The effects of music on brain functional networks: a network analysis

The prevalence of alcohol references in music and their effect on people's drinking behavior: A systematic review and meta-analysis

Understanding the prevalence of alcohol references in music and their impact on alcohol drinking behavior is important given the increased accessibility to daily music listening with the proliferation of smart devices. In this review, we estimate the pooled prevalence of alcohol references in music and its association with drinking behavior. Systematic searches were conducted across four major databases (MEDLINE, PsycINFO, EMBASE, and CINHAL). Articles were selected following duplicate checking, title and abstract screening, and full-text review. Studies reporting the prevalence of alcohol-referencing music and/or investigating its association with drinking behavior were included. Pooled prevalence with 95% confidence intervals (CIs) were computed using a random effects model. Of 1007 articles identified, 26 met inclusion criteria and 23 studies comprising 12,224 songs were eligible for meta-analysis. The overall pooled prevalence of alcohol references in music (including lyrics and videos) was 24.0% (95% CI: 19.0%-29.0%). The pooled prevalence was 22.0% (95% CI: 16.0%-29.0%) for only lyrics, 25.0% (95% CI: 18.0%-33.0%) for only the visual elements of music videos, and 29.0% (95% CI: 21.0%-38.0%) for both the lyrical content and the visual components. Only three studies assessed the relationship between listening to music with alcohol references and drinking behavior, and all three reported a positive association. Whereas almost a quarter of all songs included references to alcohol, public health preventive measures are needed to reduce alcohol exposure from music. Future research is needed to understand fully the effect of music with alcohol references on drinking behavior.

The effects of mental fatigue on fine motor performance in humans and its neural network connectivity mechanism: a dart throwing study

While it is well known that mental fatigue impairs fine motor performance, the investigation into its neural basis remains scant. Here, we investigate the impact of mental fatigue on fine motor performance and explore its underlying neural network connectivity mechanisms. A total of 24 healthy male university students were recruited and randomly divided into two groups: a mental fatigue group (MF) and a control group (Control). Both groups completed 50 dart throws, while electroencephalography (EEG) data were collected. Following the Stroop intervention, participants in the MF group exhibited a decrease in Stroop task accuracy and throwing performance, and an increase in reaction time along with VAS and NASA scores. The EEG data during dart-throwing revealed that the network connectivity strength of theta oscillations in the frontal and left central regions was significantly higher in the MF group compared with the Control group, while the network connectivity strength of alpha oscillations in the left parietal region was significantly enhanced. The interregional connectivity within the theta and alpha rhythm bands, particularly in the frontal-central-parietal network connections, also showed a significant increase in the MF group. Mental fatigue impairs dart throwing performance and is accompanied by increased connectivity in alpha and theta.

Short-Term Effect of Auditory Stimulation on Neural Activities: A Scoping Review of Longitudinal Electroencephalography and Magnetoencephalography Studies

Explored through EEG/MEG, auditory stimuli function as a suitable research probe to reveal various neural activities, including event-related potentials, brain oscillations and functional connectivity. Accumulating evidence in this field stems from studies investigating neuroplasticity induced by long-term auditory training, specifically cross-sectional studies comparing musicians and non-musicians as well as longitudinal studies with musicians. In contrast, studies that address the neural effects of short-term interventions whose duration lasts from minutes to hours are only beginning to be featured. Over the past decade, an increasing body of evidence has shown that short-term auditory interventions evoke rapid changes in neural activities, and oscillatory fluctuations can be observed even in the prestimulus period. In this scoping review, we divided the extracted neurophysiological studies into three groups to discuss neural activities with short-term auditory interventions: the pre-stimulus period, during stimulation, and a comparison of before and after stimulation. We show that oscillatory activities vary depending on the context of the stimuli and are greatly affected by the interplay of bottom-up and top-down modulational mechanisms, including attention. We conclude that the observed rapid changes in neural activitiesin the auditory cortex and the higher-order cognitive part of the brain are causally attributed to short-term auditory interventions.

The architecture of functional brain network modulated by driving during adverse weather conditions

Traffic accidents caused by adverse weather conditions have attracted the attention of many countries. Previous studies have focused on the driver's response in a particular situation under foggy conditions, but little is known about the functional brain network (FBN) topology that is modulated by driving in foggy weather, especially when the vehicle encounters cars in the opposite lane. An experiment consisting of two driving tasks is designed and conducted using sixteen participants. Functional connectivity between all pairs of channels for multiple frequency bands is assessed using the phase-locking value (PLV). Based on this, a PLV-weighted network is subsequently generated. The clustering coefficient (C) and the characteristic path length (L) are adopted as measures for the graph analysis. Statistical analyses are performed on graph-derived metrics. The major finding is that the PLV is significantly increased in the delta, theta and beta frequency bands while driving in foggy weather. Additionally, for the brain network topology metric, compared with driving in clear weather, significant increases are observed (driving in foggy weather) in the clustering coefficient for alpha and beta frequency bands and the characteristic path length for all frequency bands considered in this work. Driving in foggy weather would regulate FBN reorganization in different frequency bands. Our findings also suggest that the effects of adverse weather conditions on functional brain networks with a trend toward a more economic but less efficient architecture. Graph theory analysis may be a beneficial tool to further understand the neural mechanisms of driving in adverse weather conditions, which in turn may help to reduce the occurrence of road traffic accidents to some extent.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09825-y.

Construction and analysis of functional brain network based on emotional electroencephalogram

Networks play an important role in studying structure or functional connection of various brain areas, and explaining mechanism of emotion. However, there is a lack of comprehensive analysis among different construction methods nowadays. Therefore, this paper studies the impact of different emotions on connection of functional brain networks (FBNs) based on electroencephalogram (EEG). Firstly, we defined electrode node as brain area of vicinity of electrode to construct 32-node small-scale FBN. Pearson correlation coefficient (PCC) was used to construct correlation-based FBNs. Phase locking value (PLV) and phase synchronization index (PSI) were utilized to construct synchrony-based FBNs. Next, global properties and effects of emotion of different networks were compared. The difference of synchrony-based FBN concentrates in alpha band, and the number of differences is less than that of correlation-based FBN. Node properties of different small-scale FBNs have significant differences, offering a new basis for feature extraction of recognition regions in emotional FBNs. Later, we made partition of electrode nodes and 10 new brain areas were defined as regional nodes to construct 10-node large-scale FBN. Results show the impact of emotion on network clusters on the right forehead, and high valence enhances information processing efficiency of FBN by promoting connections in brain areas.

