Dynamic intersubject neural synchronization reflects affective responses to sad music

Music-Evoked Nostalgia Activates Default Mode and Reward Networks Across the Lifespan

Nostalgia is a mixed emotion that is often evoked by music. Nostalgic music may induce temporary improvements in autobiographical memory in individuals with cognitive decline. However, the neural mechanism underlying music-evoked nostalgia and its associated memory improvements is unclear. With the ultimate goal of understanding how nostalgia-evoking music may help retrieve autobiographical memories in individuals with cognitive impairment, we first sought to understand the neural underpinnings of these processes in healthy younger and older adults. Methodological constraints, including the lack of personally tailored and experimentally controlled stimuli, have impeded our understanding of this mechanism. Here, we utilized an innovative machine-learning-based method to construct three categories of songs, all matched for musical features: (1) personalized nostalgic, (2) familiar non-nostalgic, and (3) unfamiliar non-nostalgic. In 57 participants (29 aged 18-35; 28 aged 60 and older), we investigated the functional neural correlates of music-evoked nostalgia using fMRI. Four main findings emerged: (1) Listening to nostalgic music, more than familiar non-nostalgic or unfamiliar music, was associated with bilateral activity in the default mode network, salience network, reward network, medial temporal lobe, and supplementary motor regions, (2) Psychophysiological interaction (PPI) models indicated that listening to nostalgic music involved increased functional connectivity of self-referential (posteromedial cortex) and affect-related regions (insula), (3) Older adults had stronger BOLD signals than younger adults in nostalgia-related regions during nostalgic listening, (4) While the BOLD response to nostalgic music in younger adults was associated with trait-level factors of nostalgia proneness and cognitive ability, the response in older adults was related to affective responses to the music. Overall, our findings serve as a foundation for understanding the neural basis of music-evoked nostalgia and its potential use in future clinical interventions.

Meeting the multidimensional self: fostering selfhood at the interface of Creative Arts Therapies and neuroscience

Intriguing explorations at the intersection of the fields of neuroscience and psychology are driven by the quest to understand the neural underpinnings of "the self" and their psychotherapeutic implications. These translational efforts pertain to the unique Creative Arts Therapies (CATs) and the attributes and value of the self-related processes they offer. The self is considered as a multi-layered complex construct, comprising bodily and mental constituents, subjective-objective perspectives, spatial and temporal dimensions. Neuroscience research, mostly functional brain imaging, has proposed cogent models of the constitution, development and experience of the self, elucidating how the multiple dimensions of the self are supported by integrated hierarchical brain processes. The psychotherapeutic use of the art-forms, generating aesthetic experiences and creative processes, touch upon and connect the various layers of self-experience, nurturing the sense of self. The present conceptual analysis will describe and interweave the neural mechanisms and neural network configuration suggested to lie at the core of the ongoing self-experience, its deviations in psychopathology, and implications regarding the psychotherapeutic use of the arts. The well-established, parsimonious and neurobiologically plausible predictive processing account of brain-function will be discussed with regard to selfhood and consciousness. The epistemic affordance of the experiential CATs will further be portrayed, enabling and facilitating the creation of updated self-models of the body in the world. The neuropsychological impact of the relational therapeutic encounter will be delineated, acknowledging the intersubjective brain synchronization through communicative verbal and non-verbal means and aesthetic experiences. The recognition and assimilation of neuroscientific, phenomenological and clinical perspectives concerning the nested dimensionality of the self, ground the relational therapeutic process and the neuroplastic modulations that CATs have to offer on the premise of fostering, shaping and integrating selfhood.

Brain to brain musical interaction: A systematic review of neural synchrony in musical activities

The use of hyperscanning technology has revealed the neural mechanisms underlying multi-person interaction in musical activities. However, there is currently a lack of integration among various research findings. This systematic review aims to provide a comprehensive understanding of the social dynamics and brain synchronization in music activities through the analysis of 32 studies. The findings illustrate a strong correlation between inter-brain synchronization (IBS) and various musical activities, with the frontal, central, parietal, and temporal lobes as the primary regions involved. The application of hyperscanning not only advances theoretical research but also holds practical significance in enhancing the effectiveness of music-based interventions in therapy and education. The review also utilizes Predictive Coding Models (PCM) to provide a new perspective for interpreting neural synchronization in music activities. To address the limitations of current research, future studies could integrate multimodal data, adopt novel technologies, use non-invasive techniques, and explore additional research directions.

Time-varying similarity of neural responses to musical tension is shaped by physical features and musical themes

The similarity of understanding is important for music experience and communication, but little is understood about the sources of this common knowledge. Although neural responses to the same piece of music are known to be similar across listeners, it remains unclear whether this neural response similarity is linked to musical understanding and the role of dynamic musical attributes in shaping it. Our study addresses this gap by investigating the relationship between neural response similarity, musical tension, and dynamic musical attributes. Using electroencephalography-based inter-subject correlation (EEG-ISC), we examined how the neural response similarity among listeners varies throughout the evaluation of musical tension in the first movement of Beethoven's Piano Sonata No. 8. Participants continuously rated the degree of alignment between musical events and their expectations, while neural activity was recorded using electroencephalography (EEG). The results showed that neural response similarity fluctuated in tandem with musical tension, with increased similarity observed during moments of heightened tension. This time-varying neural response similarity was influenced by two dynamic attributes contributing to musical tension: physical features and musical themes. Specifically, its fluctuation was driven by physical features, and the patterns of its variation were modulated by musical themes, with similar time-varying patterns observed across similar thematic materials. These findings offer valuable insight into the role of dynamic musical attributes in shaping neural response similarity, and reveal an important source and mechanism of shared musical understandings.

