music influence research paper

• Open access
• Published: 21 March 2023

Changing positive and negative affects through music experiences: a study with university students

• José Salvador Blasco-Magraner 1 ,
• Gloria Bernabé-Valero 2 ,
• Pablo Marín-Liébana 1 &
• Ana María Botella-Nicolás 1  

BMC Psychology volume  11 , Article number:  76 ( 2023 ) Cite this article

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Currently, there are few empirical studies that demonstrate the effects of music on specific emotions, especially in the educational context. For this reason, this study was carried out to examine the impact of music to identify affective changes after exposure to three musical stimuli.

The participants were 71 university students engaged in a music education course and none of them were musicians. Changes in the affective state of non-musical student teachers were studied after listening to three pieces of music. An inter-subject repeated measures ANOVA test was carried out using the Positive and Negative Affect Schedule (PANAS) to measure their affective state.

The results revealed that: (i) the three musical experiences were beneficial in increasing positive affects and reducing negative affects, with significant differences between the interaction of Music Experiences × Moment (pre-post); (ii) listening to Mahler’s sad fifth symphony reduced more negative affects than the other experimental conditions; (iii) performing the blues had the highest positive effects.

Conclusions

These findings provide applied keys aspects for music education and research, as they show empirical evidence on how music can modify specific affects of personal experience.

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Introduction

The studies published on the benefits of music have been on the increase in the last two decades [ 1 , 2 , 3 ] and have branched out into different areas of research such as psychology [ 4 , 5 , 6 , 7 , 8 ], education [ 1 , 9 , 10 ] and health [ 11 , 12 ] providing ways of using music as a resource for people’s improvement.

The publication in 1996 of the famous report “Education Hides a Treasure” submitted to the UNESCO by the International Commission was an important landmark in the educational field. This report pointed out the four basic pillars of twenty-first century education: learning to know, learning to do, learning to live together, and learning to be [ 13 ]. The two last ones clearly refer to emotional education. This document posed a challenge to Education in terms of both academically and emotionally development at all levels from kindergarten to university. In this regard, there has been a notable increase in the number of studies that have shown the strong impact of music on the emotions in the different stages of education and our lives. For example, from childhood to adolescence, involving primary, secondary and university education, music is especially relevant for its beneficial effects on developing students’ emotional intelligence and prosocial skills [ 1 , 14 ]. In adults, music benefits emotional self-regulation [ 15 ], while in old age it helps to maintain emotional welfare and to experience and express spirituality [ 16 ]. This underlines the importance of providing empirical evidence on the emotional influence of music.

Influence of music on positive affects

Numerous studies have used the Positive and Negative Affect Schedule (PANAS) to evaluate the emotional impact of music [ 17 ]. This scale is valid and effective for measuring the influence of positive and negative effects of music on listeners and performers [ 10 , 18 , 19 ]. Thus, for example, empirical evidence shows that exposure to a musical stimulus favours the increase of positive affects [ 20 , 21 ] found a significant increase in three positive affects in secondary school students after listening to music, and the same results has been found after listening to diverse musical styles. These results are consistent with Schubert [ 22 ], who demonstrated that music seems to improve or maintain well-being by means of positive valence emotions (e. g. happiness, joy and calm). Other research studied extreme metal fans aged between 18 and 34 years old and found statements of physiological excitement together with increased positive affects [ 21 ]. Positive outcomes after listening to sad music have also been found [ 23 ], who played Samuel Barbers’ Adagio for Strings , described by the BBC as the world’s saddest piece of classical music, to 20 advanced music students and 20 advanced psychology students with no musical background and subsequently found that the music only had positive affects on both groups.

Several experimental designs that used sad music on university students noticed that they experienced both sadness and positive affects [ 24 , 25 ] and also found that music labeled as “happy” increased positive affects while the one labeled as “sad” reduced both positive and negative affects [ 26 ]. For other authors the strongest and most pleasant responses to sad music are associated with empathy [ 27 ]. Moreover, listening to sad music had benefits since attributes of empathy were intensified [ 27 , 28 ]. In relation to musical performances, empirical evidence found a significant increase in positive affects [ 29 ]. Thus, music induces listeners to experience positive affects, which could turn music into an instrument for personal development.

Following on from Fredrickson’s ‘broaden‐and‐build’ framework of positive emotions [ 30 ], positive affects cause changes in cognitive activities which, in turn, can cause behaviour changes. They can also expand the possibilities for action and improve physical resources. According to Fredrickson [ 30 ], positive affects trigger three sequential effects: (1) amplification of the scope for thought and action; (2) construction of personal resources to deal with difficult simplifications; (3) personal transformation by making one more creative, with a better understanding of situations, better able to face up to difficulties and better socially integrated. This leads to an “upward spiral” in which even more positive affects are experienced. A resource such as music that can increase positive affects, can therefore be considered as a step forward in personal transformation. Thus, music teachers could have a powerful tool to help students enhance their personal development.

Influence of music on negative affects

There is a great deal of controversy as regards the influence of music on negative affects. Blasco and Calatrava [ 20 ] found a significant reduction of five negative affects in secondary school students after listening to Arturo Marquez’s typically happy Danzón N O 2. Different results were found in an experiment in which the change in participants ‘affects was assessed after listening the happy "Eye of the Tiger" by Survivor and the sad "Everybody Hurts" by REM [ 26 ]. They found that the happy piece only increased the positive affects but did not reduce the negative ones, while the sad piece reduced both positive and negative affects. However, neither of these findings agree with Miller and Au [ 31 ], who carried out an experiment to compare the influence of sad and happy music on undergraduates ‘mood arousal and found that listening to both types had no significant changes on negative affects. Shulte [ 32 ] conducted a study with 30 university students to examine the impact that nostalgic music has on affects, and found that after listening to different songs, negative affects decreased. Matsumoto [ 33 ] found that sad music reduced sad feelings in deeply sad university students, while Vuoskoski and Eerola [ 34 ] showed that sad music could produce changes in memory and emotional judgements related to emotions and that experiencing music-induced sadness is intrinsically more pleasant than sad memories. It therefore seems that reducing negative affects has mostly been studied with sad and nostalgic musical stimuli. In this way, if music can reduce negative affects, it can also be involved in educational and psychological interventions focused on improving the emotional-affective sphere. Thus, for example, one study examined the effects of a wide range of music activities and found that it would be necessary to specify exactly what types of music activity lead to what types of outcomes [ 2 ]. Moore [ 3 ] also found that certain music experiences and characteristics had both desirable and undesirable effects on the neural activation patterns involved in emotion regulation. Furthermore, recent research on university students shows that music could be used to assess mood congruence effects, since these effects are reactions to the emotions evoked by music [ 35 ].

These studies demonstrate that emotional experience can be actively driven by music. Moreover, they synthesize the efforts to find ways in which music can enhance affective emotional experience by increasing positive affects and reducing the negative ones (e. g. hostility, nervousness and irritability). Although negative emotions have a great value for personal development and are necessary for psychological adjustment, coping with them and self-regulation capacities are issues that have concerned psychology. For example, Emotional Intelligence [ 36 ], which has currently been established in the educational field, constitutes a fundamental conceptual framework to increase well-being when facing negative emotions, providing keys for greater control and management of emotional reactions. It also establishes how to decrease the intensity and frequency of negative emotional states [ 37 ], providing techniques such as mindfulness meditation that have proven their effectiveness in reducing negative emotional experiences and increasing the positive ones [ 38 ]. The purpose of this research is to find whether music can be part of the varied set of resources that can be used by a teacher to modify students’ emotional experience.

