Event-related brain responses while listening to entire pieces of music

Mismatch negativity-stimulation paradigms in past and in future

Mismatch negativity (MMN) studies were initiated as part of a well-controlled experimental research tradition with the aim to identify some key principles of auditory processing and memory. During the past two decades, empirical paradigms have moved toward more ecologically valid ones while retaining rigid experimental control. In this paper, I will introduce this development of MMN stimulation paradigms starting from the paradigms used in basic science and then moving to paradigms that have been particularly relevant for studies on music learning and musical expertise. Via these historical and thematic perspectives, I wish to stimulate paradigm development further to meet the demands of naturalistic ecologically valid studies also when using MMN in the context of event-related potential technique that necessarily requires averaging across several stimulus presentations.

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.

The early adolescent brain on music: Analysis of functional dynamics reveals engagement of orbitofrontal cortex reward system

Music listening plays a pivotal role for children and adolescents, yet it remains unclear how music modulates brain activity at the level of functional networks in this young population. Analysing the dynamics of brain networks occurring and dissolving over time in response to music can provide a better understanding of the neural underpinning of music listening. We collected functional magnetic resonance imaging (fMRI) data from 17 preadolescents aged 10-11 years while listening to two similar music pieces separated by periods without music. We subsequently tracked the occurrence of functional brain networks over the recording time using a recent method that detects recurrent patterns of phase-locking in the fMRI signals: the leading eigenvector dynamics analysis (LEiDA). The probabilities of occurrence and switching profiles of different functional networks were compared between periods of music and no music. Our results showed significantly increased occurrence of a specific functional network during the two music pieces compared to no music, involving the medial orbitofrontal and ventromedial prefrontal cortices-a brain subsystem associated to reward processing. Moreover, the higher the musical reward sensitivity of the preadolescents, the more this network was preceded by a pattern involving the insula. Our findings highlight the involvement of a brain subsystem associated with hedonic and emotional processing during music listening in the early adolescent brain. These results offer novel insight into the neural underpinnings of musical reward in early adolescence, improving our understanding of the important role and the potential benefits of music at this delicate age.

Benefits of Tango Therapy in Alleviating the Motor and Non-Motor Symptoms of Parkinson’s Disease Patients—A Narrative Review

The present study examines the efficacy of tango therapy on motor and non-motor symptomatology in Parkinson’s disease, as detailed in articles published over the previous four decades (1980–2022). All data was collected using PubMed, Google Scholar, Web of Science, and Science Direct. The present descriptive study outlines the advantages of tango in the rehabilitation of Parkinson’s disease’s motor and non-motor symptoms. Numerous studies have been conducted to determine the usefulness of tango for people with PD. Information from various research is critical for determining if tango is a useful supplementary therapy for the variety of symptoms related to Parkinson’s disease. The purpose of this review was to describe the present state of research on this subject. Thus, the objective of this review is to promote awareness of tango therapy’s therapeutic benefits for Parkinson’s disease.

Prediction under uncertainty: Dissociating sensory from cognitive expectations in highly uncertain musical contexts

Predictive models in the brain rely on the continuous extraction of regularities from the environment. These models are thought to be updated by novel information, as reflected in prediction error responses such as the mismatch negativity (MMN). However, although in real life individuals often face situations in which uncertainty prevails, it remains unclear whether and how predictive models emerge in high-uncertainty contexts. Recent research suggests that uncertainty affects the magnitude of MMN responses in the context of music listening. However, musical predictions are typically studied with MMN stimulation paradigms based on Western tonal music, which are characterized by relatively high predictability. Hence, we developed an MMN paradigm to investigate how the high uncertainty of atonal music modulates predictive processes as indexed by the MMN and behavior. Using MEG in a group of 20 subjects without musical training, we demonstrate that the magnetic MMN in response to pitch, intensity, timbre, and location deviants is evoked in both tonal and atonal melodies, with no significant differences between conditions. In contrast, in a separate behavioral experiment involving 39 non-musicians, participants detected pitch deviants more accurately and rated confidence higher in the tonal than in the atonal musical context. These results indicate that contextual tonal uncertainty modulates processing stages in which conscious awareness is involved, although deviants robustly elicit low-level pre-attentive responses such as the MMN. The achievement of robust MMN responses, despite high tonal uncertainty, is relevant for future studies comparing groups of listeners' MMN responses to increasingly ecological music stimuli.