Neural signatures of shared subjective affective engagement and disengagement during movie viewing

When watching a negative emotional movie, we differ from person to person in the ease with which we engage and the difficulty with which we disengage throughout a temporally evolving narrative. We investigated neural responses of emotional processing, by considering inter-individual synchronization in subjective emotional engagement and disengagement. The neural underpinnings of these shared responses are ideally studied in naturalistic scenarios like movie viewing, wherein individuals emotionally engage and disengage at their own time and pace throughout the course of a narrative. Despite the rich data that naturalistic designs can bring to the study, there is a challenge in determining time-resolved behavioral markers of subjective engagement and disengagement and their underlying neural responses. We used a within-subject cross-over design instructing 22 subjects to watch clips of either neutral or sad content while undergoing functional magnetic resonance imaging (fMRI). Participants watched the same movies a second time while continuously annotating the perceived emotional intensity, thus enabling the mapping of brain activity and emotional experience. Our analyses revealed that between-participant similarity in waxing (engagement) and waning (disengagement) of emotional intensity was directly related to the between-participant similarity in spatiotemporal patterns of brain activation during the movie(s). Similar patterns of engagement reflected common activation in the bilateral ventromedial prefrontal cortex, regions often involved in self-referenced evaluation and generation of negative emotions. Similar patterns of disengagement reflected common activation in central executive and default mode network regions often involved in top-down emotion regulation. Together this work helps to better understand cognitive and neural mechanisms underpinning engagement and disengagement from emotionally evocative narratives.

The role of external factors in affect-sharing and their neural bases

Affect-sharing, the ability to vicariously feel another person's emotions, is the primary component of empathy that is typically thought to rely on the observer's capacity to feel the emotions of others. However, external signals, such as the target's physical characteristics, have been demonstrated to influence affect-sharing in the neuroscientific literature that speaks to the underappreciated role of external factors in eliciting affect-sharing. We consider factors that influence affect-sharing, including physical cues, emotional cues, situational factors, and observer-target relationships, as well as the neural circuits involved in these processes. Our review reveals that, while neural network activation is primarily responsible for processing affect-sharing, external factors also co-activate a top-down cognitive processing network to modulate the conscious process of affect-sharing. From this knowledge, an integrative framework of external factor interactions with affect-sharing are explained in detail. Finally, we identify critical areas for future research in social and affective neuroscience, including research gaps and incorporation of ecologically valid paradigms.

Probing neurodynamics of experienced emotions-a Hitchhiker's guide to film fMRI

Film functional magnetic resonance imaging (fMRI) has gained tremendous popularity in many areas of neuroscience. However, affective neuroscience remains somewhat behind in embracing this approach, even though films lend themselves to study how brain function gives rise to complex, dynamic and multivariate emotions. Here, we discuss the unique capabilities of film fMRI for emotion research, while providing a general guide of conducting such research. We first give a brief overview of emotion theories as these inform important design choices. Next, we discuss films as experimental paradigms for emotion elicitation and address the process of annotating them. We then situate film fMRI in the context of other fMRI approaches, and present an overview of results from extant studies so far with regard to advantages of film fMRI. We also give an overview of state-of-the-art analysis techniques including methods that probe neurodynamics. Finally, we convey limitations of using film fMRI to study emotion. In sum, this review offers a practitioners' guide to the emerging field of film fMRI and underscores how it can advance affective neuroscience.

Examining the consistency of continuous affect annotations and psychophysiological measures in response to emotional videos

Despite the growing necessity of understanding the dynamics of emotion by naturalistic stimuli, averaging time-locked responses seems insufficient to capture emotional experiences that change over time. Intersubject correlation (ISC) has been implemented to examine dynamic emotional experiences by quantifying the consistency of responses across individuals. While previous research has shown that enhanced psychophysiological ISC can capture dynamic emotional experiences in response to long-lasting videos that evoke dimensional emotions, it is not yet fully understood how psychophysiological consistency varies during videos that elicit distinct emotions, such as fear. In this study, we re-analyzed publicly available data consisting of continuous affect annotations and psychophysiological signals, namely heart rate (HR), electrodermal activity (EDA), electromyographic signals from zygomaticus major (EMG-z), and corrugator supercilii (EMG-c), in response to categorical emotional videos, namely amusing, boring, relaxing, and fearful. Results showed an overall increase in ISC in multiple measures during fearful videos, indicating that emotional experiences during fearful videos were reliably consistent across participants. The effect of amusing and boring videos on ISC revealed varying results depending on the measurements. In particular, larger ISC in valence rating, EDA, and EMG-z was found for amusing than boring videos, whereas larger ISC in HR and EMG-c was observed for boring than amusing movies. Lastly, decreased ISC for relaxing videos was observed across multiple measurements, showing inconsistent emotional experiences during relaxing videos. This study builds on previous research on physiological consistency during emotional experiences by examining how the consistency of continuous affect annotations and psychophysiological measures differs in response to videos that elicit distinct emotions.

Attachment Reminders Trigger Widespread Synchrony across Multiple Brains

Infant stimuli elicit widespread neural and behavioral response in human adults, and such massive allocation of resources attests to the evolutionary significance of the primary attachment. Here, we examined whether attachment reminders also trigger cross-brain concordance and generate greater neural uniformity, as indicated by intersubject correlation. Human mothers were imaged twice in oxytocin/placebo administration design, and stimuli included four ecological videos of a standard unfamiliar mother and infant: two infant/mother alone (Alone) and two mother-infant dyadic contexts (Social). Theory-driven analysis measured cross-brain synchrony in preregistered nodes of the parental caregiving network (PCN), which integrates subcortical structures underpinning mammalian mothering with cortical areas implicated in simulation, mentalization, and emotion regulation, and data-driven analysis assessed brain-wide concordance using whole-brain parcellation. Results demonstrated widespread cross-brain synchrony in both the PCN and across the neuroaxis, from primary sensory/somatosensory areas, through insular-cingulate regions, to temporal and prefrontal cortices. The Social context yielded significantly more cross-brain concordance, with PCNs striatum, parahippocampal gyrus, superior temporal sulcus, ACC, and PFC displaying cross-brain synchrony only to mother-infant social cues. Moment-by-moment fluctuations in mother-infant social synchrony, ranging from episodes of low synchrony to tightly coordinated positive bouts, were tracked online by cross-brain concordance in the preregistered ACC. Findings indicate that social attachment stimuli, representing evolutionary-salient universal cues that require no verbal narrative, trigger substantial interbrain concordance and suggest that the mother-infant bond, an icon standing at the heart of human civilization, may function to glue brains into a unified experience and bind humans into social groups.SIGNIFICANCE STATEMENT Infant stimuli elicit widespread neural response in human adults, attesting to their evolutionary significance, but do they also trigger cross-brain concordance and induce neural uniformity among perceivers? We measured cross-brain synchrony to ecological mother-infant videos. We used theory-driven analysis, measuring cross-brain concordance in the parenting network, and data-driven analysis, assessing brain-wide concordance using whole-brain parcellation. Attachment cues triggered widespread cross-brain concordance in both the parenting network and across the neuroaxis. Moment-by-moment fluctuations in behavioral synchrony were tracked online by cross-brain variability in ACC. Attachment reminders bind humans' brains into a unitary experience and stimuli characterized by social synchrony enhance neural similarity among participants, describing one mechanism by which attachment bonds provide the neural template for the consolidation of social groups.