Thus, although empirical evidence of the effects of music on the emotional sphere is still incipient. It seems that they can increase positive effects, but it is not clear their impact on the negative ones, since diverse and contradictory results (no change and reduction of negative affects after listening to music) were found. In addition, the effects of the type of musical piece (e.g. happy or sad music) need further investigation as different effects were found. Moreover, previous studies do not compare between the effects of listening to versus performing music. Such an approach could provide keys to highlight the importance of performing within music education. Therefore, this study aims to contribute to this scientific field, providing experimental evidence on the effects of listening to music as compared to performing music, as well as determining the effects of different types of music on positive and negative affects.

To this end, the effects of three different types of music experiences were compared: (1) listening to a sad piece, (2) listening to an epic and solemn piece, and (3) performing of a rhythm and a blues piece, to determine whether positive and negative affects were modified after exposure to these experimental situations. In particular, two hypotheses guided this study: (1) After exposure to each musical experience (listening to a sad piece; listening to a solemn piece and playing a blues), all participants will improve their emotional experience, increasing their positive affects and reducing their negative ones; and (2) the music performance will induce a greater change as compared to the listening conditions.

Participants

A total of 71 students were involved in this study, 6 men and 65 women between the ages of 20 and 40, who were studying a Teaching Grade. These students were enrolled in the "Music Education" program as part of their university degree’s syllabus. None of them had special music studies from conservatories, academies or were self-taught; thus, all had similar musical knowledge. None of them had previously listened to music in an instructional context nor had performed music with their fellow students. In addition, none of them had listening before to the musical pieces selected for this experiment.

All signed an informed consent form before participating and no payment was given for taking part in the study. As the experiment was carried out in the context of a university course, they were assured that their participation and responses would be anonymous and would have no impact on their qualifications. The research was approved by the ethical committee at the Universidad Católica de Valencia San Vicente Mártir: UCV2017- 18-28 code.

Questionnaire

To assess emotional states, the Positive and Negative Affective States scales (PANAS), was administered [ 39 ]. In particular, the Spanish version of the scale [ 17 ], whose study shows a high degree of internal consistency; in males 0.89 in positive affects and 0.91 in negative affects; in women 0.87 in positive affects and 0.89 in negative affects. In this study, good reliability level in each experimental condition was obtained (0.836–0.913 for positive affects and 0.805–0.917 for negative affects (see Table 1 for more information on Cronbach’s α for each experimental condition).

The PANAS consists of 20 items which describe different dimensions of emotional experience. Participants must answer them regarding to their current affective state. The scale is composed of 20 items; 10 positive affects (PA) and 10 negative affects (NA). Answers are graded in a 5-options (Likert scale), with reversed items, ranging from extremely (1) to very slightly or not at all (5).

Musical pieces

The musical pieces choice stemmed from the analysis of some of the music elements that most influence the perception of emotions: mode, melody and intervals. Within the melody, range and melodic direction were distinguished. The range or amplitude of the melodic line is commonly divided into wide or narrow, while the melodic direction is often classified as ascending or descending. Chang and Hoffman [ 10 ] associated narrow amplitude melodies with sadness, while Schimmark and Grob [ 40 ] related melodic amplitude with highly activated emotions. Regarding the melodic direction, Gerardi and Gerken [ 41 ] found a relationship between ascending direction and happiness and heroism, and between descending direction and sadness.

In relation to the mode, Tizón [ 42 ] stated that the major one is completely happy, while the minor one represents sadness. Thompson and Robitaille [ 43 ] considered that, in order to cause emotions such as happiness, solemnity or joy, composers use tonal melodies, while to obtain negative emotions, they use atonality and chromaticism.

In this research, the selected pieces (“Adagietto” from Gustav Mahler's Fifth Symphony, MML; and “Titans” from Alexander The Great from Vangelis, VML) are representative examples of the melodic, intervallic and modal characteristics previously exposed. Mahler's and Vangelis's pieces completely differ in modes and melodic amplitude (sad vs. heroism). Likewise, Mahler's piece is much more chromatic than Vangelis' one, which has a broader melody made up of third, fourth and fifth intervals, often representative of heroism. Those features justify the fact that they have been used as soundtracks in two films belonging to the epic genre (Alexander The Great, 2004) and drama (Death in Venice, 1971).

The musical piece that was performed by the students was chosen in order to be easy to learn in a few sessions, since they were not musicians. So, three musical pieces were used for the experimental conditions, the first two musical pieces were recordings in a CD, while the third one was performed by the subjects.

The three chosen pieces are described below:

Condition 1 (MML): “Adagietto” from Gustav Mahler’s Fifth Symphony (9:01 min), performed by the Berlin Philharmonic conducted by Claudio Abbado [ 44 ]. This is a sad, melancholic and dramatic piece that Luchino Visconti used in the film Death in Venice, made in 1971 and based on the book by Thomas Mann.

Condition 2 (VML): “Titans Theme” from Alexander the Great (3:59 min), directed by Oliver Stone and premiered in 2004, whose music was composed, produced and performed by Vangelis [ 45 ]. It has a markedly epic character with large doses of heroism and solemnity.

Condition 3 (BP): “Rhythm’s Blues” composed and played by Ana Bort (4:00 min). This is a popular African-American piece of music with an insistent rhythm and harmonically sustained by tonal degrees. This piece was performed by the participants using percussion instruments (carillons and a range of xylophones and metallophones).

The sample was divided into two groups (N 1  = 36 and N 2  = 35) that participated separately in all the phases of the study. The first two conditions (MML and VML) were carried out in each group's classroom, while the performance (BP) was developed in the musical instruments room. This room had 52 percussion instruments, including different types of chimes, xylophones and metallophones (soprano, alto and bass). It is a large space where there are only chairs and musical instruments and stands. The first group was distributed as follows: 6 chimes (3 soprano and 3 alto), 5 soprano xylophones, 5 alto xylophones, 5 bass xylophones, 5 soprano metallophones, 5 alto metallophones and 5 bass metallophones. The distribution of the second group was similar, but with one less alto metallophone.

Prior to the experiment, participants received two practical lessons in order to learn how to collectively perform the music score (third experimental condition). After the two practical lessons, during the next three sessions (leaving two weeks between each session), the experiment was carried out. In each session, an experimental condition was applied and PANAS was on-line administered online beforehand and afterwards (Pre-Post design). All participants were exposed to the three experimental conditions and completed the scale before and after listening to music.

In each of these three sessions, a different music condition was applied: MML in the first one, VML in the second one and BP in the third one.

As conditions VML and MML were listening to pieces of music, the instructions received by the subjects were: “You are going to listen to a musical piece, you ought to listen actively, avoiding distractions. You can close your eyes if you feel like to”. For the BP condition, they were said to play the musical sheet all together.

The aim of the study was to examine the effect of the music experience variable (with three levels: MML, VML and BP) in the Positive and Negative Affects subscales from the PANAS scale. The variable Moment was also studied to control biases and to analyze differences between the Pre and Post conditions.

The experiment was designed as a two-way repeated measure (RM) ANOVA with two dependent variables: Positive Affects and Negative Affects, one for each PANAS’ subscales.

The two repeated measures used in the experiment were the variables Musical Experience (ME), with three levels (MML, VML and BP) and the variable Moment, with two levels (PRE and POST). All participants were exposed to the three experimental conditions.