The effect of musicality on language recovery after awake glioma surgery

Introduction

Awake craniotomy is increasingly used to resect intrinsic brain tumors while preserving language. The level of musical training might affect the speed and extend of postoperative language recovery, as increased white matter connectivity in the corpus callosum is described in musicians compared to non-musicians.

Methods

In this cohort study, we included adult patients undergoing treatment for glioma with an awake resection procedure at two neurosurgical centers and assessed language preoperatively (T1) and postoperatively at three months (T2) and one year (T3) with the Diagnostic Instrument for Mild Aphasia (DIMA), transferred to z-scores. Moreover, patients' musicality was divided into three groups based on the Musical Expertise Criterion (MEC) and automated volumetric measures of the corpus callosum were conducted.

Results

We enrolled forty-six patients, between June 2015 and September 2021, and divided in: group A (non-musicians, n = 19, 41.3%), group B (amateur musicians, n = 17, 36.9%) and group C (trained musicians, n = 10, 21.7%). No significant differences on postoperative language course between the three musicality groups were observed in the main analyses. However, a trend towards less deterioration of language (mean/SD z-scores) was observed within the first three months on the phonological domain (A: -0.425/0.951 vs. B: -0.00100/1.14 vs. C: 0.0289/0.566, p-value = 0.19) with a significant effect between non-musicians vs. instrumentalists (A: -0.425/0.951 vs. B + C: 0.201/0.699, p = 0.04). Moreover, a non-significant trend towards a larger volume (mean/SD cm³) of the corpus callosum was observed between the three musicality groups (A: 6.67/1.35 vs. B: 7.09/1.07 vs. C: 8.30/2.30, p = 0.13), with the largest difference of size in the anterior corpus callosum in non-musicians compared to trained musicians (A: 3.28/0.621 vs. C: 4.90/1.41, p = 0.02).

Conclusion

With first study on this topic, we support that musicality contributes to language recovery after awake glioma surgery, possibly attributed to a higher white matter connectivity at the anterior part of the corpus callosum. Our conclusion should be handled with caution and interpreted as hypothesis generating only, as most of our results were not significant. Future studies with larger sample sizes are needed to confirm our hypothesis.

Why art? The role of arts in arts and health

This article is an answer to a report called "What is the evidence on the role of the arts in improving health and well-being?" The authors conclude that the arts have an impact on mental and physical health. Yet, the question of the role of the arts remains unanswered. What is and what is not an art effect? Recently, embodied theory has inspired articles on the perception of art. These articles have not yet received attention in the field of Arts and Health. Scholars in psychosomatic medicine have argued for an approach based on recent work in enactive embodied theory to investigate the connection between the body and the mind. The present article examines how key concepts in this theory relate to art. This leads to a discussion of art in terms of empathy-the relation between the internal state of the artist and the internal state of the beholder. I exemplify with a conceptual framework of musical empathy. Implications for health are addressed.

Alterations in Functional Network Topology Within Normal Hemispheres Contralateral to Anterior Circulation Steno-Occlusive Disease: A Resting-State BOLD Study

The purpose of this study was to assess spatially remote effects of hemodynamic impairment on functional network topology contralateral to unilateral anterior circulation steno-occlusive disease (SOD) using resting-state blood oxygen level-dependent (BOLD) imaging, and to investigate the relationships between network connectivity and cerebrovascular reactivity (CVR), a measure of hemodynamic stress. Twenty patients with unilateral, chronic anterior circulation SOD and 20 age-matched healthy controls underwent resting-state BOLD imaging. Five-minute standardized baseline BOLD acquisition was followed by acetazolamide infusion to measure CVR. The BOLD baseline was used to analyze network connectivity contralateral to the diseased hemispheres of SOD patients. Compared to healthy controls, reduced network degree (z-score = −1.158 ± 1.217, P < 0.001, false discovery rate (FDR) corrected), local efficiency (z-score = −1.213 ± 1.120, P < 0.001, FDR corrected), global efficiency (z-score = −1.346 ± 1.119, P < 0.001, FDR corrected), and enhanced modularity (z-score = 1.000 ± 1.205, P = 0.002, FDR corrected) were observed in the contralateral, normal hemispheres of SOD patients. Network degree (P = 0.089, FDR corrected; P = 0.027, uncorrected) and nodal efficiency (P = 0.089, FDR corrected; P = 0.045, uncorrected) showed a trend toward a positive association with CVR. The results indicate remote abnormalities in functional connectivity contralateral to the diseased hemispheres in patients with unilateral SOD, despite the absence of macrovascular disease or demonstrable hemodynamic impairment. The clinical impact of remote functional disruptions requires dedicated investigation but may portend far reaching consequence for even putatively unilateral cerebrovascular disease.

The Effect of Music Listening on EEG Functional Connectivity of Brain: A Short-Duration and Long-Duration Study

Music is considered a powerful brain stimulus, as listening to it can activate several brain networks. Music of different kinds and genres may have a different effect on the human brain. The goal of this study is to investigate the change in the brain’s functional connectivity (FC) when music is used as a stimulus. Secondly, the effect of listening to the subject’s favorite music is compared with listening to specifically formulated relaxing music with alpha binaural beats. Finally, the effect of the duration of music listening is studied. Subjects’ electroencephalographic (EEG) signals were captured as they listened to favorite and relaxing music. After preprocessing and artifact removal, the EEG recordings were decomposed into the delta, theta, alpha, and beta frequency bands, and the grand-averaged connectivity matrices were generated using Inter-Site Phase Clustering (ISPC) for each frequency band and each type of music. Furthermore, each lobe of the brain was analyzed separately to understand the effect of music on specific regions of the brain. EEG-FC among different channels was accessed by using graph theory and Network-based Statistics (NBS). To determine the significance of the changes in brain networks after listening to music, statistical analysis was conducted using Analysis of Variance (ANOVA) and t-test. The study of listening to music for a short duration verifies that either favorite or preferred music can affect the FC of the subject and induce a relaxation state. The short duration study also verifies a significant (ANOVA and t-test: p < 0.05) effectiveness of relaxing music over favorite music to induce relaxation and alertness in the subject. In the study of long duration, it is concluded that listening to relaxing music can increase functional connectivity and connections strength in the frontal lobe of the subject. A significant increase (ANOVA and t-test: p < 0.05) in FC in alpha and theta band and a significant decrease (ANOVA and t-test: p < 0.05) in FC in beta band in the frontal and parietal lobe of the brain verifies the hypothesis that the relaxing music can help the subject to achieve relaxation, activeness, and alertness.