Dynamic emotional states shape the episodic structure of memory

Human emotions fluctuate over time. However, it is unclear how these shifting emotional states influence the organization of episodic memory. Here, we examine how emotion dynamics transform experiences into memorable events. Using custom musical pieces and a dynamic emotion-tracking tool to elicit and measure temporal fluctuations in felt valence and arousal, our results demonstrate that memory is organized around emotional states. While listening to music, fluctuations between different emotional valences bias temporal encoding process toward memory integration or separation. Whereas a large absolute or negative shift in valence helps segment memories into episodes, a positive emotional shift binds sequential representations together. Both discrete and dynamic shifts in music-evoked valence and arousal also enhance delayed item and temporal source memory for concurrent neutral items, signaling the beginning of new emotional events. These findings are in line with the idea that the rise and fall of emotions can sculpt unfolding experiences into memories of meaningful events.

Automated Classification of Dyadic Conversation Scenarios using Autonomic Nervous System Responses

Two people's physiological responses become more similar as those people talk or cooperate, a phenomenon called physiological synchrony. The degree of synchrony correlates with conversation engagement and cooperation quality, and could thus be used to characterize interpersonal interaction. In this study, we used a combination of physiological synchrony metrics and pattern recognition algorithms to automatically classify four different dyadic conversation scenarios: two-sided positive conversation, two-sided negative conversation, and two one-sided scenarios. Heart rate, skin conductance, respiration and peripheral skin temperature were measured from 16 dyads in all four scenarios, and individual as well as synchrony features were extracted from them. A two-stage classifier based on stepwise feature selection and linear discriminant analysis achieved a four-class classification accuracy of 75.0% in leave-dyad-out crossvalidation. Removing synchrony features reduced accuracy to 65.6%, indicating that synchrony is informative. In the future, such classification algorithms may be used to, e.g., provide real-time feedback about conversation mood to participants, with applications in areas such as mental health counseling and education. The approach may also generalize to group scenarios and adjacent areas such as cooperation and competition.

Topographic representation of visually evoked emotional experiences in the human cerebral cortex

Affective neuroscience seeks to uncover the neural underpinnings of emotions that humans experience. However, it remains unclear whether an affective space underlies the discrete emotion categories in the human brain, and how it relates to the hypothesized affective dimensions. To address this question, we developed a voxel-wise encoding model to investigate the cortical organization of human emotions. Results revealed that the distributed emotion representations are constructed through a fundamental affective space. We further compared each dimension of this space to 14 hypothesized affective dimensions, and found that many affective dimensions are captured by the fundamental affective space. Our results suggest that emotional experiences are represented by broadly spatial overlapping cortical patterns and form smooth gradients across large areas of the cortex. This finding reveals the specific structure of the affective space and its relationship to hypothesized affective dimensions, while highlighting the distributed nature of emotional representations in the cortex.

Inter-subject correlations of EEG reflect subjective arousal and acoustic features of music

Background

Research on music-induced emotion and brain activity is constantly expanding. Although studies using inter-subject correlation (ISC), a collectively shared brain activity analysis method, have been conducted, whether ISC during music listening represents the music preferences of a large population remains uncertain; additionally, it remains unclear which factors influence ISC during music listening. Therefore, here, we aimed to investigate whether the ISCs of electroencephalography (EEG) during music listening represent a preference for music reflecting engagement or interest of a large population in music.

Methods

First, we selected 21 pieces of music from the Billboard Japan Hot 100 chart of 2017, which served as an indicator of preference reflecting the engagement and interest of a large population. To ensure even representation, we chose one piece for every fifth song on the chart, spanning from highly popular music to less popular ones. Next, we recorded EEG signals while the subjects listened to the selected music, and they were asked to evaluate four aspects (preference, enjoyment, frequency of listening, and arousal) for each song. Subsequently, we conducted ISC analysis by utilizing the first three principal components of EEG, which were highly correlated across subjects and extracted through correlated component analysis (CorrCA). We then explored whether music with high preferences that reflected the engagement and interest of large population had high ISC values. Additionally, we employed cluster analysis on all 21 pieces of music, utilizing the first three principal components of EEG, to investigate the impact of emotions and musical characteristics on EEG ISC during music listening.

Results

A significant distinction was noted between the mean ISC values of the 10 higher-ranked pieces of music compared to the 10 lower-ranked pieces of music [t(542) = -1.97, p = 0.0025]. This finding suggests that ISC values may correspond preferences reflecting engagement or interest of a large population. Furthermore, we found that significant variations were observed in the first three principal component values among the three clusters identified through cluster analysis, along with significant differences in arousal levels. Moreover, the characteristics of the music (tonality and tempo) differed among the three clusters. This indicates that the principal components, which exhibit high correlation among subjects and were employed in calculating ISC values, represent both subjects' arousal levels and specific characteristics of the music.

Conclusion

Subjects' arousal values during music listening and music characteristics (tonality and tempo) affect ISC values, which represent the interest of a large population in music.