The design did not include a control group, similar to many other studies in the field of music psychology [ 27 , 30 ]. The control was carried out from the intra-subject pre-post measurement of all the participants. The rationale for this design lies in the complexity of the control condition (or placebo) design in psychology [ 46 ]. While placebos in pharmacological trials are sugar pills, in psychology it is difficult to establish an equivalent period of time similar to the musical pieces (e. g. 9 min) without activity, so that cognitive activity occurred during this period of time (e. g. daydreaming, reading a story, etc.) could bias and limit the generalization of results.

Additionally, one of the goals of this study was to compare the effects of listening to music compared to performance on affects. For this reason, two music listening experiences (MML and VML) and a musical performance experience (BP) were designed. In order to control potential biases, participants did not know the musical pieces in the experimental conditions and they had a low level of musical performance competence (musicians were excluded).

It was used SPSS statistics v.26 for the statistical analyzes.

Two ANOVA were performed. The first one, analyzed two dependent variables at the same time: Positive Affects (PA) and Negative Affects (NA).

In the second ANOVA, the 20 items of the PANAS scale were taken as dependent variables. The rest of the experimental design was similar to the first one, a two-way RM ANOVA with variables Musical Experience (ME) and Moment as repeated measures.

Examination of frequency distributions, histograms, and tests of homogeneity of variance and normality for the criterion measures indicated that the assumptions for the use of parametric statistics were met. Normality was met in all tests except for one, but the ANOVA is robust against this assumption violation. All the analyses presented were performed with the significance level (alpha) set at 0.05, two-tailed tests. Means and standard deviations for the 6 experimental conditions for both subscales, Positive Affects and Negative Affects, are presented in Table 1 .

Mauchly’s test of sphericity was statistically significant for Musical Experience and Musical Experience*Moment focusing on NA as the dependent variable ( p  < 0.05). The test only was significant for Musical Experience for PA as dependent variable ( p  < 0.05). The rest of the W’s Mauchly were not significant ( p  > 0.05), so we assumed sphericity for the non-mentioned variables and worked with the assumed sphericity univariate solution. For the variables which the W’s Mauchly was significant, the univariate solution was also taken, but choosing the corrected Greenhouse–Geisser epsilon approximation due to its conservativeness.

A significant principal effect of the Musical Experience variable F(1.710,119.691) = 22.505, p  < 0.05, η 2  = 0.243; the Moment variable F(1,70) = 45.291, p  < 0.05, η 2  = 0.393; and the Musical Experience*Moment interaction F(2,140) = 32.502, p  < 0.05, η 2  = 0.317 were found for PA.

Statistically significance was found for Moment F(1, 70) = 70.729, p  < 0.05, η 2  = 0.503 and Musical Experience*Moment interaction F(1.822, 127.555) = 8.594, p  < 0.05, η 2  = 0.109, but not for Musical Experience F(1.593, 111.540) = 2.713, p  < 0.05, η 2  = 0.037, for the other dependent variable, NA.

Table 2 shows pairwise comparisons between Musical Experience levels. Bonferroni’s correction was applied in order to control type I error. We only interpret the results for the Positive Affects because the Musical Experience effect was not statistically significant for Negative Affects. Results show that condition VML presents a significant higher punctuation in Positive Affects than the other two conditions ( p  < 0.05). It also shows that the musical condition MML is significantly above BP in Positive Affects ( p  < 0.05).

As regards Moment variable (Table 3 ), all but one Pre-Post differences were statistically significant ( p  < 0.05) for all the three conditions for both Positive and Negative Affects dependent variables. The Pre-Post difference found in Positive Affects for the VML Musical Experience did not reach the statistical level ( p  = 0.319).

Focusing on these statistically significant differences, we observe that conditions MML and BP, for PA, decreased from Pre to Post condition, indicating that positive emotions increased significantly between pre and post measures. On the other hand, for NA, all conditions increased from Pre to Post conditions, indicating that negative affects were decreased between pre and post conditions. Once again, one should bear in mind that items were reversed, thus, a higher scores in NA means a decrease in affects.

In order to measure the interaction effect, significant differences between simple effects were analysed.

The simple effect of Moment (level2-level1) in the first Music Experience condition (MML) in PA was compared with the simple effect of Moment (level2-level1) in the second Musical Experience condition (VML). Music Experience conditions 2–3 (VML-BP) and 1–3 (MML-BP) were compared in the same way. Thus, taking into account PA and NA variables, a total of 6 comparisons, 3 per dependent variable, were made.

The results of these comparisons are shown in Table 4 . Comparisons for PA range from T1 to T3 and comparisons for NA range from T4 to T6. All of them are significant ( p  < 0.05) which means that there are statistically significant differences between all the Musical Experience conditions when comparing the Moment (pre/post) simple effects.

In Table 5 , we can look at the differences’ values. As we said before the differences between Pre and Post conditions are significant when comparing the three musical conditions. The biggest difference for positive affects is between MML and BP (T3 = 8.443), and between VML and MML (T4 = − 6.887) for negative affects.

In this second part, the results obtained from the second two-way RM ANOVA with the 20 items as dependent variables are considered. Results of the descriptive analysis of each item: Interested, Excited, Strong, Enthusiastic, Proud, Alert, Inspired, Determined, Attentive, Active, Distressed, Upset, Guilty, Afraid, Hostile, Irritable, Ashamed, Nervous, Jittery, Scared ; in each musical condition: MML, VML and BP; and for the PRE and POST measurements, can be found in the Additional file 1 (Appendix A).

As regards the ANOVA test that compares the three experimental conditions in each mood, Mauchly’s Sphericity Test indicates that sphericity cannot be assumed for the musical experience in most of the variables of the items of effects, except for Interested, Alert, Inspired, Active and Irritable . For these items, the highest observed power index among Greenhouse–Geisser, Huynh–Feldt and Lower-bound epsilon corrections was taken for each variable. For the interaction Musical Experience*Moment, sphericity was not assumed for Distressed, Guilty, Hostile and Scared . For these items, the same above-cited criterion was followed.

Musical experience has a principal effect on all the positive affects, but only has it for 5 negative affects ( Nervous, Jittery, Scared, Hostile and Upset ) ( p  < 0.05). For more detail see Table S1 from Additional file 1 : Appendix B.

The principal effect of Moment is also statistically significant ( p  < 0.05) for all (positive and negative), but two items: Guilty ( p  = 0.073) and Hostile ( p  = 0.123). All the differences between Pre and Post for positive affects are positive, which means that scores in conditions Pre were significantly higher than in condition Post. The other way around occurs for negative affects, all the differences Pre-Post are negative, meaning that the Post condition is significantly higher than the Pre condition. For more detail, see Table S2 from Additional file 1 : Appendix B. In this way, Pre-post changes (Moment) improve affective states; the positive affects increase while the negative are reduced, except for Guilty ( p  = 0.073) and Hostile ( p  = 0.123).

Comparing the proportion of variance explained by the musical experienced and Moment (Tables s1 and s2 from the Additional file 1 : Appendix B), it is observed that most of the η 2 scores in musical experience are below 0.170, except Active and Alert , which are higher. On the other hand, the η 2 scores for Moment are close to 0.300. From these results we can state that, taking only one of the variables at a time, the proportion of the dependent variable’s variance explained by Moment is higher than the proportion of the dependent variable’s variance explained by Musical Experience.