Mental Calculation Drives Reliable and Weak Distant Connectivity While Music Listening Induces Dense Local Connectivity

Mathematical calculation usually requires sustained attention to manipulate numbers in the mind, while listening to light music has a relaxing effect on the brain. The differences in the corresponding brain functional network topologies underlying these behaviors remain rarely known. Here, we systematically examined the brain dynamics of four behaviors (resting with eyes closed and eyes open, tasks of music listening and mental calculation) using 64-channel electroencephalogram (EEG) recordings and graph theory analysis. We developed static and dynamic minimum spanning tree (MST) analysis method and demonstrated that the brain network topology under mental calculation is a more line-like structure with less tree hierarchy and leaf fraction; however, the hub regions, which are mainly located in the frontal, temporal and parietal regions, grow more stable over time. In contrast, music-listening drives the brain to exhibit a highly rich network of star structure, and the hub regions are mainly located in the posterior regions. We then adopted the dynamic dissimilarity of different MSTs over time based on the graph Laplacian and revealed low dissimilarity during mental calculation. These results suggest that the human brain functional connectivity of individuals has unique dynamic diversity and flexibility under various behaviors.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-021-00027-w.

Principles and open questions in functional brain network reconstruction

Graph theory is now becoming a standard tool in system-level neuroscience. However, endowing observed brain anatomy and dynamics with a complex network representation involves often covert theoretical assumptions and methodological choices which affect the way networks are reconstructed from experimental data, and ultimately the resulting network properties and their interpretation. Here, we review some fundamental conceptual underpinnings and technical issues associated with brain network reconstruction, and discuss how their mutual influence concurs in clarifying the organization of brain function.

Sex Differences are Reflected in Microstructural White Matter Alterations of Musical Sophistication: A Diffusion MRI Study

Background: The human-specified ability to engage with different kinds of music in sophisticated ways is named “Musical Sophistication.” Herein, we investigated specific white matter (WM) tracts that are associated with musical sophistication and musicality in both genders, separately, using Diffusion MRI connectometry approach. We specifically aimed to explore potential sex differences regarding WM alterations correlated with musical sophistication.

Methods: 123 healthy participants [70 (56.9%) were male, mean age = 36.80 ± 18.86 year], who were evaluated for musical sophistication using Goldsmiths Musical Sophistication Index (Gold-MSI) self-assessment instrument from the LEMON database, were recruited in this study. The WM correlates of two Gold-MSI subscales (active engagement and music training) were analyzed. Images were prepared and analyzed with diffusion connectometry to construct the local connectome. Multiple regression models were then fitted to address the correlation of local connectomes with Gold-MSI components with the covariates of age and handedness.

Results: a significant positive correlation between WM integrity in the corpus callosum (CC), right corticospinal tract (CST), cingulum, middle cerebellar peduncle (MCP), bilateral parieto-pontine tract, bilateral cerebellum, and left arcuate fasciculus (AF) and both active engagement [false discovery rate (FDR) = 0.008] and music training (FDR = 0.057) was detected in males. However, WM integrity in the body of CC, MCP, and cerebellum in females showed an inverse association with active engagement (FDR = 0.046) and music training (FDR = 0.032).

Conclusion: WM microstructures with functional connection with motor and somatosensory areas (CST, cortico-pontine tracts, CC, cerebellum, cingulum, and MCP) and language processing area (AF) have significant correlation with music engagement and training. Our findings show that these associations are different between males and females, which could potentially account for distinctive mechanisms related to musical perception and musical abilities across genders.

On the estimate of music appraisal from surface EEG: a dynamic-network approach based on cross-sensor PAC measurements

Objective.The aesthetic evaluation of music is strongly dependent on the listener and reflects manifold brain processes that go well beyond the perception of incident sound. Being a high-level cognitive reaction, it is difficult to predict merely from the acoustic features of the audio signal and this poses serious challenges to contemporary music recommendation systems. We attempted to decode music appraisal from brain activity, recorded via wearable EEG, during music listening.Approach.To comply with the dynamic nature of music stimuli, cross-frequency coupling measurements were employed in a time-evolving manner to capture the evolving interactions between distinct brain-rhythms during music listening. Brain response to music was first represented as a continuous flow of functional couplings referring to both regional and inter-regional brain dynamics and then modelled as an ensemble of time-varying (sub)networks. Dynamic graph centrality measures were derived, next, as the final feature-engineering step and, lastly, a support-vector machine was trained to decode the subjective music appraisal. A carefully designed experimental paradigm provided the labeled brain signals.Main results.Using data from 20 subjects, dynamic programming to tailor the decoder to each subject individually and cross-validation, we demonstrated highly satisfactory performance (MAE= 0.948,R²= 0.63) that can be attributed, mostly, to interactions of left frontal gamma rhythm. In addition, our music-appraisal decoder was also employed in a part of the DEAP dataset with similar success. Finally, even a generic version of the decoder (common for all subjects) was found to perform sufficiently.Significance.A novel brain signal decoding scheme was introduced and validated empirically on suitable experimental data. It requires simple operations and leaves room for real-time implementation. Both the code and the experimental data are publicly available.