Naturalistic auditory stimuli with fNIRS prefrontal cortex imaging: A potential paradigm for disorder of consciousness diagnostics (a study with healthy participants)

Disorder of consciousness (DOC) is a devastating condition due to brain damage. A patient in this condition is non-responsive, but nevertheless might be conscious at least at some level. Determining the conscious level of DOC patients is important for both medical and ethical reasons, but reliably achieving this has been a major challenge. Naturalistic stimuli in combination with neuroimaging have been proposed as a promising approach for DOC patient diagnosis. Capitalizing on and extending this proposal, the goal of the present study conducted with healthy participants was to develop a new paradigm with naturalistic auditory stimuli and functional near-infrared spectroscopy (fNIRS) - an approach that can be used at the bedside. Twenty-four healthy participants passively listened to 9 min of auditory story, scrambled auditory story, classical music, and scrambled classical music segments while their prefrontal cortex activity was recorded using fNIRS. We found much higher intersubject correlation (ISC) during story compared to scrambled story conditions both at the group level and in the majority of individual subjects, suggesting that fNIRS imaging of the prefrontal cortex might be a sensitive method to capture neural changes associated with narrative comprehension. In contrast, the ISC during the classical music segment did not differ reliably from scrambled classical music and was also much lower than the story condition. Our main result is that naturalistic auditory stories with fNIRS might be used in a clinical setup to identify high-level processing and potential consciousness in DOC patients.

Development and validation of an fMRI-informed EEG model of reward-related ventral striatum activation

Reward processing is essential for our mental-health and well-being. In the current study, we developed and validated a scalable, fMRI-informed EEG model for monitoring reward processing related to activation in the ventral-striatum (VS), a significant node in the brain's reward system. To develop this EEG-based model of VS-related activation, we collected simultaneous EEG/fMRI data from 17 healthy individuals while listening to individually-tailored pleasurable music - a highly rewarding stimulus known to engage the VS. Using these cross-modal data, we constructed a generic regression model for predicting the concurrently acquired Blood-Oxygen-Level-Dependent (BOLD) signal from the VS using spectro-temporal features from the EEG signal (termed hereby VS-related-Electrical Finger Print; VS-EFP). The performance of the extracted model was examined using a series of tests that were applied on the original dataset and, importantly, an external validation dataset collected from a different group of 14 healthy individuals who underwent the same EEG/FMRI procedure. Our results showed that the VS-EFP model, as measured by simultaneous EEG, predicted BOLD activation in the VS and additional functionally relevant regions to a greater extent than an EFP model derived from a different anatomical region. The developed VS-EFP was also modulated by musical pleasure and predictive of the VS-BOLD during a monetary reward task, further indicating its functional relevance. These findings provide compelling evidence for the feasibility of using EEG alone to model neural activation related to the VS, paving the way for future use of this scalable neural probing approach in neural monitoring and self-guided neuromodulation.

Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs

Moral elevation, the emotion that arises when individuals observe others' moral behaviors, plays an important role in determining moral behaviors in real life. While recent research has demonstrated the potential to decode basic emotions with brain signals, there has been limited exploration of affective computing for moral elevation, an emotion related to social cognition. To address this gap, we recorded electroencephalography (EEG) signals from 23 participants while they viewed videos that were expected to elicit moral elevation. More than 30,000 danmaku comments were extracted as a crowdsourcing tagging method to label moral elevation continuously at a 1-s temporal resolution. Then, by employing power spectra features and the least absolute shrinkage and selection operator regularized regression analyses, we achieved a promising prediction performance for moral elevation (prediction r = 0.44 ± 0.11). Our findings indicate that it is possible to decode moral elevation using EEG signals. Moreover, the small-sample neural data can predict the continuous moral elevation experience conveyed in danmaku comments from a large population.

Sound-induced analgesia cannot always be observed in adult mice

Music seems promising as an adjuvant pain treatment in humans, while its mechanism remains to be illustrated. In rodent models of chronic pain, few studies reported the analgesic effect of music. Recently, Zhou et al. stated that the analgesic effects of sound depended on a low (5 dB) signal-to-noise ratio (SNR) relative to ambient noise in mice. However, despite employing multiple behavioral analysis approaches, we were unable to extend these findings to a mice model of chronic pain listening to the 5 dB SNR.

Analysis and Classification of Music-Induced States of Sadness

The enjoyment and pleasure derived from sad music has sparked fascination among researchers due to its seemingly paradoxical nature in producing positive affect. Research is yet to develop a comprehensive understanding of this “paradox.” Contradictory findings have resulted in a great variability within the literature, meaning results and interpretations can be difficult to derive. Consequently, this review collated the current literature, seeking to utilize the variability in the findings to propose a model of differential sad states, providing a means for past and future findings to be interpreted. The proposed model is based on theoretical understanding, as such it requires full empirical support. Comparisons to alternative models, theoretical, clinical, and cognitive implications, as well as future directions are discussed.

On the encoding of natural music in computational models and human brains

This article discusses recent developments and advances in the neuroscience of music to understand the nature of musical emotion. In particular, it highlights how system identification techniques and computational models of music have advanced our understanding of how the human brain processes the textures and structures of music and how the processed information evokes emotions. Musical models relate physical properties of stimuli to internal representations called features, and predictive models relate features to neural or behavioral responses and test their predictions against independent unseen data. The new frameworks do not require orthogonalized stimuli in controlled experiments to establish reproducible knowledge, which has opened up a new wave of naturalistic neuroscience. The current review focuses on how this trend has transformed the domain of the neuroscience of music.