Neural Correlates of Music Listening: Does the Music Matter?

The last decades have seen a proliferation of music and brain studies, with a major focus on plastic changes as the outcome of continuous and prolonged engagement with music. Thanks to the advent of neuroaesthetics, research on music cognition has broadened its scope by considering the multifarious phenomenon of listening in all its forms, including incidental listening up to the skillful attentive listening of experts, and all its possible effects. These latter range from objective and sensorial effects directly linked to the acoustic features of the music to the subjectively affective and even transformational effects for the listener. Of special importance is the finding that neural activity in the reward circuit of the brain is a key component of a conscious listening experience. We propose that the connection between music and the reward system makes music listening a gate towards not only hedonia but also eudaimonia, namely a life well lived, full of meaning that aims at realizing one's own "daimon" or true nature. It is argued, further, that music listening, even when conceptualized in this aesthetic and eudaimonic framework, remains a learnable skill that changes the way brain structures respond to sounds and how they interact with each other.

Study of Auditory Brain Cognition Laws-Based Recognition Method of Automobile Sound Quality

The research shows that subjective feelings of people, such as emotions and fatigue, can be objectively reflected by electroencephalography (EEG) physiological signals Thus, an evaluation method based on EEG, which is used to explore auditory brain cognition laws, is introduced in this study. The brain cognition laws are summarized by analyzing the EEG power topographic map under the stimulation of three kinds of automobile sound, namely, quality of comfort, powerfulness, and acceleration. Then, the EEG features of the subjects are classified through a machine learning algorithm, by which the recognition of diversified automobile sound is realized. In addition, the Kalman smoothing and minimal redundancy maximal relevance (mRMR) algorithm is used to improve the recognition accuracy. The results show that there are differences in the neural characteristics of diversified automobile sound quality, with a positive correlation between EEG energy and sound intensity. Furthermore, by using the Kalman smoothing and mRMR algorithm, recognition accuracy is improved, and the amount of calculation is reduced. The novel idea and method to explore the cognitive laws of automobile sound quality from the field of brain-computer interface technology are provided in this study.

Psychological, psychophysiological and behavioural effects of participant-selected vs. researcher-selected music in simulated urban driving

We investigated the effect of participant-selected (PSel) and researcher-selected (RSel) music on urban driving behaviour in young men (N = 27; M_age = 20.6 years, SD = 1.9 years). A counterbalanced, within-subjects design was used with four simulated driving conditions: PSel fast-tempo music, PSel slow-tempo music, RSel music and an urban traffic-noise control. The between-subjects variable of personality (introverts vs. extroverts) was explored. The presence of PSel slow-tempo music and RSel music optimised affective valence and arousal for urban driving. NASA Task Load Index scores indicated that the urban traffic-noise control increased mental demand compared to PSel slow-tempo music. In the PSel slow-tempo condition, less use was made of the brake pedal. When compared to extroverts, introverts recorded lower mean speed and attracted lower risk ratings under PSel slow-tempo music. The utility of PSel slow-tempo and RSel music was demonstrated in terms of optimising affective state for simulated urban driving.

NeuroDante: Poetry Mentally Engages More Experts but Moves More Non-Experts, and for Both the Cerebral Approach Tendency Goes Hand in Hand with the Cerebral Effort

Neuroaesthetics, the science studying the biological underpinnings of aesthetic experience, recently extended its area of investigation to literary art; this was the humus where neurocognitive poetics blossomed. Divina Commedia represents one of the most important, famous and studied poems worldwide. Poetry stimuli are characterized by elements (meter and rhyme) promoting the processing fluency, a core aspect of neuroaesthetics theories. In addition, given the evidence of different neurophysiological reactions between experts and non-experts in response to artistic stimuli, the aim of the present study was to investigate, in poetry, a different neurophysiological cognitive and emotional reaction between Literature (L) and Non-Literature (NL) students. A further aim was to investigate whether neurophysiological underpinnings would support explanation of behavioral data. Investigation methods employed: self-report assessments (recognition, appreciation, content recall) and neurophysiological indexes (approach/withdrawal (AW), cerebral effort (CE) and galvanic skin response (GSR)). The main behavioral results, according to fluency theories in aesthetics, suggested in the NL but not in the L group that the appreciation/liking went hand by hand with the self-declared recognition and with the content recall. The main neurophysiological results were: (i) higher galvanic skin response in NL, whilst higher CE values in L; (ii) a positive correlation between AW and CE indexes in both groups. The present results extended previous evidence relative to figurative art also to auditory poetry stimuli, suggesting an emotional attenuation “expertise-specific” showed by experts, but increased cognitive processing in response to the stimuli.