Modifications in the Topological Structure of EEG Functional Connectivity Networks during Listening Tonal and Atonal Concert Music in Musicians and Non-Musicians

The present work aims to demonstrate the hypothesis that atonal music modifies the topological structure of electroencephalographic (EEG) connectivity networks in relation to tonal music. To this, EEG monopolar records were taken in musicians and non-musicians while listening to tonal, atonal, and pink noise sound excerpts. EEG functional connectivities (FC) among channels assessed by a phase synchronization index previously thresholded using surrogate data test were computed. Sound effects, on the topological structure of graph-based networks assembled with the EEG-FCs at different frequency-bands, were analyzed throughout graph metric and network-based statistic (NBS). Local and global efficiency normalized (vs. random-network) measurements (NLE|NGE) assessing network information exchanges were able to discriminate both music styles irrespective of groups and frequency-bands. During tonal audition, NLE and NGE values in the beta-band network get close to that of a small-world network, while during atonal and even more during noise its structure moved away from small-world. These effects were attributed to the different timbre characteristics (sounds spectral centroid and entropy) and different musical structure. Results from networks topographic maps for strength and NLE of the nodes, and for FC subnets obtained from the NBS, allowed discriminating the musical styles and verifying the different strength, NLE, and FC of musicians compared to non-musicians.

The Effect of Music and White Noise on Electroencephalographic (EEG) Functional Connectivity in Neonates in the Neonatal Intensive Care Unit

The purpose of this study is to investigate whether listening to music and white noise affects functional connectivity on scalp electroencephalography (EEG) in neonates in the neonatal intensive care unit.Nine neonates of ≥34 weeks' gestational age, who were already undergoing clinical continuous EEG monitoring in the neonatal intensive care unit, listened to lullaby-like music and white noise for 1 hour each separated by a 2-hour interval of no intervention. EEG segments during periods of music, white noise, and no intervention were band-pass filtered as delta (0.5-4 Hz), theta (4-8 Hz), lower alpha (8-10 Hz), upper alpha (10-13 Hz), beta (13-30 Hz), and gamma (30-45 Hz). Synchronization likelihood was used as a measure of connectivity between any 2 electrodes.In theta, lower alpha, and upper alpha frequency bands, the synchronization likelihood values yielded statistical significance with sound (music, white noise and no intervention) and with edge (between any 2 electrodes) factors. In theta, lower alpha, and upper alpha frequency bands, statistical significance was obtained between music and white noise (t = 3.12, 3.32, and 3.68, respectively; P < .017), and between white noise and no intervention (t = 4.51, 3.09, and 2.95, respectively, P < .017). However, there was no difference between music and no intervention.Although limited by a small sample size and the 1-time only auditory intervention, these preliminary results demonstrate the feasibility of EEG connectivity analyses even at bedside in neonates on continuous EEG monitoring in the neonatal intensive care unit. They also point to the possibility of detecting significant changes in functional connectivity related to the theta and alpha bands using auditory interventions.

Electro-Encephalography and Electro-Oculography in Aeronautics: A Review Over the Last Decade (2010-2020)

Electro-encephalography (EEG) and electro-oculography (EOG) are methods of electrophysiological monitoring that have potentially fruitful applications in neuroscience, clinical exploration, the aeronautical industry, and other sectors. These methods are often the most straightforward way of evaluating brain oscillations and eye movements, as they use standard laboratory or mobile techniques. This review describes the potential of EEG and EOG systems and the application of these methods in aeronautics. For example, EEG and EOG signals can be used to design brain-computer interfaces (BCI) and to interpret brain activity, such as monitoring the mental state of a pilot in determining their workload. The main objectives of this review are to, (i) offer an in-depth review of literature on the basics of EEG and EOG and their application in aeronautics; (ii) to explore the methodology and trends of research in combined EEG-EOG studies over the last decade; and (iii) to provide methodological guidelines for beginners and experts when applying these methods in environments outside the laboratory, with a particular focus on human factors and aeronautics. The study used databases from scientific, clinical, and neural engineering fields. The review first introduces the characteristics and the application of both EEG and EOG in aeronautics, undertaking a large review of relevant literature, from early to more recent studies. We then built a novel taxonomy model that includes 150 combined EEG-EOG papers published in peer-reviewed scientific journals and conferences from January 2010 to March 2020. Several data elements were reviewed for each study (e.g., pre-processing, extracted features and performance metrics), which were then examined to uncover trends in aeronautics and summarize interesting methods from this important body of literature. Finally, the review considers the advantages and limitations of these methods as well as future challenges.

Resting-state EEG Dynamics Reveals Differences in Network Organization and its Fluctuation between Frequency Bands

Functional connectivity in EEG resting-state is not stable but fluctuates considerably. The aim of this study was to investigate how efficient information flows through a network, i.e. how resting-state EEG networks are organized and whether this organization it also subject to fluctuations. Differences of the network organization (small-worldness), degree of clustered connectivity, and path length as an indicator of how information is integrated into the network across time was compared between theta, alpha and beta bands. We show robust differences in network organization (small-worldness) between frequency bands. Fluctuations in network organization were larger in the theta, compared to the alpha and beta frequency. Variation in network organization and not the frequency of fluctuations differs between frequency bands. Furthermore, the degree of clustered connectivity and its modulation across time is the same across frequency bands, but the path length revealed the same modulatory pattern as the small-world metric. It is therefore the interplay of local processing efficiency and global information processing efficiency in the brain that fluctuates in a frequency-specific way. Properties of how information can be integrated is subject to fluctuations in a frequency-specific way in the resting-state. The possible relevance of these resting-state EEG properties is discussed including its clinical relevance.

Review of computational neuroaesthetics: bridging the gap between neuroaesthetics and computer science

The mystery of aesthetics attracts scientists from various research fields. The topic of aesthetics, in combination with other disciplines such as neuroscience and computer science, has brought out the burgeoning fields of neuroaesthetics and computational aesthetics within less than two decades. Despite profound findings are carried out by experimental approaches in neuroaesthetics and by machine learning algorithms in computational neuroaesthetics, these two fields cannot be easily combined to benefit from each other and findings from each field are isolated. Computational neuroaesthetics, which inherits computational approaches from computational aesthetics and experimental approaches from neuroaesthetics, seems to be promising to bridge the gap between neuroaesthetics and computational aesthetics. Here, we review theoretical models and neuroimaging findings about brain activity in neuroaesthetics. Then machine learning algorithms and computational models in computational aesthetics are enumerated. Finally, we introduce studies in computational neuroaesthetics which combine computational models with neuroimaging data to analyze brain connectivity during aesthetic appreciation or give a prediction on aesthetic preference. This paper outlines the rich potential for computational neuroaesthetics to take advantages from both neuroaesthetics and computational aesthetics. We conclude by discussing some of the challenges and potential prospects in computational neuroaesthetics, and highlight issues for future consideration.