The effect of interaction, shown in Table S3 from the Additional file 1 : Appendix B is significant in 7 positive moods ( Interested, Excited, Enthusiastic, Alert, Determined, Active and Proud ) and 4 negative moods ( Hostile , Irritable, Nervous , and Jittery ).

The pairwise comparisons of Musical Experience’s levels show a wide variety of patterns. Looking at Positive Affects, there is only one item ( Active ) which present significant differences between the three musical conditions. Items Concentrated and Decided do not present any significant difference between any musical conditions. The rest of the Positive items show at least one significant difference between conditions VML and BP. All differences are positive when comparing VML-MML, VML-BP MML-BP, except for Alert and Proud. So, in general, scores are higher for the first two conditions in relation to the third one, meaning that third musical condition presents the biggest increase for Positive Affects (remember items where reversed). For more detail see Additional file 1 : Appendix C.

As regard pairwise comparisons of Musical Experience’s for negative affects, only the items which had a significant principal effect of the variable Musical Experience are shown here. There is a significant difference between conditions VML and MML in item Nervous ; between VML and BP for Scared ( p  < 0.05). For Jittery ; all three conditions differed significantly from each other ( p  < 0.05). Conditions MML and BP differed significantly for Hostile ( p  < 0.05) and conditions VML and BP almost differed significantly for Upset item, but null hypothesis cannot be rejected as p  = 0.056. For more detail see Additional file 1 : Appendix C. All differences were negative when comparing VML-MML, VML-BP MML-BP, except for Nervous and Jittery . So, in general, scores are lower for the first and second condition in relation to the third one.

Positive effects increased significantly during the post phase of all the music experiences, showing that exposure to any of the three music stimuli improved positive affectivity. There were also significant differences between the three experiences in this phase, according to the following order of improvements in positive affectivity: (1) the rhythm and blues performance (BP), (2) listening to Mahler (MML) and (3) listening to Vangelis (VML). As regards the effects of the musical experience x Moment interaction , all the comparisons were significant, with bigger differences in the interpretation of the blues (BP) than in listening to Mahler (MML) and Vangelis (VML). However, the comparison between both experiences, although significant, was smaller. These results indicate that performing music is significantly effective in increasing positive effects. We will explain these results in greater detail below as regards the specific affective states.

As regards Negative Affects, the comparison of the simple effects showed that these decreased after the musical experiences, although in this first analysis the VML musical experience did not differ from the other two. However, the results of the effects of the interaction between musical experiencie x Moment showed that all the comparisons were significant, with a larger difference between MML and VML than the one between BP and each of the other experiences. Listening to Mahler (MML) was more effective in reducing negative affects, compared to both listening to Vangelis and interpreting the blues (BP). These results agree with previous studies [ 26 , 32 ], in which listening to sad music helped to reduce negative affectivity. In this study, it was the most effective condition, although exposure to all three musical experiences reduced negative affects.

The analysis of the specific affective states shows that most items that belong to Positive Affect scale are the most sensitive ones to the PRE-POST change, the different musical conditions and the interpretation of both effects. However, some items of the Negative Affect scale did not differ in the different music conditions or in the music experience × Moment interaction . For example, there were two items (Guilty and Hostile) that did not obtain significance. These results are consistent with the fact that music has certain limits as regards its impact on people’s affects and does not influence all equally. For example, Guilty has profound psychological implications that cannot be affected by simple exposure to certain musical experiences. This means we should be cautious in inferring that music alone can have therapeutical effects on complex emotional states whose treatment should include empirically validated methods. Also, emotional experiences are widely diverse so that any instrument used to measure them is limited as regards the affective/emotional state under study. These results suggest the importance of reviewing the items that compose the PANAS scale in musical studies to adapt it in order to include affective states more sensitive to musical experiences and eliminate the least relevant items.

The analysis of the results in the specific affective states, allows us to delve deeper into each experimental condition. Thus, regarding the results obtained in the complete scale of PANAS, listening to Mahler (MML), causes desirable changes by raising two positive affects ( Inspired and Attentive ) and reducing 10 negative affects ( Distressed, Upset, Afraid, Hostile, Irritable, Ashamed, Nervous, Jittery, and Scared ). This shows that this music condition had a greater effect on the negative affects than the other ones. These results agree with previous studies [ 26 , 32 ], which found that sad music could effectively reduce negative affects, although other studies came to the opposite conclusion. For instance, Miller and Au [ 31 ] found that sad music did not significantly change negative affects. Some authors [ 47 , 48 ] have argued that adults prefer to listen to sad music to regulate their feelings after a negative psychological experience in order to feel better. Taruffi and Koelsch [ 49 ] concluded that sad music could induce listeners to a wide range of positive effects, after a study with 772 participants. In order to contribute to this debate. It would be interesting to control personality variables that might explain these differences on the specific emotions evoked by sad music. In this study, it has been shown that a sad piece of music can be more effective in reducing negative affects than in increasing positive ones. Although the results come from undergraduate students, similar outcomes could be obtained from children and adolescents, although further research is required. In fact, Borella et al. [ 50 ] studied the influence of age on the effects of music and found that the emotional effects influenced cognitive performance (working memory) in such a way that the type of music (Mozart vs. Albinoni) had a stronger influence on young people than on adults. Kawakami and Hatahira [ 28 ], in a study on 84 primary schoolchildren, also found that exposure to sad music pleased them and their level of empathy correlated with their taste for sad music.

Listening to Vangelis (VML) increased 3 positive affects ( Excited, Inspired and Attentive ) and reduced 8 negative affects ( Distressed, Upset, Afraid, Irritable, Ashamed, Nervous, Jittery , and Scared ). Surprisingly, two positive affects were reduced in this experimental condition ( Alert and Attentive ). It could be explained due to the characteristic ostinato rhythm of this piece of music. It was found a similar effect in the study by Campbell et al., [ 26 ] in which sad music reduced both positive and negative affects. This musical condition also managed to modify negative affects more than positive ones.

Performing the blues (BP) increased all 10 positive affects, indicating that performing is more effective in increasing positive affects than listening. These results agree with the study by Dunbar et al. [ 29 ], who found that music performance significantly increased positive affects.

Performing the blues (BP) reduced 6 negative affects, although it was more effective in increasing positive affective states. Vigorous rhythmic music was also found to be positively associated with the use of all the forms of regulating emotions, which suggests that this type of music is especially useful for emotion modulation [ 51 ]. It was found an exception, since Jittery increased after the blues performance. It could be explained by the negative experience that is sometimes associated with music performance. Therefore, it should be taken into account that music performance could increase some negative effects. For example, Dimsdale et al. [ 52 ] found that a strong negative emotional response to a certain type of music in adolescents was related to risk behaviour, indicating that research into the repertory of music experiences needs to be broadened to diverse styles in different age groups to identify all the types of emotional response and their psychological consequences. However, this result should be taken with caution and further research should focus on whether the effect of increased agitation is usual after music performances.

To sum up, this study contributes to the scientific field on the following points: (1) all the musical experiences had significant effects on improving emotional states, increasing positive affects and decreasing the negative ones, which shows the importance of musical experiences on improving the affective sphere; (2) the specific affects that increased, decreased or did not change for each musical experience were identified, providing specific and useful keys for the design of future interventions; and (3) the differences between various types of musical experiences were analyzed, finding more improvements in the performing conditions than in the listening ones.

Limitations and future directions

Limitations.

The sample, made up of university students with a very homogeneous profile in terms of age and sociodemographic characteristics, could limit the generalization of the results. In addition, the low percentage of men in the sample could also affect the generalizability of the results, although no previous studies have reported gender-based differential effects on the positive and negative affects after musical experiences.