Extracting human cortical responses to sound onsets and acoustic feature changes in real music, and their relation to event rate

Evoked cortical responses (ERs) have mainly been studied in controlled experiments using simplified stimuli. Though, an outstanding question is how the human cortex responds to the complex stimuli encountered in realistic situations. Few electroencephalography (EEG) studies have used Music Information Retrieval (MIR) tools to extract cortical P1/N1/P2 to acoustical changes in real music. However, less than ten events per music piece could be detected leading to ERs due to limitations in automatic detection of sound onsets. Also, the factors influencing a successful extraction of the ERs have not been identified. Finally, previous studies did not localize the sources of the cortical generators. This study is based on an EEG/MEG dataset from 48 healthy normal hearing participants listening to three real music pieces. Acoustic features were computed from the audio signal of the music with the MIR Toolbox. To overcome limits in automatic methods, sound onsets were also manually detected. The chance of obtaining detectable ERs based on ten randomly picked onset points was less than 1:10,000. For the first time, we show that naturalistic P1/N1/P2 ERs can be reliably measured across 100 manually identified sound onsets, substantially improving the signal-to-noise level compared to <10 trials. More ERs were measurable in musical sections with slow event rates (0.2 Hz-2.5 Hz) than with fast event rates (>2.5 Hz). Furthermore, during monophonic sections of the music only P1/P2 were measurable, and during polyphonic sections only N1. Finally, MEG source analysis revealed that naturalistic P2 is located in core areas of the auditory cortex.

Neural Dynamics of Cognitive Control in Various Types of Incongruence

Conflict-control is a core function of cognitive control. Although numerous studies have considered cognitive control to be domain-general, the shared and distinct brain responses to different types of incongruence or conflict remain unclear. Using a hybrid flanker task, the present study explored the temporal dynamics of brain activation to three types of incongruence: flanker interference, rule-based response switch (rule-switch), and action-based response switch (response-alternation). The results showed that: (1) all three types of incongruence evoked larger N2 amplitudes than the congruent condition in the frontal region, with the N2 amplitudes and topographical distribution of the N2 effect differing between the different types of incongruence; and (2) in the P300 time window, the flanker interference condition yielded the most delayed P300 latency, whereas the rule-switch and response-alternation conditions yielded smaller P300 amplitudes with a longer interval from P300 peak to a keypress. These findings suggest that different types of incongruence are first monitored similarly by the cognitive control system and then resolved differently.

Exploring Frequency-Dependent Brain Networks from Ongoing EEG Using Spatial ICA During Music Listening

Recently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during freely listening to music. We used a data-driven method that combined music information retrieval with spatial Fourier Independent Components Analysis (spatial Fourier-ICA) to probe the interplay between the spatial profiles and the spectral patterns of the brain network emerging from music listening. Correlation analysis was performed between time courses of brain networks extracted from EEG data and musical feature time series extracted from music stimuli to derive the musical feature related oscillatory patterns in the listening brain. We found brain networks of musical feature processing were frequency-dependent. Musical feature time series, especially fluctuation centroid and key feature, were associated with an increased beta activation in the bilateral superior temporal gyrus. An increased alpha oscillation in the bilateral occipital cortex emerged during music listening, which was consistent with alpha functional suppression hypothesis in task-irrelevant regions. We also observed an increased delta-beta oscillatory activity in the prefrontal cortex associated with musical feature processing. In addition to these findings, the proposed method seems valuable for characterizing the large-scale frequency-dependent brain activity engaged in musical feature processing.