Decreasing Delirium Through Music: A Randomized Pilot Trial

BACKGROUND

Management of delirium in intensive care units is challenging because effective therapies are lacking. Music is a promising nonpharmacological intervention.

OBJECTIVES

To determine the feasibility and acceptability of personalized music (PM), slow-tempo music (STM), and attention control (AC) in patients receiving mechanical ventilation in an intensive care unit, and to estimate the effect of music on delirium.

METHODS

A randomized controlled trial was performed in an academic medical-surgical intensive care unit. After particular inclusion and exclusion criteria were applied, patients were randomized to groups listening to PM, relaxing STM, or an audiobook (AC group). Sessions lasted 1 hour and were given twice daily for up to 7 days. Patients wore noise-canceling headphones and used mp3 players to listen to their music/audiobook. Delirium and delirium severity were assessed twice daily by using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and the CAM-ICU-7, respectively.

RESULTS

Of the 1589 patients screened, 117 (7.4%) were eligible. Of those, 52 (44.4%) were randomized, with a recruitment rate of 5 patients per month. Adherence was higher in the groups listening to music (80% in the PM and STM groups vs 30% in the AC group; P = .01), and 80% of patients surveyed rated the music as enjoyable. The median number (interquartile range) of delirium/coma-free days by day 7 was 2 (1-6) for PM, 3 (1-6) for STM, and 2 (0-3) for AC (P = .32). Median delirium severity was 5.5 (1-7) for PM, 3.5 (0-7) for STM, and 4 (1-6.5) for AC (P = .78).

CONCLUSIONS

Music delivery is acceptable to patients and is feasible in intensive care units. Further research testing use of this promising intervention to reduce delirium is warranted.

Alteration of perceived emotion and brain functional connectivity by changing the musical rhythmic pattern

The arrangement of musical notes and their time intervals, also known as musical rhythm is one of the core elements of music. Nevertheless, the cognitive process and neural mechanism of the human brain that underlay the perception of musical rhythm are poorly understood. In this study, we hypothesized that changes in musical rhythmic patterns alter the emotional content expressed by music and the way it is perceived, that assumably causes specific changes in the brain functional connectome. Therefore, 18 male children aged 10-14 years old were recruited and exposed to 12 musical excerpts while their brain's electrical activity was recorded using a 32-channel EEG recorder. The musical rhythmic patterns were changed by manipulating only note values in beats while keeping time signature and other elements in a fixed state. The experienced emotions were assessed using a 2-dimensional self-assessment manikin questionnaire. The behavioral data showed that an increase in the complexity of musical rhythmic patterns significantly enhances perceived valence and arousal levels. In addition, the pattern of brain functional connectivity was also estimated using the weighted phase lag index and their association with behavioral changes was calculated. Interestingly, the behavioral changes were mainly associated with alteration of brain functional connectivity at the alpha band in the fronto-central connections. These results emphasize the important role of the motor cortical site-fronto-central connections, in the perception of musical rhythmic pattern. These findings may improve conception of the underlying brain mechanism involved in the perception of musical rhythm.

Frontal brain asymmetries as effective parameters to assess the quality of audiovisual stimuli perception in adult and young cochlear implant users

How is music perceived by cochlear implant (CI) users? This question arises as “the next step” given the impressive performance obtained by these patients in language perception. Furthermore, how can music perception be evaluated beyond self-report rating, in order to obtain measurable data? To address this question, estimation of the frontal electroencephalographic (EEG) alpha activity imbalance, acquired through a 19-channel EEG cap, appears to be a suitable instrument to measure the approach/withdrawal (AW index) reaction to external stimuli. Specifically, a greater value of AW indicates an increased propensity to stimulus approach, and vice versa a lower one a tendency to withdraw from the stimulus. Additionally, due to prelingually and postlingually deafened pathology acquisition, children and adults, respectively, would probably differ in music perception. The aim of the present study was to investigate children and adult CI users, in unilateral (UCI) and bilateral (BCI) implantation conditions, during three experimental situations of music exposure (normal, distorted and mute). Additionally, a study of functional connectivity patterns within cerebral networks was performed to investigate functioning patterns in different experimental populations. As a general result, congruency among patterns between BCI patients and control (CTRL) subjects was seen, characterised by lowest values for the distorted condition (vs. normal and mute conditions) in the AW index and in the connectivity analysis. Additionally, the normal and distorted conditions were significantly different in CI and CTRL adults, and in CTRL children, but not in CI children. These results suggest a higher capacity of discrimination and approach motivation towards normal music in CTRL and BCI subjects, but not for UCI patients. Therefore, for perception of music CTRL and BCI participants appear more similar than UCI subjects, as estimated by measurable and not self-reported parameters.

Exploring the fatigue affecting electroencephalography based functional brain networks during real driving in young males

In recent years, a large proportion of traffic accidents are caused by driver fatigue. The brain has been conceived as a complex network, whose function can be assessed with EEG. Hence, in this research, fourteen subjects participated in the real driving experiments, and a comprehensive EEG-based expert system was designed for detecting driver fatigue. Collected EEG signals were first decomposed into delta-range, theta-range, alpha-range and beta-range by wavelet packet transform (WPT). Unlike other approaches, a multi-channel network construction method based on Phase Lag Index (PLI) was then proposed in this paper. Finally, the functional connectivity between alert state (at the beginning of the drive) and fatigue state (at the end of the drive) in multiple frequency bands were analyzed. The results indicate that functional connectivity of the brain area was significantly different between alert and fatigue states, especially in alpha-range and beta-range. Particularly, the frontal-to-parietal functional connectivity was weakened. Meanwhile, lower clustering coefficient (C) values and higher characteristic path length (L) values were observed in fatigue state in comparison with alert state. Based on this, two new EEG feature selection approaches, C and L in the corresponding sub-frequency range were applied to feature recognition and classification system. Using a support vector machine (SVM) machine learning algorithm, these features were combined to distinguish between alert and fatigue states, achieving an accuracy of 94.4%, precision of 94.3%, sensitivity of 94.6% and false alarm rate of 5.7%. The results suggest that brain network analysis approaches combined with SVM are helpful to alert drivers while being sleepy or even fatigue.