Functional near-infrared spectroscopy imaging of the prefrontal cortex during a naturalistic comedy movie

Naturalistic stimulation (i.e., movies and auditory narratives of some minutes' length) has been a powerful approach to bringing more real-life experiences into laboratory experiments. Data-driven, intersubject correlation (ISC) analysis permits examining to what extent activity in a specific brain region correlates across participants during exposure to a naturalistic stimulus, as well as testing whether neural activity correlates with behavioral measures. Notably, most of the previous research with naturalistic stimuli was conducted using functional fMRI (fMRI). Here, we tested whether a naturalistic approach and the ISC are feasible using functional near-infrared spectroscopy (fNIRS) - the imaging method particularly suited for populations of patients and children. Fifty-three healthy adult participants watched twice a 3-min segment of a Charlie Chaplin movie while we recorded the brain activity on the surface of their prefrontal cortex using fNIRS. In addition, an independent group of 18 participants used a continuous scoring procedure to rate the extent to which they felt that different parts of the movie fragment were funny. Our two findings were as follows. First, we found higher-than-zero ISC in fNIRS signals in the prefrontal cortex lobes, a result that was particularly high in the oxygenated channels during the first repetition of the movie. Second, we found a significant negative correlation between oxygenated brain signals and ratings of the movie's humorousness. In a series of control analyses we demonstrated that this latter correlation could not be explained by various non-humor-related movie sensory properties (e.g., auditory volume and image brightness). The key overall outcome of the present study is that fNIRS in combination with the naturalistic paradigms and the ISC might be a sensitive and powerful research method to explore cognitive processing. Our results also suggest a potential role of the prefrontal cortex in humor appreciation.

Ongoing first-hand pain facilitates somatosensory resonance but inhibits affective sharing in empathy for pain

Alterations of empathy for others' pain among patients with chronic pain remained inconsistent. Here, applying a capsaicin-based ongoing pain model on healthy participants, this study investigated how ongoing first-hand pain influences empathic reactions to vicarious pain stimuli. Healthy participants were randomly treated with topical capsaicin cream (capsaicin group) or hand cream (control group) on the left forearm. Video clips showing limbs in painful and non-painful situations were used to induce empathic responses. The capsaicin group showed greater empathic neural responses in the right primary somatosensory cortex (S1) than the control group but smaller responses in the left anterior insula (AI) accompanied with smaller empathic pain-intensity ratings. Notably, the intensity of ongoing pain negatively correlated with empathy-related neural responses in the left AI. Inter-subject phase synchronization analysis was used to assess stimulus-dependent dynamic functional connectivity within or between brain regions engaged in pain empathy. The capsaicin group showed greater empathy-related neural synchronization within S1 and between S1 and AI, but less synchronization within AI and between AI and MCC. Behaviorally, the differential inter-subject pain-intensity rating alignment between painful and non-painful videos was more positive for the capsaicin group than for the control group, and this effect was partially mediated by the inter-subject neural synchronization between S1 and AI. These results suggest that ongoing first-hand pain facilitates neural activation and synchronization within brain regions associated with empathy-related somatosensory resonance at the cost of inhibiting activation and synchronization within brain regions engaged in empathy-related affective sharing.

Dynamic Functional Connectivity of Emotion Processing in Beta Band with Naturalistic Emotion Stimuli

While naturalistic stimuli, such as movies, better represent the complexity of the real world and are perhaps crucial to understanding the dynamics of emotion processing, there is limited research on emotions with naturalistic stimuli. There is a need to understand the temporal dynamics of emotion processing and their relationship to different dimensions of emotion experience. In addition, there is a need to understand the dynamics of functional connectivity underlying different emotional experiences that occur during or prior to such experiences. To address these questions, we recorded the EEG of participants and asked them to mark the temporal location of their emotional experience as they watched a video. We also obtained self-assessment ratings for emotional multimedia stimuli. We calculated dynamic functional the connectivity (DFC) patterns in all the frequency bands, including information about hubs in the network. The change in functional networks was quantified in terms of temporal variability, which was then used in regression analysis to evaluate whether temporal variability in DFC (tvDFC) could predict different dimensions of emotional experience. We observed that the connectivity patterns in the upper beta band could differentiate emotion categories better during or prior to the reported emotional experience. The temporal variability in functional connectivity dynamics is primarily related to emotional arousal followed by dominance. The hubs in the functional networks were found across the right frontal and bilateral parietal lobes, which have been reported to facilitate affect, interoception, action, and memory-related processing. Since our study was performed with naturalistic real-life resembling emotional videos, the study contributes significantly to understanding the dynamics of emotion processing. The results support constructivist theories of emotional experience and show that changes in dynamic functional connectivity can predict aspects of our emotional experience.

Sound induces analgesia through corticothalamic circuits

Sound-including music and noise-can relieve pain in humans, but the underlying neural mechanisms remain unknown. We discovered that analgesic effects of sound depended on a low (5-decibel) signal-to-noise ratio (SNR) relative to ambient noise in mice. Viral tracing, microendoscopic calcium imaging, and multitetrode recordings in freely moving mice showed that low-SNR sounds inhibited glutamatergic inputs from the auditory cortex (ACx^Glu) to the thalamic posterior (PO) and ventral posterior (VP) nuclei. Optogenetic or chemogenetic inhibition of the ACx^Glu→PO and ACx^Glu→VP circuits mimicked the low-SNR sound-induced analgesia in inflamed hindpaws and forepaws, respectively. Artificial activation of these two circuits abolished the sound-induced analgesia. Our study reveals the corticothalamic circuits underlying sound-promoted analgesia by deciphering the role of the auditory system in pain processing.

Sounding out pain

A circuit for sound-induced analgesia has been found in the mouse brain

Inferring Brain State Dynamics Underlying Naturalistic Stimuli Evoked Emotion Changes With dHA-HMM

The brain functional mechanisms underlying emotional changes have been primarily studied based on the traditional task design with discrete and simple stimuli. However, the brain state transitions when exposed to continuous and naturalistic stimuli with rich affection variations remain poorly understood. This study proposes a dynamic hyperalignment algorithm (dHA) to functionally align the inter-subject neural activity. The hidden Markov model (HMM) was used to study how the brain dynamics responds to emotion during long-time movie-viewing activity. The results showed that dHA significantly improved inter-subject consistency and allowed more consistent temporal HMM states across participants. Afterward, grouping the emotions in a clustering dendrogram revealed a hierarchical grouping of the HMM states. Further emotional sensitivity and specificity analyses of ordered states revealed the most significant differences in happiness and sadness. We then compared the activation map in HMM states during happiness and sadness and found significant differences in the whole brain, but strong activation was observed during both in the superior temporal gyrus, which is related to the early process of emotional prosody processing. A comparison of the inter-network functional connections indicates unique functional connections of the memory retrieval and cognitive network with the cerebellum network during happiness. Moreover, the persistent bilateral connections among salience, cognitive, and sensorimotor networks during sadness may reflect the interaction between high-level cognitive networks and low-level sensory networks. The main results were verified by the second session of the dataset. All these findings enrich our understanding of the brain states related to emotional variation during naturalistic stimuli.