The CI MuMuFe - A New MMN Paradigm for Measuring Music Discrimination in Electric Hearing

Cochlear implants (CIs) allow good perception of speech while music listening is unsatisfactory, leading to reduced music enjoyment. Hence, a number of ongoing efforts aim to improve music perception with a CI. Regardless of the nature of these efforts, effect measurements must be valid and reliable. While auditory skills are typically examined by behavioral methods, recording of the mismatch negativity (MMN) response, using electroencephalography (EEG), has recently been applied successfully as a supplementary objective measure. Eleven adult CI users and 14 normally hearing (NH) controls took part in the present study. To measure their detailed discrimination of fundamental features of music we applied a new multifeature MMN-paradigm which presented four music deviants at four levels of magnitude, incorporating a novel "no-standard" approach to be tested with CI users for the first time. A supplementary test measured behavioral discrimination of the same deviants and levels. The MMN-paradigm elicited significant MMN responses to all levels of deviants in both groups. Furthermore, the CI-users' MMN amplitudes and latencies were not significantly different from those of NH controls. Both groups showed MMN strength that was in overall alignment with the deviation magnitude. In CI users, however, discrimination of pitch levels remained undifferentiated. On average, CI users' behavioral performance was significantly below that of the NH group, mainly due to poor pitch discrimination. Although no significant effects were found, CI users' behavioral results tended to be in accordance with deviation magnitude, most prominently manifested in discrimination of the rhythm deviant. In summary, the study indicates that CI users may be able to discriminate subtle changes in basic musical features both in terms of automatic neural responses and of attended behavioral detection. Despite high complexity, the new CI MuMuFe paradigm and the "no-standard" approach provided reliable results, suggesting that it may serve as a relevant tool in future CI research. For clinical use, future studies should investigate the possibility of applying the paradigm with the purpose of assessing discrimination skills not only at the group level but also at the individual level.

Atonal Music: Can Uncertainty Lead to Pleasure?

In recent years, the field of neuroaesthetics has gained considerable attention with music being a favored object of study. The majority of studies concerning music have, however, focused on the experience of Western tonal music (TM), which is characterized by tonal hierarchical organization, a high degree of consonance, and a tendency to provide the listener with a tonic as a reference point during the listening experience. We argue that a narrow focus on Western TM may have led to a one-sided view regarding the qualities of the aesthetic experience of music since Western art music from the 20th and 21st century like atonal music (AM) – while lacking a tonal hierarchical structure, and while being highly dissonant and hard to predict – is nevertheless enjoyed by a group of avid listeners. We propose a research focus that investigates, in particular, the experience of AM as a novel and compelling way with which to enhance our understanding of both the aesthetic appreciation of music and the role of predictive models in the context of musical pleasure. We use music theoretical analysis and music information retrieval methods to demonstrate how AM presents the listener with a highly uncertain auditory environment. Specifically, an analysis of a corpus of 100 musical segments is used to illustrate how tonal classical music and AM differ quantitatively in terms of both key and pulse clarity values. We then examine person related, extrinsic and intrinsic factors, that point to potential mechanisms underlying the appreciation and pleasure derived from AM. We argue that personality traits like “openness to experience,” the framing of AM as art, and the mere exposure effect are key components of such mechanisms. We further argue that neural correlates of uncertainty estimation could represent a central mechanism for engaging with AM and that such contexts engender a comparatively weak predictive model in the listener. Finally we argue that in such uncertain contexts, correct predictions may be more subjectively rewarding than prediction errors since they signal to the individual that their predictive model is improving.

A Systematic Review for Human EEG Brain Signals Based Emotion Classification, Feature Extraction, Brain Condition, Group Comparison

The study of electroencephalography (EEG) signals is not a new topic. However, the analysis of human emotions upon exposure to music considered as important direction. Although distributed in various academic databases, research on this concept is limited. To extend research in this area, the researchers explored and analysed the academic articles published within the mentioned scope. Thus, in this paper a systematic review is carried out to map and draw the research scenery for EEG human emotion into a taxonomy. Systematically searched all articles about the, EEG human emotion based music in three main databases: ScienceDirect, Web of Science and IEEE Xplore from 1999 to 2016. These databases feature academic studies that used EEG to measure brain signals, with a focus on the effects of music on human emotions. The screening and filtering of articles were performed in three iterations. In the first iteration, duplicate articles were excluded. In the second iteration, the articles were filtered according to their titles and abstracts, and articles outside of the scope of our domain were excluded. In the third iteration, the articles were filtered by reading the full text and excluding articles outside of the scope of our domain and which do not meet our criteria. Based on inclusion and exclusion criteria, 100 articles were selected and separated into five classes. The first class includes 39 articles (39%) consists of emotion, wherein various emotions are classified using artificial intelligence (AI). The second class includes 21 articles (21%) is composed of studies that use EEG techniques. This class is named 'brain condition'. The third class includes eight articles (8%) is related to feature extraction, which is a step before emotion classification. That this process makes use of classifiers should be noted. However, these articles are not listed under the first class because these eight articles focus on feature extraction rather than classifier accuracy. The fourth class includes 26 articles (26%) comprises studies that compare between or among two or more groups to identify and discover human emotion-based EEG. The final class includes six articles (6%) represents articles that study music as a stimulus and its impact on brain signals. Then, discussed the five main categories which are action types, age of the participants, and number size of the participants, duration of recording and listening to music and lastly countries or authors' nationality that published these previous studies. it afterward recognizes the main characteristics of this promising area of science in: motivation of using EEG process for measuring human brain signals, open challenges obstructing employment and recommendations to improve the utilization of EEG process.