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.

Graph analysis of functional brain network topology using minimum spanning tree in driver drowsiness

A large number of traffic accidents due to driver drowsiness have been under more attention of many countries. The organization of the functional brain network is associated with drowsiness, but little is known about the brain network topology that is modulated by drowsiness. To clarify this problem, in this study, we introduce a novel approach to detect driver drowsiness. Electroencephalogram (EEG) signals have been measured during a simulated driving task, in which participants are recruited to undergo both alert and drowsy states. The filtered EEG signals are then decomposed into multiple frequency bands by wavelet packet transform. Functional connectivity between all pairs of channels for multiple frequency bands is assessed using the phase lag index (PLI). Based on this, PLI-weighted networks are subsequently calculated, from which minimum spanning trees are constructed-a graph method that corrects for comparison bias. Statistical analyses are performed on graph-derived metrics as well as on the PLI connectivity values. The major finding is that significant differences in the delta frequency band for three graph metrics and in the theta frequency band for five graph metrics suggesting network integration and communication between network nodes are increased from alertness to drowsiness. Together, our findings also suggest a more line-like configuration in alert states and a more star-like topology in drowsy states. Collectively, our findings point to a more proficient configuration in drowsy state for lower frequency bands. Graph metrics relate to the intrinsic organization of functional brain networks, and these graph metrics may provide additional insights on driver drowsiness detection for reducing and preventing traffic accidents and further understanding the neural mechanisms of driver drowsiness.

Standardizing music characteristics for the management of pain: A systematic review and meta-analysis of clinical trials

PURPOSE

To evaluate if music characteristics like tempo, harmony, melody, instrumentation, volume, and pitch, as defined by musical theory, are described in randomized clinical trials (RCTs) evaluating the effects of music-listening on the quantified pain perception of adults, and if these characteristics influence music's overall therapeutic effect.

METHODS

A systematic review and meta-analysis of RCTs evaluating music-listening for pain management on adults was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses statement. The databases Pubmed, Scopus, SCIELO, SpringerLink, Global Health Library, Cochrane, EMBASE, and LILACS were searched. Studies published between 2004 and 2017 with quantified measurements of pain were included. Quality was evaluated using the Scottish Intercollegiate Guidelines Network methodology checklist for RCT, and effect sizes were reported with standardized mean differences.

RESULTS

A total of 85 studies were included for qualitative analysis but only 56.47% described at least one music characteristic. Overall meta-analysis found a significant effect, with high heterogeneity, of music for pain management (SMD -0.59, I2 = 85%). Only instrumentation characteristics (lack of lyrics, of percussion or of nature sounds), and 60-80 bpm tempo were described sufficiently for analysis. All three instrumentation characteristics had significant effects, but only the lack of lyrics showed an acceptable heterogeneity.

CONCLUSIONS

Results show that music without lyrics is effective for the management of pain. Due to insufficient data, no ideal music characteristics for the management of pain were identified suggesting that music, as an intervention, needs standardization through an objective language such as that of music theory.

A Comparative Study of Standardized Infinity Reference and Average Reference for EEG of Three Typical Brain States

The choice of different reference electrodes plays an important role in deciphering the functional meaning of electroencephalography (EEG) signals. In recent years, the infinity zero reference using the reference electrode standard technique (REST) has been increasingly applied, while the average reference (AR) was generally advocated as the best available reference option in previous classical EEG studies. Here, we designed EEG experiments and performed a direct comparison between the influences of REST and AR on EEG-revealed brain activity features for three typical brain behavior states (eyes-closed, eyes-open and music-listening). The analysis results revealed the following observations: (1) there is no significant difference in the alpha-wave-blocking effect during the eyes-open state compared with the eyes-closed state for both REST and AR references; (2) there was clear frontal EEG asymmetry during the resting state, and the degree of lateralization under REST was higher than that under AR; (3) the global brain functional connectivity density (FCD) and local FCD have higher values for REST than for AR under different behavior states; and (4) the value of the small-world network characteristic in the eyes-closed state is significantly (in full, alpha, beta and gamma frequency bands) higher than that in the eyes-open state, and the small-world effect under the REST reference is higher than that under AR. In addition, the music-listening state has a higher small-world network effect than the eyes-closed state. The above results suggest that typical EEG features might be more clearly presented by applying the REST reference than by applying AR when using a 64-channel recording.

Early detection of consciousness in patients with acute severe traumatic brain injury