Besides, the choice of the pieces of music was based on theoretical criteria and students’ music preferences were not taken into account. This will be included in future research, since the specific choice of the pieces could affect the positive or negative valence of participants’ emotions. However, the goal of using pieces of music not chosen by participants was to elicit new musical experiences for them. Furthermore, no participant was a musician and none of them had previous knowledge of any of the pieces, which may lead to a bias in the results.

In relation to this, the huge amount of available pieces of music, all of them influenced by their cultural and historical context, make it difficult to generalize that certain music parameters correlate with specific emotions. It would be necessary a cross-cultural approach to reach that conclusion.

Future directions

It is recommended to introduce the variables of music preferences and music history to control their effect on the results and to be able to compare the different musical parameters of the pieces together with participants’ preferences.

Likewise, it would be interesting to identify the affects with a greater or lesser degree of influence by music, to adjust the psychological evaluation instrument to the characteristics of the experiment, including items of emotions that can be modified after exposure to a music experience.

The PANAS manual [ 39 ] indicates that a wide variety of affective states (60) and eight different temporal instructions were included in its construction, showing its great versatility. In further research, this instrument should be adapted to for a more specific application to music studies. For instance, by including other emotional states that could be related with the influence of music (e.g. Tranquility , Gratitude , Elevation ), in order to measure more exactly the effects of music on people’s affective experiences.

Accordingly, it would be interesting to evaluate participants' affective traits to establish a baseline and control personality variables, helping to delve into the different levels of the hierarchical structure of affectivity and its relationship with the various music parameters.

Finally, it is recommended that the psychology of music include objective psychophysiological measurements together with self-report evaluations, so that conclusions arising from the experiments have greater robustness and can increase the impact of the contribution to the scientific community.

This study have shown how different music experiences, such as listening and performing, influence the changes in positive and negative affects in student teachers. The results show that the three musical experiences studied are effective in improving the affects by comparing the emotional states before and after the music experiences. It was also showed that there are differences between the effects obtained in each of the music experiences. Besides, improving both types of affects will depend largely on the selected music for the purpose. Although further evidence is required, the results support the importance of music in education, since it provides tools to increase positive affects and to decrease the negative ones, which is important for emotional intelligence development [ 53 , 54 ].

The three music experiences studied are more effective in reducing negative emotional states than in increasing the positive ones. This finding provides useful clues for music teachers to provide strategies that favor emotional regulation. For instance, in order to reduce hostility, irritability and nervousness, students could be exposed to musical auditions of both sad and solemn pieces, choosing musical pieces with similar characteristics to those described in this study. These auditions will be a resource for stress management in the classroom, as well as a tool that students can adopt and generalize to other contexts. Moreover, it is highly likely that students have not heard this type of music before and this experience could increase their repertoire of musical preferences, enhancing their emotional regulation.

The blues performance had a greater impact on participants' positive affects than listening to the other two pieces so, if any teacher wants to increase them (e.g., enthusiasm, interest, etc.), students could be asked to perform simple pieces such as Rhythm's Blues. In this way, musical performance could increase students' resources, contributing to higher levels of motivation, concentration and interest, which promotes learning [ 55 , 56 , 57 , 58 ]. Likewise, it could be very useful for elementary and secondary music teachers, who will be able to contribute to socio-emotional improvement and personal development of their students. Particularly, musical experiences could be a valuable resource for secondary teachers, since music is important in adolescents' lives and can be an interesting tool for meeting their emotional needs [ 59 ]. This is supported by Kokotsaki and Hallam [ 60 ], who consider that performing music helps students feel like active agents of a group, develop a strong sense of belonging, gain popularity, make "like-minded" relationships, improve their social skills and foster a strong sense of self-esteem and satisfaction.

This study shows that experiencing with various unknown musical pieces can have positive effects on emotions. According to this finding, university professors of Teaching grade in music education should encourage future teachers to experience various musical styles, rhythms and tonalities, avoiding prejudices. Thereby, future music teachers will be able to use a diversity of musical experiences that broaden the emotional effects and fulfill the socio-emotional function of music education. In relation to Fredrickson's 'broaden‐and‐build' framework of positive emotions [ 30 ], music can become a mean of widening other positive emotional states, constructing personal resources and transforming people, and contribute to an upward spiral of positive emotions. Taking into account the underlying psychological mechanisms of the impact of music on the emotional states it will be possible to use it to improve emotional area and other aspects of the personal sphere, as Chang et al., [ 10 ] maintain. Therefore, music education is an important resource to improve the emotional development of students.

Availability of data and materials

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We should like to express our gratitude to the Valencia University student teachers for their disinterested and valuable contribution to this study.

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Blasco-Magraner, J.S., Bernabé-Valero, G., Marín-Liébana, P. et al. Changing positive and negative affects through music experiences: a study with university students. BMC Psychol 11 , 76 (2023). https://doi.org/10.1186/s40359-023-01110-9

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Understanding the Influence of Music on Emotions: A Historical Review

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Kimberly Sena Moore, Understanding the Influence of Music on Emotions: A Historical Review, Music Therapy Perspectives , Volume 35, Issue 2, October 2017, Pages 131–143, https://doi.org/10.1093/mtp/miw026

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Music has long been thought to influence human emotions. There is significant interest among researchers and the public in understanding music-induced emotions; in fact, a common motive for engaging with music is its emotion-inducing capabilities ( Juslin & Sloboda, 2010). Traditionally, the influence of music on emotions has been described as dichotomous. The Greeks viewed it as either mimesis , a representation of an external reality, or catharsis , a purification of the soul through an emotional experience ( Cook & Dibben, 2010). This type of dichotomous viewpoint has persisted under various labels, such as formalist versus absolutist, and referential versus expressionist ( Meyer, 1956). However, these perspectives all emerged from musicology. Outside musicology, the scientific study of emotions was intermittent and, until recently, references to music’s effect on emotions were rare ( Sloboda & Juslin, 2010). Since the 1990s, there has been increased interest in studying music-induced emotions, particularly in psychology ( Juslin & Sloboda, 2010). This interest extends to the music therapy profession as well. For example, a professional music therapist in the United States is required to be able to develop and implement music therapy experiences designed to focus on emotion-related treatment goals, such as the ability to empathize, and the client’s overall affect, mood, and emotions ( Certification Board for Music Therapists [CBMT], 2015), and must apply knowledge of music-based emotional responses ( American Music Therapy Association [AMTA], 2013). Given the increased interest in psychology and the clinical implications for the music therapist, it seems timely to analyze and reflect on how the understanding of music-induced emotions has evolved in order to support current and future research and clinical practice. As current understanding is built upon prior knowledge, a historical review can serve to examine previous directions and help inform future study ( Hanson-Abromeit & Davis, 2007). Thus, the purpose of this inquiry was to provide a historical overview of prominent theories of music and emotion and connect them to current understanding. More specifically, the objectives were:

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Exposure to different kinds of music influences how the brain interprets rhythm

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When listening to music, the human brain appears to be biased toward hearing and producing rhythms composed of simple integer ratios — for example, a series of four beats separated by equal time intervals (forming a 1:1:1 ratio).

However, the favored ratios can vary greatly between different societies, according to a large-scale study led by researchers at MIT and the Max Planck Institute for Empirical Aesthetics and carried out in 15 countries. The study included 39 groups of participants, many of whom came from societies whose traditional music contains distinctive patterns of rhythm not found in Western music.