Music in the brain

Music is ubiquitous across human cultures - as a source of affective and pleasurable experience, moving us both physically and emotionally - and learning to play music shapes both brain structure and brain function. Music processing in the brain - namely, the perception of melody, harmony and rhythm - has traditionally been studied as an auditory phenomenon using passive listening paradigms. However, when listening to music, we actively generate predictions about what is likely to happen next. This enactive aspect has led to a more comprehensive understanding of music processing involving brain structures implicated in action, emotion and learning. Here we review the cognitive neuroscience literature of music perception. We show that music perception, action, emotion and learning all rest on the human brain's fundamental capacity for prediction - as formulated by the predictive coding of music model. This Review elucidates how this formulation of music perception and expertise in individuals can be extended to account for the dynamics and underlying brain mechanisms of collective music making. This in turn has important implications for human creativity as evinced by music improvisation. These recent advances shed new light on what makes music meaningful from a neuroscientific perspective.

Basic Empathy Scale: A Systematic Review and Reliability Generalization Meta-Analysis

The Basic Empathy Scale (BES) has been internationally used to measure empathy. A systematic review including 74 articles that implement the instrument since its development in 2006 was carried out. Moreover, an evidence validity analysis and a reliability generalization meta-analysis were performed to examine if the scale presented the appropriate values to justify its application. Results from the systematic review showed that the use of the BES is increasing, although the research areas in which it is being implemented are currently being broadened. The validity analyses indicated that both the type of factor analysis and reliability are reported in validation studies much more than the consequences of testing are. Regarding the meta-analysis results, the mean of Cronbach's α for cognitive empathy was 0.81 (95% CI: 0.77-0.85), with high levels of heterogeneity (I2 = 98.81%). Regarding affective empathy, the mean of Cronbach's α was 0.81 (95% CI: 0.76-0.84), with high levels of heterogeneity. It was concluded that BES is appropriate to be used in general population groups, although not recommended for clinical diagnosis; and there is a moderate to high heterogeneity in the mean of Cronbach's α. The practical implications of the results in mean estimation and heterogeneity are discussed.

Classification of emotion categories based on functional connectivity patterns of the human brain

Neurophysiological and psychological models posit that emotions depend on connections across wide-spread corticolimbic circuits. While previous studies using pattern recognition on neuroimaging data have shown differences between various discrete emotions in brain activity patterns, less is known about the differences in functional connectivity. Thus, we employed multivariate pattern analysis on functional magnetic resonance imaging data (i) to develop a pipeline for applying pattern recognition in functional connectivity data, and (ii) to test whether connectivity patterns differ across emotion categories. Six emotions (anger, fear, disgust, happiness, sadness, and surprise) and a neutral state were induced in 16 participants using one-minute-long emotional narratives with natural prosody while brain activity was measured with functional magnetic resonance imaging (fMRI). We computed emotion-wise connectivity matrices both for whole-brain connections and for 10 previously defined functionally connected brain subnetworks and trained an across-participant classifier to categorize the emotional states based on whole-brain data and for each subnetwork separately. The whole-brain classifier performed above chance level with all emotions except sadness, suggesting that different emotions are characterized by differences in large-scale connectivity patterns. When focusing on the connectivity within the 10 subnetworks, classification was successful within the default mode system and for all emotions. We thus show preliminary evidence for consistently different sustained functional connectivity patterns for instances of emotion categories particularly within the default mode system.

Automatic Estimation of Interpersonal Engagement During Naturalistic Conversation Using Dyadic Physiological Measurements

Physiological responses of two interacting individuals contain a wealth of information about the dyad: for example, the degree of engagement or trust. However, nearly all studies on dyadic physiological responses have targeted group-level analysis: e.g., correlating physiology and engagement in a large sample. Conversely, this paper presents a study where physiological measurements are combined with machine learning algorithms to dynamically estimate the engagement of individual dyads. Sixteen dyads completed 15-min naturalistic conversations and self-reported their engagement on a visual analog scale every 60 s. Four physiological signals (electrocardiography, skin conductance, respiration, skin temperature) were recorded, and both individual physiological features (e.g., each participant's heart rate) and synchrony features (indicating degree of physiological similarity between two participants) were extracted. Multiple regression algorithms were used to estimate self-reported engagement based on physiological features using either leave-interval-out crossvalidation (training on 14 60-s intervals from a dyad and testing on the 15th interval from the same dyad) or leave-dyad-out crossvalidation (training on 15 dyads and testing on the 16th). In leave-interval-out crossvalidation, the regression algorithms achieved accuracy similar to a 'baseline' estimator that simply took the median engagement of the other 14 intervals. In leave-dyad-out crossvalidation, machine learning achieved a slightly higher accuracy than the baseline estimator and higher accuracy than an independent human observer. Secondary analyses showed that removing synchrony features and personality characteristics from the input dataset negatively impacted estimation accuracy and that engagement estimation error was correlated with personality traits. Results demonstrate the feasibility of dynamically estimating interpersonal engagement during naturalistic conversation using physiological measurements, which has potential applications in both conversation monitoring and conversation enhancement. However, as many of our estimation errors are difficult to contextualize, further work is needed to determine acceptable estimation accuracies.