See Schiff (doi:10.1093/awx209) for a scientific commentary on this article. Patients with acute severe traumatic brain injury may recover consciousness before self-expression. Without behavioural evidence of consciousness at the bedside, clinicians may render an inaccurate prognosis, increasing the likelihood of withholding life-sustaining therapies or denying rehabilitative services. Task-based functional magnetic resonance imaging and electroencephalography techniques have revealed covert consciousness in the chronic setting, but these techniques have not been tested in the intensive care unit. We prospectively enrolled 16 patients admitted to the intensive care unit for acute severe traumatic brain injury to test two hypotheses: (i) in patients who lack behavioural evidence of language expression and comprehension, functional magnetic resonance imaging and electroencephalography detect command-following during a motor imagery task (i.e. cognitive motor dissociation) and association cortex responses during language and music stimuli (i.e. higher-order cortex motor dissociation); and (ii) early responses to these paradigms are associated with better 6-month outcomes on the Glasgow Outcome Scale-Extended. Patients underwent functional magnetic resonance imaging on post-injury Day 9.2 ± 5.0 and electroencephalography on Day 9.8 ± 4.6. At the time of imaging, behavioural evaluation with the Coma Recovery Scale-Revised indicated coma (n = 2), vegetative state (n = 3), minimally conscious state without language (n = 3), minimally conscious state with language (n = 4) or post-traumatic confusional state (n = 4). Cognitive motor dissociation was identified in four patients, including three whose behavioural diagnosis suggested a vegetative state. Higher-order cortex motor dissociation was identified in two additional patients. Complete absence of responses to language, music and motor imagery was only observed in coma patients. In patients with behavioural evidence of language function, responses to language and music were more frequently observed than responses to motor imagery (62.5-80% versus 33.3-42.9%). Similarly, in 16 matched healthy subjects, responses to language and music were more frequently observed than responses to motor imagery (87.5-100% versus 68.8-75.0%). Except for one patient who died in the intensive care unit, all patients with cognitive motor dissociation and higher-order cortex motor dissociation recovered beyond a confusional state by 6 months. However, 6-month outcomes were not associated with early functional magnetic resonance imaging and electroencephalography responses for the entire cohort. These observations suggest that functional magnetic resonance imaging and electroencephalography can detect command-following and higher-order cortical function in patients with acute severe traumatic brain injury. Early detection of covert consciousness and cortical responses in the intensive care unit could alter time-sensitive decisions about withholding life-sustaining therapies.

The role of music therapy in rehabilitation: improving aphasia and beyond

Music is part of the human nature, and it is also philogenically relevant to language evolution. Language and music are bound together in the enhancement of important social functions, such as communication, cooperation and social cohesion. In the last few years, there has been growing evidence that music and music therapy may improve communication skills (but not only) in different neurological disorders. One of the plausible reasons concerning the rational use of sound and music in neurorehabilitation is the possibility to stimulate brain areas involved in emotional processing and motor control, such as the fronto-parietal network. In this narrative review, we are going to describe the role of music therapy in improving aphasia and other neurological disorders, underlying the reasons why this tool could be effective in rehabilitative settings, especially in individuals affected by stroke.

Exploring the effect of sound and music on health in hospital settings: A narrative review

BACKGROUND

Sound in hospital space has traditionally been considered in negative terms as both intrusive and unwanted, and based mainly on sound levels. However, sound level is only one aspect of the soundscape. There is strong evidence that exploring the positive aspect of sound in a hospital context can evoke positive feelings in both patients and nurses. Music psychology studies have also shown that music intervention in health care can have a positive effect on patient's emotions and recuperating processes. In this way, hospital spaces have the potential to reduce anxiety and stress, and make patients feel comfortable and secure. This paper describes a review of the literature exploring sound perception and its effect on health care.

DATA SOURCES AND REVIEW METHODS

This review sorted the literature and main issues into themes concerning sound in health care spaces; sound, stress and health; positive soundscape; psychological perspective of music and emotion; music as a complementary medicine for improving health care; contradicting arguments concerning the use of music in health care; and implications for clinical practice. Using Web of Science, PubMed, Scopus, ProQuest Central, MEDLINE, and Google, a literature search on sound levels, sound sources and the impression of a soundscape was conducted. The review focused on the role and use of music on health care in clinical environments. In addition, other pertinent related materials in shaping the understanding of the field were retrieved, scanned and added into this review.

RESULTS

The result indicated that not all noises give a negative impression within healthcare soundscapes. Listening to soothing music was shown to reduce stress, blood pressure and post-operative trauma when compared to silence. Much of the sound conveys meaningful information that is positive for both patients and nurses, in terms of soft wind, bird twitter, and ocean sounds.

CONCLUSIONS

Music perception was demonstrated to bring about positive change in patient-reported outcomes such as eliciting positive emotion, and decreasing the levels of stressful conditions. Whilst sound holds both negative and positive aspects of the hospital ecosystem and may be stressful, it also possesses a soothing quality that induces positive feelings in patients. Conceptualizing the nature of sound in the hospital context as a soundscape, rather than merely noise can permit a subtler and socially useful understanding of the role of sound and music in the hospital setting, thereby creating a means for improving the hospital experience for patients and nurses.

Enhanced functional connectivity properties of human brains during in-situ nature experience

In this study, we investigated the impacts of in-situ nature and urban exposure on human brain activities and their dynamics. We randomly assigned 32 healthy right-handed college students (mean age = 20.6 years, SD = 1.6; 16 males) to a 20 min in-situ sitting exposure in either a nature (n = 16) or urban environment (n = 16) and measured their Electroencephalography (EEG) signals. Analyses revealed that a brief in-situ restorative nature experience may induce more efficient and stronger brain connectivity with enhanced small-world properties compared with a stressful urban experience. The enhanced small-world properties were found to be correlated with “coherent” experience measured by Perceived Restorativeness Scale (PRS). Exposure to nature also induces stronger long-term correlated activity across different brain regions with a right lateralization. These findings may advance our understanding of the functional activities during in-situ environmental exposures and imply that a nature or nature-like environment may potentially benefit cognitive processes and mental well-being.

Hypothesizing Music Intervention Enhances Brain Functional Connectivity Involving Dopaminergic Recruitment: Common Neuro-correlates to Abusable Drugs

The goal of this review is to explore the clinical significance of music listening on neuroplasticity and dopaminergic activation by understanding the role of music therapy in addictive behavior treatment. fMRI data has shown that music listening intensely modifies mesolimbic structural changes responsible for reward processing (e.g., nucleus accumbens [NAc]) and may control the emotional stimuli's effect on autonomic and physiological responses (e.g., hypothalamus). Music listening has been proven to induce the endorphinergic response blocked by naloxone, a common opioid antagonist. NAc opioid transmission is linked to the ventral tegmental area (VTA) dopamine release. There are remarkable commonalities between listening to music and the effect of drugs on mesolimbic dopaminergic activation. It has been found that musical training before the age of 7 results in changes in white-matter connectivity, protecting carriers with low dopaminergic function (DRD2A1 allele, etc.) from poor decision-making, reward dependence, and impulsivity. In this article, we briefly review a few studies on the neurochemical effects of music and propose that these findings are relevant to the positive clinical findings observed in the literature. We hypothesize that music intervention enhances brain white matter plasticity through dopaminergic recruitment and that more research is needed to explore the efficacy of these therapies.