“Our study provides the clearest evidence yet for some degree of universality in music perception and cognition, in the sense that every single group of participants that was tested exhibits biases for integer ratios. It also provides a glimpse of the variation that can occur across cultures, which can be quite substantial,” says Nori Jacoby, the study’s lead author and a former MIT postdoc, who is now a research group leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt, Germany.

The brain’s bias toward simple integer ratios may have evolved as a natural error-correction system that makes it easier to maintain a consistent body of music, which human societies often use to transmit information.

“When people produce music, they often make small mistakes. Our results are consistent with the idea that our mental representation is somewhat robust to those mistakes, but it is robust in a way that pushes us toward our preexisting ideas of the structures that should be found in music,” says Josh McDermott, an associate professor of brain and cognitive sciences at MIT and a member of MIT’s McGovern Institute for Brain Research and Center for Brains, Minds, and Machines.

McDermott is the senior author of the study, which appears today in Nature Human Behaviour. The research team also included scientists from more than two dozen institutions around the world.

A global approach

The new study grew out of a smaller analysis that Jacoby and McDermott published in 2017. In that paper , the researchers compared rhythm perception in groups of listeners from the United States and the Tsimane’, an Indigenous society located in the Bolivian Amazon rainforest.

To measure how people perceive rhythm, the researchers devised a task in which they play a randomly generated series of four beats and then ask the listener to tap back what they heard. The rhythm produced by the listener is then played back to the listener, and they tap it back again. Over several iterations, the tapped sequences became dominated by the listener’s internal biases, also known as priors.

“The initial stimulus pattern is random, but at each iteration the pattern is pushed by the listener’s biases, such that it tends to converge to a particular point in the space of possible rhythms,” McDermott says. “That can give you a picture of what we call the prior, which is the set of internal implicit expectations for rhythms that people have in their heads.”

When the researchers first did this experiment, with American college students as the test subjects, they found that people tended to produce time intervals that are related by simple integer ratios. Furthermore, most of the rhythms they produced, such as those with ratios of 1:1:2 and 2:3:3, are commonly found in Western music.

The researchers then went to Bolivia and asked members of the Tsimane’ society to perform the same task. They found that Tsimane’ also produced rhythms with simple integer ratios, but their preferred ratios were different and appeared to be consistent with those that have been documented in the few existing records of Tsimane’ music.

“At that point, it provided some evidence that there might be very widespread tendencies to favor these small integer ratios, and that there might be some degree of cross-cultural variation. But because we had just looked at this one other culture, it really wasn’t clear how this was going to look at a broader scale,” Jacoby says.

To try to get that broader picture, the MIT team began seeking collaborators around the world who could help them gather data on a more diverse set of populations. They ended up studying listeners from 39 groups, representing 15 countries on five continents — North America, South America, Europe, Africa, and Asia.

“This is really the first study of its kind in the sense that we did the same experiment in all these different places, with people who are on the ground in those locations,” McDermott says. “That hasn’t really been done before at anything close to this scale, and it gave us an opportunity to see the degree of variation that might exist around the world.”

Cultural comparisons

Just as they had in their original 2017 study, the researchers found that in every group they tested, people tended to be biased toward simple integer ratios of rhythm. However, not every group showed the same biases. People from North America and Western Europe, who have likely been exposed to the same kinds of music, were more likely to generate rhythms with the same ratios. However, many groups, for example those in Turkey, Mali, Bulgaria, and Botswana showed a bias for other rhythms.

“There are certain cultures where there are particular rhythms that are prominent in their music, and those end up showing up in the mental representation of rhythm,” Jacoby says.

The researchers believe their findings reveal a mechanism that the brain uses to aid in the perception and production of music.

“When you hear somebody playing something and they have errors in their performance, you’re going to mentally correct for those by mapping them onto where you implicitly think they ought to be,” McDermott says. “If you didn’t have something like this, and you just faithfully represented what you heard, these errors might propagate and make it much harder to maintain a musical system.”

Among the groups that they studied, the researchers took care to include not only college students, who are easy to study in large numbers, but also people living in traditional societies, who are more difficult to reach. Participants from those more traditional groups showed significant differences from college students living in the same countries, and from people who live in those countries but performed the test online.

“What’s very clear from the paper is that if you just look at the results from undergraduate students around the world, you vastly underestimate the diversity that you see otherwise,” Jacoby says. “And the same was true of experiments where we tested groups of people online in Brazil and India, because you’re dealing with people who have internet access and presumably have more exposure to Western music.”

The researchers now hope to run additional studies of different aspects of music perception, taking this global approach.

“If you’re just testing college students around the world or people online, things look a lot more homogenous. I think it’s very important for the field to realize that you actually need to go out into communities and run experiments there, as opposed to taking the low-hanging fruit of running studies with people in a university or on the internet,” McDermott says.

The research was funded by the James S. McDonnell Foundation, the Canadian National Science and Engineering Research Council, the South African National Research Foundation, the United States National Science Foundation, the Chilean National Research and Development Agency, the Austrian Academy of Sciences, the Japan Society for the Promotion of Science, the Keio Global Research Institute, the United Kingdom Arts and Humanities Research Council, the Swedish Research Council, and the John Fell Fund.

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Music’s power over our brains

Armed with more interest and funding, researchers are investigating how music may enhance brain development and academic performance and even help people recover from COVID-19

Vol. 51, No. 8 Print version: page 24

• Cognition and the Brain
• Neuropsychology

One of the most poignant early images of the coronavirus pandemic was of Italians playing music and singing from their balconies even as the virus ravaged their cities. Others soon followed suit, including pop stars streaming live performances from their homes and choirs sharing concerts via Zoom—all trying to provide connection during a frightening and uncertain time.

Of course, music has been bringing people together for millennia, and not just during crises. And in the last few decades, investigators have been training their attention on the so-called universal language of music—how it affects our brains and how it might be used to facilitate health and healing. That interest is now being fueled by new research attention and funding: In June, the Global Council on Brain Health, an independent science and policy collaborative devoted to understanding brain health, released a report concluding that music has “significant potential to enhance brain health and well-being for individuals of different ages and different levels of health” and making recommendations for future study. And last year, Sound Health , a program launched by the National Institutes of Health (NIH) and the Kennedy Center, in association with the National Endowment for the Arts (NEA), awarded $20 million over five years to support its first 15 research projects on the topic, including several headed by psychologists.

“Why is music so captivating for us?” asks Thomas Cheever, PhD, staff assistant to NIH Director Francis Collins, MD, PhD, for Sound Health and a program director at the National Institute of Neurological Disorders and Stroke. “The more we understand about that, the more fascinating it’s going to be, and the more we are going to learn about how the brain works in general.” Psychologists and neuroscientists are particularly interested to find out which neural pathways are affected by music, how music influences children’s development, and how music interventions may help people with a range of physical and mental health conditions, including Alzheimer’s disease, schizophrenia, delirium and Parkinson’s disease.

And they are adding COVID-19 to the conditions they are trying to ease. Babar A. Khan, MD, assistant professor of medicine at the Indiana University School of Medicine in Indianapolis, for example, is using a Sound Health grant to test a music intervention with patients who have delirium, including those with COVID-19. Delirium—an acute, short-term condition marked by confusion and emotional disruption—afflicts as many as 80% of patients who are in the intensive care unit for respiratory failure, including those with COVID.