Spatial Connectivity and Temporal Dynamic Functional Network Connectivity of Musical Emotions Evoked by Dynamically Changing Tempo

Music tempo is closely connected to listeners' musical emotion and multifunctional neural activities. Music with increasing tempo evokes higher emotional responses and music with decreasing tempo enhances relaxation. However, the neural substrate of emotion evoked by dynamically changing tempo is still unclear. To investigate the spatial connectivity and temporal dynamic functional network connectivity (dFNC) of musical emotion evoked by dynamically changing tempo, we collected dynamic emotional ratings and conducted group independent component analysis (ICA), sliding time window correlations, and k-means clustering to assess the FNC of emotion evoked by music with decreasing tempo (180-65 bpm) and increasing tempo (60-180 bpm). Music with decreasing tempo (with more stable dynamic valences) evoked higher valence than increasing tempo both with stronger independent components (ICs) in the default mode network (DMN) and sensorimotor network (SMN). The dFNC analysis showed that with time-decreasing FNC across the whole brain, emotion evoked by decreasing music was associated with strong spatial connectivity within the DMN and SMN. Meanwhile, it was associated with strong FNC between the DMN-frontoparietal network (FPN) and DMN-cingulate-opercular network (CON). The paired t-test showed that music with a decreasing tempo evokes stronger activation of ICs within DMN and SMN than that with an increasing tempo, which indicated that faster music is more likely to enhance listeners' emotions with multifunctional brain activities even when the tempo is slowing down. With increasing FNC across the whole brain, music with an increasing tempo was associated with strong connectivity within FPN; time-decreasing connectivity was found within CON, SMN, VIS, and between CON and SMN, which explained its unstable valence during the dynamic valence rating. Overall, the FNC can help uncover the spatial and temporal neural substrates of musical emotions evoked by dynamically changing tempi.

A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams

Neuroforecasting predicts population-wide choices based on neural data of individuals and can be used, for example, in neuromarketing to estimate campaign successes. To deliver true value, the brain activity metrics should deliver predictive value above and beyond traditional stated preferences. Evidence from movie trailer research has proposed neural synchrony, which compares the similarity of brain responses across participants and has shown to be a promising tool in neuroforecasting for movie popularity. The music industry might also benefit from these increasingly accurate success predictors, but only one study has been forecasting music popularity, using functional magnetic resonance imaging measures. Current research validates the strength of neural synchrony as a predictive measure for popularity of music, making use of electroencephalogram to capture moment-to-moment neural similarity between respondents while they listen to music. Neural synchrony is demonstrated to be a significant predictor for public appreciation on Spotify 3 weeks and 10 months after the release of the albums, especially when combined with the release of a single. On an individual level, other brain measures were shown to relate to individual subjective likeability ratings, including Frontal Alpha Asymmetry and engagement when combined with the factors artist and single release. Our results show the predictive value of brain activity measures outperforms stated preferences. Especially, neural synchrony carries high predictive value for the popularity on Spotify, providing the music industry with an essential asset for efficient decision making and investments, in addition to other practical implications that include neuromarketing and advertising industries.

Dynamic functional network connectivity associated with musical emotions evoked by different tempi

Background：Music tempo has strong clinical maneuverability and positive emotional effect in music therapy, which can directly evoke multiple emotions and dynamic neural changes in the whole-brain. However, the precise relationship between music tempo and its emotional effects remains unclear. The present study aimed to investigate the dynamic functional network connectivity (dFNC) associated with emotions elicited by music at different tempi.

METHODS

We obtained emotion ratings of fast- (155-170 bpm), middle- (90 bpm), and slow-tempo (50-60 bpm) piano music from 40 participants both during and after functional magnetic resonance imaging (fMRI). Group independent component analysis (ICA), sliding time window correlations, and k-means clustering were used to assess dFNC of fMRI data. Paired t-tests were conducted to compare the difference of neural networks.

RESULTS

(1) Fast music was associated with higher ratings of emotional valence and arousal, which were accompanied with increasing dFNC between somatomotor (SM) and cingulo-opercular (CO) networks and decreasing dFNC between fronto-parietal and SM networks. (2) Even with stronger activation in auditory (AUD) networks, slow music was associated with weaker emotion than fast music, with decreasing FNC across the brain and the participation of default mode (DM). (3) Middle-tempo music elicited moderate emotional activation with the most stable dFNC in the whole brain.

CONCLUSION

Faster music increases neural activity in the SM and CO regions, increasing the intensity of the emotional experience. In contrast, slower music was associated with decreasing engagement of AUD and stable engagement of DM, resulting in a weak emotional experience. These findings suggested that the time-varying aspects of functional connectivity can help to uncover the dynamic neural substrates of tempo-evoked emotion while listening to music.

Decreased intersubject synchrony in dynamic valence ratings of sad movie contents in dysphoric individuals

Emotional reactions to movies are typically similar between people. However, depressive symptoms decrease synchrony in brain responses. Less is known about the effect of depressive symptoms on intersubject synchrony in conscious stimulus-related processing. In this study, we presented amusing, sad and fearful movie clips to dysphoric individuals (those with elevated depressive symptoms) and control participants to dynamically rate the clips' valences (positive vs. negative). We analysed both the valence ratings' mean values and intersubject correlation (ISC). We used electrodermal activity (EDA) to complement the measurement in a separate session. There were no group differences in either the EDA or mean valence rating values for each movie type. As expected, the valence ratings' ISC was lower in the dysphoric than the control group, specifically for the sad movie clips. In addition, there was a negative relationship between the valence ratings' ISC and depressive symptoms for sad movie clips in the full sample. The results are discussed in the context of the negative attentional bias in depression. The findings extend previous brain activity results of ISC by showing that depressive symptoms also increase variance in conscious ratings of valence of stimuli in a mood-congruent manner.

Naturalistic Stimuli in Affective Neuroimaging: A Review

Naturalistic stimuli such as movies, music, and spoken and written stories elicit strong emotions and allow brain imaging of emotions in close-to-real-life conditions. Emotions are multi-component phenomena: relevant stimuli lead to automatic changes in multiple functional components including perception, physiology, behavior, and conscious experiences. Brain activity during naturalistic stimuli reflects all these changes, suggesting that parsing emotion-related processing during such complex stimulation is not a straightforward task. Here, I review affective neuroimaging studies that have employed naturalistic stimuli to study emotional processing, focusing especially on experienced emotions. I argue that to investigate emotions with naturalistic stimuli, we need to define and extract emotion features from both the stimulus and the observer.

