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

The neuroscience of music – towards ecological validity

Studies in the neuroscience of music gained momentum in the 1990s as an integrated part of the well-controlled experimental research tradition. However, during the past two decades, these studies have moved toward more naturalistic, ecologically valid paradigms. Here, I introduce this move in three frameworks: (i) sound stimulation and empirical paradigms, (ii) study participants, and (iii) methods and contexts of data acquisition. I wish to provide a narrative historical overview of the development of the field and, in parallel, to stimulate innovative thinking to further advance the ecological validity of the studies without overlooking experimental rigor.

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.

Brain oscillation recordings of the audience in a live concert-like setting

There are only a few previous EEG studies that were conducted while the audience is listening to live music. However, in laboratory settings using music recordings, EEG frequency bands theta and alpha are connected to music improvisation and creativity. Here, we measured EEG of the audience in a concert-like setting outside the laboratory and compared the theta and alpha power evoked by partly improvised versus regularly performed familiar versus unfamiliar live classical music. To this end, partly improvised and regular versions of pieces by Bach (familiar) and Melartin (unfamiliar) were performed live by a chamber trio. EEG data from left and right frontal and central regions of interest were analysed to define theta and alpha power during each performance. After the performances, the participants rated how improvised and attractive each of the performances were. They also gave their affective ratings before and after each performance. We found that theta power was enhanced during the familiar improvised Bach piece and the unfamiliar improvised Melartin piece when compared with the performance of the same piece performed in a regular manner. Alpha power was not modulated by manner of performance or by familiarity of the piece. Listeners rated partly improvised performances of a familiar Bach and unfamiliar Melartin piece as more improvisatory and innovative than the regular performances. They also indicated more joy and less sadness after listening to the unfamiliar improvised piece of Melartin and less fearful and more enthusiastic after listening to the regular version of Melartin than before listening. Thus, according to our results, it is possible to study listeners’ brain functions with EEG during live music performances outside the laboratory, with theta activity reflecting the presence of improvisation in the performances.

A Practice-Inspired Mindset for Researching the Psychophysiological and Medical Health Effects of Recreational Dance (Dance Sport)

“Dance” has been associated with many psychophysiological and medical health effects. However, varying definitions of what constitute “dance” have led to a rather heterogenous body of evidence about such potential effects, leaving the picture piecemeal at best. It remains unclear what exact parameters may be driving positive effects. We believe that this heterogeneity of evidence is partly due to a lack of a clear definition of dance for such empirical purposes. A differentiation is needed between (a) the effects on the individual when the activity of “dancing” is enjoyed as a dancer within different dance domains (e.g., professional/”high-art” type of dance, erotic dance, religious dance, club dancing, Dance Movement Therapy (DMT), and what is commonly known as hobby, recreational or social dance), and (b) the effects on the individual within these different domains, as a dancer of the different dance styles (solo dance, partnering dance, group dance; and all the different styles within these). Another separate category of dance engagement is, not as a dancer, but as a spectator of all of the above. “Watching dance” as part of an audience has its own set of psychophysiological and neurocognitive effects on the individual, and depends on the context where dance is witnessed. With the help of dance professionals, we first outline some different dance domains and dance styles, and outline aspects that differentiate them, and that may, therefore, cause differential empirical findings when compared regardless (e.g., amount of interpersonal contact, physical exertion, context, cognitive demand, type of movements, complexity of technique and ratio of choreography/improvisation). Then, we outline commonalities between all dance styles. We identify six basic components that are part of any dance practice, as part of a continuum, and review and discuss available research for each of them concerning the possible health and wellbeing effects of each of these components, and how they may relate to the psychophysiological and health effects that are reported for “dancing”: (1) rhythm and music, (2) sociality, (3) technique and fitness, (4) connection and connectedness (self-intimation), (5) flow and mindfulness, (6) aesthetic emotions and imagination. Future research efforts might take into account the important differences between types of dance activities, as well as the six components, for a more targeted assessment of how “dancing” affects the human body.

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.

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.

Evaluation of Contralateral Suppression of Otoacoustic Emissions in Bharatanatyam Dancers and Non-Dancers

OBJECTIVES

There is limited literature regarding the objective estimation of auditory attention in healthy individuals who regularly practice dance. This study attempted to evaluate the contralateral suppression of otoacoustic emissions (OAE) in Bharatanatyam dancers and non-dancers.

MATERIALS AND METHODS

The study included40 adults (20 dancers and 20 non-dancers) with normal hearing. The differences in the contralateral suppression of distortion product OAE between the groups were compared.

RESULTS

The results of the present study revealed that there was an increased amount of suppression of OAE in dancers compared with non-dancers. It suggests that dance practice enhances sensory perception and improves auditory attention. The constant practice of dance could have led to plasticity of the efferent auditory system.

CONCLUSION

Thus, dance training may be used to strengthen efferent auditory system functioning. However, further studies witha larger sample size are essential for better generalization of the results.

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.

Naturalistic music and dance: Cortical phase synchrony in musicians and dancers

Expertise in music has been investigated for decades and the results have been applied not only in composition, performance and music education, but also in understanding brain plasticity in a larger context. Several studies have revealed a strong connection between auditory and motor processes and listening to and performing music, and music imagination. Recently, as a logical next step in music and movement, the cognitive and affective neurosciences have been directed towards expertise in dance. To understand the versatile and overlapping processes during artistic stimuli, such as music and dance, it is necessary to study them with continuous naturalistic stimuli. Thus, we used long excerpts from the contemporary dance piece Carmen presented with and without music to professional dancers, musicians, and laymen in an EEG laboratory. We were interested in the cortical phase synchrony within each participant group over several frequency bands during uni- and multimodal processing. Dancers had strengthened theta and gamma synchrony during music relative to silence and silent dance, whereas the presence of music decreased systematically the alpha and beta synchrony in musicians. Laymen were the only group of participants with significant results related to dance. Future studies are required to understand whether these results are related to some other factor (such as familiarity to the stimuli), or if our results reveal a new point of view to dance observation and expertise.

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.