If the intervention proves helpful, says Khan, “it will be used immediately during the course of the current pandemic.”

Enhancing child development

One ongoing research interest is how music may affect youth in terms of language development, attention, perception, executive function, cognition and social-emotional development. Psychologist Assal Habibi, PhD, an assistant research professor at the University of Southern California Dornsife’s Brain and Creativity Institute, has been investigating these topics for the past seven years in collaboration with the Los Angeles Philharmonic Youth Orchestra, known as YOLA, an after-school program that brings low-income youngsters together to learn, play and perform music. Now in its final year, the study has been tracking brain and learning outcomes of 75 children who are either participating in YOLA, a community sports program or no after-school program.

Data published from the first few years of the intervention show that YOLA participants gradually develop auditory and cognitive advantages over youth who aren’t involved in music. After the second year of the study, the YOLA participants showed greater ability to perceive pitch, rhythm and frequency of sounds, as well as enhanced development in the auditory pathway, the neurological route that connects the inner ear to auditory association areas in the brain ( Developmental Cognitive Neuroscience , Vol. 21, 2016). After the third and fourth years in the program, they also began to perform better on tasks unrelated to music, including on executive function tasks involving working memory and delayed gratification—likely because of the discipline required to patiently learn pieces of music, Habibi says. In addition, youth involved in YOLA showed greater development in brain areas related to language and auditory processing, and greater neuronal connectivity in the corpus callosum, the nerve bundle that connects the brain’s right and left hemispheres ( Cerebral Cortex , Vol. 28, No. 12, 2018).

“We obviously expected their musical skills to get better,” she says, “but it seems a broad range of other skills are also impacted by music.”

Habibi now has a grant from the NEA to follow these same children into adolescence to see whether the brain benefits they derived early on translate into real-life behaviors and decisions as teens—choice of peers, for example, or whether they show up to class. She also has an NIH Sound Health grant to compare differences in executive functioning among bilingual youth who are learning music and those who are learning music but only speak one language.

“As a developmental psychologist, I don’t think there’s just one pathway to better executive function in children,” she explains. “So, it will be interesting for us to identify different mechanisms and understand how each one works.”

Music and mental illness

Researchers are also exploring whether music may prove to be a helpful therapy for people experiencing depression, anxiety and more serious mental health conditions. A study of 99 Chinese heart bypass surgery patients, for example, found that those who received half an hour of music therapy after the operation—generally light, relaxing music of their own choice—had significantly lower self-reports of depression and anxiety than those who rested or received conventional medical check-ins in the same time frame ( Journal of Cardiothoracic Surgery , Vol. 15, No. 1, 2020). Meanwhile, in conjunction with the Global Council on Brain Health’s strong endorsement of more research on music and brain health, an AARP survey of 3,185 adults found that music has a small but statistically significant impact on people’s self-reported mental well-being, depression and anxiety.

Others are examining whether music interventions could benefit those with serious mental illness. Yale experimental psychologist and cognitive neuroscientist Philip Corlett, PhD, for example, will use a Sound Health grant to test an intervention in which people with schizophrenia come together to write and perform music for one another. The work builds on Corlett’s developing model of schizophrenia, which maintains that people with the disorder have difficulty revising and updating their views of self and reality based on newly emerging events, considered a central feature of the healthy human brain. Making music with others—which involves both positive social interactions and a type of expression with predictable outcomes—could allow participants to experience more realistic predictions and hence foster their sense of predictability and security, he hypothesizes.

“If we can show that music-making changes the mechanisms that we think underwrite these symptoms [of schizophrenia],” Corlett says, “then we can figure out its active ingredients and ultimately come up with ways to deliver this to people who need it.”

Therapy for older adults

The impact of music on older adults’ well-being is likewise of keen interest to researchers, who are looking at how music therapy may help verbal fluency and memory in people with Alzheimer’s disease ( Journal of Alzheimer’s Disease , Vol. 64, No. 4, 2018) and how singing in a choir may reduce loneliness and increase interest in life among diverse older adults ( The Journals of Gerontology: Series B , Vol. 75, No. 3, 2020). Music even shows promise in preventing injury: A study by Annapolis, Maryland–based neurologic music therapist Kerry Devlin and colleagues showed that music therapy can help older adults with Parkinson’s disease and other movement disorders improve their gait and reduce falls ( Current Neurology and Neuroscience Reports , Vol. 19, No. 11, 2019).

Still others are investigating how music can help people recover from serious illnesses and conditions, including, now, COVID-19. In a pilot study, Khan of Indiana University showed that patients with delirium on mechanical ventilators who listened to slow-tempo music for seven days spent one less day in delirium and a medically induced coma than those listening to their favorite music or to an audio book ( American Journal of Critical Care , Vol. 29, No. 2, 2020). Now, with his Sound Health grant, he is comparing the effects of slow-tempo music or silence on 160 participants with delirium, including COVID-19 patients on ventilators in hospitals in Indianapolis.

Studies like these underscore music’s potential as a safe and effective medical intervention, as well as the importance of conducting more research on which kinds of music interventions work for whom, when and how, including during this difficult time, adds Cheever.

“How do we get [music therapy] into the same realm as other interventions that are the standard of care for any given indication?” he says. “The answer to that, I think, is a solid evidence base.”

Further reading

NIH/Kennedy Center Workshop on Music and the Brain: Finding Harmony Cheever, T., et al., Neuron , 2018

Effects of Music Training on Inhibitory Control and Associated Neural Networks in School-Aged Children: A Longitudinal Study Hennessy, S.L., et al., Frontiers in Neuroscience , 2019

Decreasing Delirium Through Music: A Randomized Pilot Trial Khan, S.H., et al., American Journal of Critical Care , 2020

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How music affects society

Music is a remarkable part of human society. The fact that music has been part of our cultures for so long shows how much of an integral part it plays in what makes us human beings. The aim of this report is to understand the various ways that music can influence society. This research attempts to explain the way that music can affect human behaviour through focus on the ‘self’, Space and place, and Social community. Music can have a profound effect on the lives of human being, enriching their everyday experiences and changing the way that they view the world. As far back as ancient Greece, the importance of music has been noted and studied, which has led to modern research uncovering just how important it can be. This dissertation investigates the links between music and the formation of identities; including emotional effects of music and the creation of subcultures, whilst looking at research which links music taste with social structures such as class and ethnicity. It examines the way that music can improve intellect, physical activity and create trends within consumerist activity. Finally, it seeks to examine how music can be employed towards specific goals; from media usage all the way to its influences on social change. There is no doubt that music effects society, influencing the human race from the smallest areas of social behaviour to the largest. Thus, the following dissertation aims to uncover the various ways that music influences society and just how important these influences are to our way of life.

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Researchers working within the field of music and society often comment that they wish to use their research for the betterment of society and individuals, wherever possible. In many cases, this process of betterment requires some sort of behavioral change—whether this is changing poor habits to promote healthy living and thinking or changing destructive behavior in order to lead more productive and connected lives. It can increasingly be seen in the world today that social behavior has a complex array of influences and motivations and rarely is empirical evidence one of them. No amount of thoroughly researched evidence or logically developed arguments influences this behavior. Brexit and the Trump administration are two examples of this phenomenon. What seems to influence this seemingly bizarre social behavior is a collective belief in a narrative. The narrative needs to speak to common emotions, senses of identities and memories, but it does not need to necessarily be supported by...