Independent component processes underlying emotions during natural music listening

The aim of this study was to investigate the brain processes underlying emotions during natural music listening. To address this, we recorded high-density electroencephalography (EEG) from 22 subjects while presenting a set of individually matched whole musical excerpts varying in valence and arousal. Independent component analysis was applied to decompose the EEG data into functionally distinct brain processes. A k-means cluster analysis calculated on the basis of a combination of spatial (scalp topography and dipole location mapped onto the Montreal Neurological Institute brain template) and functional (spectra) characteristics revealed 10 clusters referring to brain areas typically involved in music and emotion processing, namely in the proximity of thalamic-limbic and orbitofrontal regions as well as at frontal, fronto-parietal, parietal, parieto-occipital, temporo-occipital and occipital areas. This analysis revealed that arousal was associated with a suppression of power in the alpha frequency range. On the other hand, valence was associated with an increase in theta frequency power in response to excerpts inducing happiness compared to sadness. These findings are partly compatible with the model proposed by Heller, arguing that the frontal lobe is involved in modulating valenced experiences (the left frontal hemisphere for positive emotions) whereas the right parieto-temporal region contributes to the emotional arousal.

Choral singing therapy following stroke or Parkinson's disease: an exploration of participants' experiences

PURPOSE

People with stroke or Parkinson's disease (PD) live with reduced mood, social participation and quality of life (QOL). Communication difficulties affect 90% of people with PD (dysarthria) and over 33% of people with stroke (aphasia). These consequences are disabling in many ways. However, as singing is typically still possible, its therapeutic use is of increasing interest. This article explores the experiences of and factors influencing participation in choral singing therapy (CST) by people with stroke or PD and their significant others.

METHOD

Participants (eight people with stroke, six with PD) were recruited from a community music therapy choir running CST. Significant others (seven for stroke, two for PD) were also recruited. Supported communication methods were used as needed to undertake semi-structured interviews (total N = 23).

RESULTS

Thematic analysis indicated participants had many unmet needs associated with their condition, which motivated them to explore self-management options. CST participation was described as an enjoyable social activity, and participation was perceived as improving mood, language, breathing and voice.

CONCLUSIONS

Choral singing was perceived by people with stroke and PD to help them self-manage some of the consequences of their condition, including social isolation, low mood and communication difficulties.

IMPLICATIONS FOR REHABILITATION

Choral singing therapy (CST) is sought out by people with stroke and PD to help self-manage symptoms of their condition. Participation is perceived as an enjoyable activity which improves mood, voice and language symptoms. CST may enable access to specialist music therapy and speech language therapy protocols within community frameworks.

Reconfiguration of the Brain Functional Network Associated with Visual Task Demands

Neuroimaging studies have demonstrated that the topological properties of resting-state brain functional networks are modulated through task performances. However, the reconfiguration of functional networks associated with distinct degrees of task demands is not well understood. In the present study, we acquired fMRI data from 18 healthy adult volunteers during resting-state (RS) and two visual tasks (i.e., visual stimulus watching, VSW; and visual stimulus decision, VSD). Subsequently, we constructed the functional brain networks associated with these three conditions and analyzed the changes in the topological properties (e.g., network efficiency, wiring-cost, modularity, and robustness) among them. Although the small-world attributes were preserved qualitatively across the functional networks of the three conditions, changes in the topological properties were also observed. Compared with the resting-state, the functional networks associated with the visual tasks exhibited significantly increased network efficiency and wiring-cost, but decreased modularity and network robustness. The changes in the task-related topological properties were modulated according to the task complexity (i.e., from RS to VSW and VSD). Moreover, at the regional level, we observed that the increased nodal efficiencies in the visual and working memory regions were positively associated with the increase in task complexity. Together, these results suggest that the increased efficiency of the functional brain network and higher wiring-cost were observed to afford the demands of visual tasks. These observations provide further insights into the mechanisms underlying the reconfiguration of the brain network during task performance.

Investigation of global and local network properties of music perception with culturally different styles of music

BACKGROUND

Graph theoretical analysis has recently become a popular research tool in neuroscience, however, there have been very few studies on brain responses to music perception, especially when culturally different styles of music are involved.

METHODS

Electroencephalograms were recorded from ten subjects listening to Chinese traditional music, light music and western classical music. For event-related potentials, phase coherence was calculated in the alpha band and then constructed into correlation matrices. Clustering coefficients and characteristic path lengths were evaluated for global properties, while clustering coefficients and efficiency were assessed for local network properties.

RESULTS

Perception of light music and western classical music manifested small-world network properties, especially with a relatively low proportion of weights of correlation matrices. For local analysis, efficiency was more discernible than clustering coefficient. Nevertheless, there was no significant discrimination between Chinese traditional and western classical music perception.

CONCLUSIONS

Perception of different styles of music introduces different network properties, both globally and locally. Research into both global and local network properties has been carried out in other areas; however, this is a preliminary investigation aimed at suggesting a possible new approach to brain network properties in music perception.

Revealing spatio-spectral electroencephalographic dynamics of musical mode and tempo perception by independent component analysis

Background

Music conveys emotion by manipulating musical structures, particularly musical mode- and tempo-impact. The neural correlates of musical mode and tempo perception revealed by electroencephalography (EEG) have not been adequately addressed in the literature.

Method

This study used independent component analysis (ICA) to systematically assess spatio-spectral EEG dynamics associated with the changes of musical mode and tempo.

Results

Empirical results showed that music with major mode augmented delta-band activity over the right sensorimotor cortex, suppressed theta activity over the superior parietal cortex, and moderately suppressed beta activity over the medial frontal cortex, compared to minor-mode music, whereas fast-tempo music engaged significant alpha suppression over the right sensorimotor cortex.

Conclusion

The resultant EEG brain sources were comparable with previous studies obtained by other neuroimaging modalities, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). In conjunction with advanced dry and mobile EEG technology, the EEG results might facilitate the translation from laboratory-oriented research to real-life applications for music therapy, training and entertainment in naturalistic environments.