physiological reactions and neural circuitry of people with autism spectrum disorder (ASD). There is growing evidence, reported in several studies in this review article, indicating that music is a relative strength of people with ASD including musical pitch perception, musical memory, and identification of music-evoked emotions. Listening to music activates neural circuits of reward and emotion response, which are described. Research presented shows adults with ASD also activate these systems when listening to music, although there may be developmental differences in the physiological and neural response to music in childhood and adolescence alongside typical behavioral response. Nonetheless, studies reviewed lend support to the use of music therapy and education for people with ASD, specifically to improve social skills and communication. Neural correlates of response to music therapy and education are also discussed. Taken together, findings reviewed provide evidence for music as a strength-based approach for ASD to assess reward and emotion response and as a powerful tool for intervention.

A review of music-evoked visual mental imagery: Conceptual issues, relation to emotion, and functional outcome.

Visual mental imagery has been characterized as an important aspect of our mental life, which consists of “seeing” in the absence of a sensory stimulus. However, the mechanisms underlying how visual mental images unfold during music listening have remained largely neglected. Here, we review the existing literature on the relation between music-evoked emotions and images, and we draw attention to how visual mental imagery has been previously conceptualized in the music domain. We also propose to adopt a conceptual framework from research on spontaneous cognition, which will promote a more nuanced and comprehensive understanding of the different types of music-evoked visual mental imagery. Finally, we highlight how music’s capability to trigger images can be harnessed in daily life as well as in therapeutic practices to foster the benefits and minimize the costs of visual mental imagery.

Music-evoked emotion recognition based on cognitive principles inspired EEG temporal and spectral features

Electroencephalographic (EEG) based emotion recognition has attracted increasing attention in the field of human-computer interaction (HCI). But, how to use the cognitive principles to enhance the emotion recognition model is still a challenge. The purpose of this research paper is to investigate the emotion cognitive process and its application. Firstly, to evoke the response emotions, a three-stage experimental paradigm of long-time music stimuli was designed. The EEG signals were recorded in 15 healthy adults during the listening of 16 music clips respectively. Then, the time course analysis method of music-evoked emotions was proposed to examine the differences of brain activities. There was great increase of the spectral power in alpha band and a slight decrease in high-frequency beta and gamma bands during music listening. Through time analysis, the characteristics of the inspiring–keeping–fading were also found in different emotional states. After that, the most relevant EEG features were selected based on the time correlation analysis between EEG and music features. Finally, based on the cognitive principles inspired EEG features, an emotional prediction system was built. From the results, the accuracies of binary classification were 66.8% for valence and 59.5% for arousal. The accuracies of 3-classes classification performed as 45.9% for valence and 45.1% for arousal. These results suggest that with the help of cognitive principles, a better emotional recognition system could be built. Understanding the cognitive process could promote the development of artificial intelligence.

Music-Evoked Emotions—Current Studies

The present study is focused on a review of the current state of investigating music-evoked emotions experimentally, theoretically and with respect to their therapeutic potentials. After a concise historical overview and a schematic of the hearing mechanisms, experimental studies on music listeners and on music performers are discussed, starting with the presentation of characteristic musical stimuli and the basic features of tomographic imaging of emotional activation in the brain, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), which offer high spatial resolution in the millimeter range. The progress in correlating activation imaging in the brain to the psychological understanding of music-evoked emotion is demonstrated and some prospects for future research are outlined. Research in psychoneuroendocrinology and molecular markers is reviewed in the context of music-evoked emotions and the results indicate that the research in this area should be intensified. An assessment of studies involving measuring techniques with high temporal resolution down to the 10 ms range, as, e.g., electroencephalography (EEG), event-related brain potentials (ERP), magnetoencephalography (MEG), skin conductance response (SCR), finger temperature, and goose bump development (piloerection) can yield information on the dynamics and kinetics of emotion. Genetic investigations reviewed suggest the heredity transmission of a predilection for music. Theoretical approaches to musical emotion are directed to a unified model for experimental neurological evidence and aesthetic judgment. Finally, the reports on musical therapy are briefly outlined. The study concludes with an outlook on emerging technologies and future research fields.