Coupling of Action-Perception Brain Networks during Musical Pulse Processing: Evidence from Region-of-Interest-Based Independent Component Analysis

Our sense of rhythm relies on orchestrated activity of several cerebral and cerebellar structures. Although functional connectivity studies have advanced our understanding of rhythm perception, this phenomenon has not been sufficiently studied as a function of musical training and beyond the General Linear Model (GLM) approach. Here, we studied pulse clarity processing during naturalistic music listening using a data-driven approach (independent component analysis; ICA). Participants' (18 musicians and 18 controls) functional magnetic resonance imaging (fMRI) responses were acquired while listening to music. A targeted region of interest (ROI) related to pulse clarity processing was defined, comprising auditory, somatomotor, basal ganglia, and cerebellar areas. The ICA decomposition was performed under different model orders, i.e., under a varying number of assumed independent sources, to avoid relying on prior model order assumptions. The components best predicted by a measure of the pulse clarity of the music, extracted computationally from the musical stimulus, were identified. Their corresponding spatial maps uncovered a network of auditory (perception) and motor (action) areas in an excitatory-inhibitory relationship at lower model orders, while mainly constrained to the auditory areas at higher model orders. Results revealed (a) a strengthened functional integration of action-perception networks associated with pulse clarity perception hidden from GLM analyses, and (b) group differences between musicians and non-musicians in pulse clarity processing, suggesting lifelong musical training as an important factor that may influence beat processing.

Global Sensory Qualities and Aesthetic Experience in Music

A well-known tradition in the study of visual aesthetics holds that the experience of visual beauty is grounded in global computational or statistical properties of the stimulus, for example, scale-invariant Fourier spectrum or self-similarity. Some approaches rely on neural mechanisms, such as efficient computation, processing fluency, or the responsiveness of the cells in the primary visual cortex. These proposals are united by the fact that the contributing factors are hypothesized to be global (i.e., they concern the percept as a whole), formal or non-conceptual (i.e., they concern form instead of content), computational and/or statistical, and based on relatively low-level sensory properties. Here we consider that the study of aesthetic responses to music could benefit from the same approach. Thus, along with local features such as pitch, tuning, consonance/dissonance, harmony, timbre, or beat, also global sonic properties could be viewed as contributing toward creating an aesthetic musical experience. Several such properties are discussed and their neural implementation is reviewed in the light of recent advances in neuroaesthetics.

Early auditory processing in musicians and dancers during a contemporary dance piece

The neural responses to simple tones and short sound sequences have been studied extensively. However, in reality the sounds surrounding us are spectrally and temporally complex, dynamic and overlapping. Thus, research using natural sounds is crucial in understanding the operation of the brain in its natural environment. Music is an excellent example of natural stimulation which, in addition to sensory responses, elicits vast cognitive and emotional processes in the brain. Here we show that the preattentive P50 response evoked by rapid increases in timbral brightness during continuous music is enhanced in dancers when compared to musicians and laymen. In dance, fast changes in brightness are often emphasized with a significant change in movement. In addition, the auditory N100 and P200 responses are suppressed and sped up in dancers, musicians and laymen when music is accompanied with a dance choreography. These results were obtained with a novel event-related potential (ERP) method for natural music. They suggest that we can begin studying the brain with long pieces of natural music using the ERP method of electroencephalography (EEG) as has already been done with functional magnetic resonance (fMRI), these two brain imaging methods complementing each other.