The Embodied-Enactive-Interactive Brain: Bridging Neuroscience and Creative Arts Therapies

The recognition and incorporation of evidence-based neuroscientific concepts into creative arts therapeutic knowledge and practice seem valuable and advantageous for the purpose of integration and professional development. Moreover, exhilarating insights from the field of neuroscience coincide with the nature, conceptualization, goals, and methods of Creative Arts Therapies (CATs), enabling comprehensive understandings of the clinical landscape, from a translational perspective. This paper contextualizes and discusses dynamic brain functions that have been suggested to lie at the heart of intra- and inter-personal processes. Touching upon fundamental aspects of the self and self-other interaction, the state-of-the-art neuroscientific-informed views will shed light on mechanisms of the embodied, predictive and relational brain. The conceptual analysis introduces and interweaves the following contemporary perspectives of brain function: firstly, the grounding of mental activity in the lived, bodily experience will be delineated; secondly, the enactive account of internal models, or generative predictive representations, shaped by experience, will be defined and extensively deliberated; and thirdly, the interpersonal simulation and synchronization mechanisms that support empathy and mentalization will be thoroughly considered. Throughout the paper, the cross-talks between the brain and the body, within the brain through functionally connected neural networks and in the context of agent-environment dynamics, will be addressed. These communicative patterns will be elaborated on to unfold psychophysiological linkage, as well as psychopathological shifts, concluding with the neuroplastic change associated with the formulation of CATs. The manuscript suggests an integrative view of the brain-body-mind in contexts relevant to the therapeutic potential of the expressive creative arts and the main avenues by which neuroscience may ground, enlighten and enrich the clinical psychotherapeutic practice.

Frontotemporal dementia, music perception and social cognition share neurobiological circuits: A meta-analysis

Frontotemporal dementia (FTD) is a neurodegenerative disease that presents with profound changes in social cognition. Music might be a sensitive probe for social cognition abilities, but underlying neurobiological substrates are unclear. We performed a meta-analysis of voxel-based morphometry studies in FTD patients and functional MRI studies for music perception and social cognition tasks in cognitively normal controls to identify robust patterns of atrophy (FTD) or activation (music perception or social cognition). Conjunction analyses were performed to identify overlapping brain regions. In total 303 articles were included: 53 for FTD (n = 1153 patients, 42.5% female; 1337 controls, 53.8% female), 28 for music perception (n = 540, 51.8% female) and 222 for social cognition in controls (n = 5664, 50.2% female). We observed considerable overlap in atrophy patterns associated with FTD, and functional activation associated with music perception and social cognition, mostly encompassing the ventral language network. We further observed overlap across all three modalities in mesolimbic, basal forebrain and striatal regions. The results of our meta-analysis suggest that music perception and social cognition share neurobiological circuits that are affected in FTD. This supports the idea that music might be a sensitive probe for social cognition abilities with implications for diagnosis and monitoring.

Links Between the Neurobiology of Oxytocin and Human Musicality

The human species possesses two complementary, yet distinct, universal communication systems—language and music. Functional imaging studies have revealed that some core elements of these two systems are processed in closely related brain regions, but there are also clear differences in brain circuitry that likely underlie differences in functionality. Music affects many aspects of human behavior, especially in encouraging prosocial interactions and promoting trust and cooperation within groups of culturally compatible but not necessarily genetically related individuals. Music, presumably via its impact on the limbic system, is also rewarding and motivating, and music can facilitate aspects of learning and memory. In this review these special characteristics of music are considered in light of recent research on the neuroscience of the peptide oxytocin, a hormone that has both peripheral and central actions, that plays a role in many complex human behaviors, and whose expression has recently been reported to be affected by music-related activities. I will first briefly discuss what is currently known about the peptide’s physiological actions on neurons and its interactions with other neuromodulator systems, then summarize recent advances in our knowledge of the distribution of oxytocin and its receptor (OXTR) in the human brain. Next, the complex links between oxytocin and various social behaviors in humans are considered. First, how endogenous oxytocin levels relate to individual personality traits, and then how exogenous, intranasal application of oxytocin affects behaviors such as trust, empathy, reciprocity, group conformity, anxiety, and overall social decision making under different environmental conditions. It is argued that many of these characteristics of oxytocin biology closely mirror the diverse effects that music has on human cognition and emotion, providing a link to the important role music has played throughout human evolutionary history and helping to explain why music remains a special prosocial human asset. Finally, it is suggested that there is a potential synergy in combining oxytocin- and music-based strategies to improve general health and aid in the treatment of various neurological dysfunctions.

Inter-subject Similarity of Brain Activity in Expert Musicians After Multimodal Learning: A Behavioral and Neuroimaging Study on Learning to Play a Piano Sonata

Human behavior is inherently multimodal and relies on sensorimotor integration. This is evident when pianists exhibit activity in motor and premotor cortices, as part of a dorsal pathway, while listening to a familiar piece of music, or when naïve participants learn to play simple patterns on the piano. Here we investigated the interaction between multimodal learning and dorsal-stream activity over the course of four weeks in ten skilled pianists by adopting a naturalistic data-driven analysis approach. We presented the pianists with audio-only, video-only and audiovisual recordings of a piano sonata during functional magnetic resonance imaging (fMRI) before and after they had learned to play the sonata by heart for a total of four weeks. We followed the learning process and its outcome with questionnaires administered to the pianists, one piano instructor following their training, and seven external expert judges. The similarity of the pianists' brain activity during stimulus presentations was examined before and after learning by means of inter-subject correlation (ISC) analysis. After learning, an increased ISC was found in the pianists while watching the audiovisual performance, particularly in motor and premotor regions of the dorsal stream. While these brain structures have previously been associated with learning simple audio-motor sequences, our findings are the first to suggest their involvement in learning a complex and demanding audiovisual-motor task. Moreover, the most motivated learners and the best performers of the sonata showed ISC in the dorsal stream and in the reward brain network.