Psychophysiological Indices of Music-Evoked Emotions in Musicians

A number of psychophysiological measures indexing autonomic and somatovisceral activation to music have been proposed in line with the wider emotion literature. However, attempts to replicate experimental findings and provide converging evidence for music-evoked emotions through physiological changes, overt expression, and subjective measures have had mixed success. This may be due to issues in stimulus and participant selection. Therefore, the aim of Experiment 1 was to select musical stimuli that were controlled for instrumentation, musical form, style, and familiarity. We collected a wide range of subjective responses from 30 highly trained musicians to music varying along the affective dimensions of arousal and valence. Experiment 2 examined a set of psychophysiological correlates of emotion in 20 different musicians by measuring heart rate, skin conductance, and facial electromyography during listening without requiring behavioral reports. Excerpts rated higher in arousal in Experiment 1 elicited larger cardiovascular and electrodermal responses. Excerpts rated positively in valence produced higher zygomaticus major activity, whereas excerpts rated negatively in valence produced higher corrugator supercilii activity. These findings provide converging evidence of emotion induction during music listening in musicians via subjective self-reports and psychophysiological measures, and further, that such responses are similar to emotions observed outside the musical domain.

Review on Neural Correlates of Emotion Regulation and Music: Implications for Emotion Dysregulation.

Previous studies have examined the neural correlates of emotion regulation and the neural changes that are evoked by music exposure. However, the link between music and emotion regulation is poorly understood. The objectives of this review are to (1) synthesize what is known about the neural correlates of emotion regulation and music-evoked emotions, and (2) consider the possibility of therapeutic effects of music on emotion dysregulation. Music-evoked emotions can modulate activities in both cortical and subcortical systems, and across cortical-subcortical networks. Functions within these networks are integral to generation and regulation of emotions. Since dysfunction in these networks are observed in numerous psychiatric disorders, a better understanding of neural correlates of music exposure may lead to more systematic and effective use of music therapy in emotion dysregulation.

Music-evoked emotions in schizophrenia

Background/objectivesPrevious studies have reported that people with schizophrenia have impaired musical abilities. Here we developed a simple music-based assay to assess patient's ability to associate a minor chord with sadness. We further characterize correlations between impaired musical responses and psychiatric symptoms. MethodWe exposed participants sequentially to two sets of sound stimuli, first a C-major progression and chord, and second a C-minor progression and chord. Participants were asked which stimulus they associated with sadness, the first set, the second set, or neither. The severity of psychiatric symptoms was assessed using the Positive and Negative Syndrome Scale (PANSS). Study participants were 29 patients diagnosed with schizophrenia and 29 healthy volunteers matched in age, gender and musical background. Result37.9% (95% confidence interval [CI]:19.1–56.7) of patients with schizophrenia associated the minor chord set as sad, compared with 97.9% (95%CI: 89.5–103.6) of controls. Four patients were diagnosed with treatment-resistant schizophrenia, and all four failed to associate the minor chord with sadness. Patients who did not recognize minor chords as sad had significantly higher scores on all PANSS subscales. ConclusionsA simple test allows music-evoked emotions to be assessed in schizophrenia patient, and may show potential relationships between music-evoked emotions and psychiatric symptoms.

Hey Mister Tambourine Man, Play a Drug for Me: Music as Medication.

Listening to music may be thought of as noninvasive and nonpharmacological, but music should be considered a drug therapy. Music exposure has measurable neurobiological effects that are linked to systems regulating reward, motivation, and pleasure; stress and arousal; and immunity. Functional neuroimaging and lesion studies demonstrate that music-evoked emotions are associated with modulation of linked limbic and paralimbic brain regions. Some of these regions are involved in reward, motivation, and pleasure, and there are additional projections to brain structures regulating autonomic, emotional, and cognitive function. Controlled clinical studies have found significant benefits with the use of music for depression and anxiety, pain relief, stroke recovery, schizophrenia, and behavioral and psychological symptoms of dementia. Because music is not associated with significant adverse effects, it is a viable adjunctive treatment option for patients in many different clinical settings. [Journal of Psychosocial Nursing and Mental Health Services, 54(12), 23-27.].