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In the past decade, with the rapid development of cognitive neuroscience and brain function detection technology, the relationship between music and brain has increasingly attracted the attention of neuroscientists. More and more research shows that the influence of music on people is not only emotional; it has a positive effect on brain development and cognitive development. Different states of the brain understand music in different ways, stimulating specific areas of the left and right hemispheres of the brain to evoke specific “music memories”, causing corresponding physiological changes. Music activities must be based on brain mechanisms and neural mechanisms to complete, and the most basic way of human brain and nervous system activity is communication and signal transmission between cells. In this paper, we explored the influence of music on the brain. We compared the differences in cognition and memory within a group of students with various academic performances. Through the test of color memory, the length of response time is used as a cognitive ability scale. The results showed that the experimental group performed better, confirming that listening to music can have certain positive effect on cognitive ability, specifically, improving memory. Listening to music could enhance the performance and reduce errors in the questions that the color of the word matched.

Music , Brain Plasticity , Music Therapy , Cognition and Memory

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1. Introduction

With the rapid development of cognitive neuroscience and neuroimaging technology, there are more and more researches focused on exploring the relationship between music and its effects on the brain. Since music is fundamentally transmitted in the form of sound waves, its interaction with the brain waves has always been the center of many research fields. Research shows that the influence of music on people is not only emotional; it has a positive effect on brain development and cognitive development. Different states of the brain understand music in different ways, stimulating specific areas of the brain, causing corresponding physiological effects. As a result, many researchers see music as a potential therapeutic tool than a mere entertainment, for example, the potential effect of music therapy on Alzheimer’s Disease, anxiety, and people with concentration deficiency. With more understanding of this research concentration, more therapeutic options could benefit a broader patient community by providing a higher living quality.

Previous research shows that music can stimulate the areas relating to motor, language, and cognitive functions simultaneously, and effectively improve patients’ cognitive and working memory. There’s also evidence showing that music training is closely connected to the stimulation of neurons and executive function of the prefrontal cortex. As a result, we seek to find out whether music training could effectively improve the participants’ memory function, subsequently improving their learning abilities. We will also explore whether classical music could effectively improve the participants’ concentration and learning efficiency. In this study, we performed two sets of experiment to test the connection between music and memory function.

2. Music and Memory of Brain

2.1. Memory

Generally speaking, the processing of forming a memory involves encoding, storing, retaining, and subsequently recalling information and past experiences. Dating back to 1904, a German evolutionary biologist Richard Semon put forward a theory, suggesting that Mneme is a fundamental organic plasticity that allows the preservation of experience; it is Mneme “which in the organic world links the past and present in a living bond” [1] [2]. He proposed the idea of engram, which refers to the change in the nervous system, or the “memory trace” that preserves the effects of experience. He posited that a memory would leave a physical trace in the brain; and the brain, when stimulated, would replay the memory. Semon’s theory about memory inspired many scientists, and it is greatly reflected on the modern theories of memory. In 2012, by employing optogenetic technology, Susumu Tonegawa’s lab at MIT first showed that an engram was real [3]. The incident of a 27-year-old American Henry Molaison had his hippocampi removed as a means to cure his seizures but lost his ability to make new memories led to the discovery that hippocampus is required to attain episodic memories. However, these detailed memories are not stored in the hippocampus, instead, are transferred to the brain cortex. In 2017, Tonewaga’s lab has revealed the details of how engrams are made in the hippocampus and then uploaded for storage in the brain cortex [1]. Semon proposed his idea of engrams decades before researchers understood neural signals are sent by electronic impulses. Since then, researches has decoded much of the electrical signaling, and shown how learning and memory correspond to the strengthening of connections between individual neurons.

2.2. The Relationship between Memory Differences and Music Training

Although most studies that examined associations between music training and cognitive abilities had correlational designs, the prevailing bias is that music training causes improvements in cognition [4] [5]. In order to explore whether the differences in individual memory and personality are related to the acceptance of music, we designed the following experiments.

Participants were 8 students selected from an international high school in China. They were adolescents at a stage of rapid mental development through rigorous academic trainings. Participants were divided into four categories (Good, Fair, Limited, and Weak) according to their school academic performance differences. Through the test of color memory, the length of response time is used as a cognitive ability scale. Before the test, as a control group, we analyzed the cognitive ability and academic differences of the four groups of students; then let them accept the same music training, and once again measured the correlation between cognitive ability and academic ability. The correlation results and analysis were given as followings ( Figure 1 and Figure 2 ).

Figure 1 . Cognitive analysis before accepting music. (a) Analysis of reaction time before accepting music; (b) Analysis of errors made before accepting music.

Figure 2 . Cognitive analysis after accepting music. (a) Analysis of reaction time after accepting music; (b) Analysis of errors made after accepting music.

Both of the trials before and after students listening to music show a strong, direct and positive relationship between the mean time of response and the academic performances of the participants (r 2 = 0.9118, r 2 = 0.9855). Students in the Good category has the shortest response time compare to other categories. The worse the academic performance, generally the more time the participants spend answering the questions. Similarly, both trials of before and after students listening to music show a direct and positive relationship between the mean errors and the academic performances of the participants (r 2 = 0.5715, r 2 = 0.8972). Students with better academic performance would make fewer errors, and students with worse academic performances would make relatively more errors. Therefore, there is a positive correlation between academic achievement and students’ average reaction time and average error.

To figure out whether music has influences on matched response time and unmatched response time, paired t-tests are performed at α = 0.05 significance level. The null hypothesis is μ dmatched = 0, and the alternative hypothesis is μ dmatched > 0, where μ dmatched is the difference in the mean of the matched median response time before and after listening to music. A paired t-test is used, where t = x dmatche d/(S dmatched ), x dmatched = 10.88, S dmatched = 79.36, n = 8. The resulting t value is 0.39 with degrees of freedom of 7. The p-value is 0.35. Since the p-value is bigger than the significant level (α = 0.05), the result failed to reject the null hypothesis, thus there is no convincing evidence that listening to music could enhance the performance and reduce in errors in the questions that the color of the word matched.

In addition to the matched questions, a paired t-test is performed at α = 0.05 significance level to determine the significance of listening to music on unmatched question response. The null hypothesis is μ dunmatched = 0, and the alternative hypothesis is μ dunmatched > 0, where μ dunmatched is the difference in the mean of the unmatched median response time before and after listening to music. A paired t-test is used, where t = x dunmatched /(S dunmatched ), x dunmatched = −36.38, S dunmatched = 83.32, n = 8. The resulting t value is −1.23 with degrees of freedom of 7. The p-value is 0.87. Since the p-value is bigger than the significant level (α = 0.05), the result failed to reject the null hypothesis, thus there is no convincing evidence that listening to music could enhance the performance and reduce errors in the questions that the color of the word did not match.

2.3. Enhance Memory

As early as the 1960s, Bulgarian Lozanov created the “implicit learning method”. He believed that soothing and beautiful classical music can help ease emotional tension, improve concentration, and learn more efficiently [6]. Some scholars believe that musical stimuli generate additional information that interferes with attention, affecting people’s memory efficiency [7]. In the past ten years, scientists have extensively explored the relationship between music and memory.

For the molecular biological basis of music affecting memory, researchers believe that music stimulation can change the secretion of some neurotransmitters and peptide hormones, thereby enhancing people’s memory. Recent studies have found that the secretion of vasopressin AVP (4 - 8) is significantly increased when the music is felt. It can significantly activate the protein kinase MAPK, which significantly increases the transcription level of the “immediate early gene” c-fos, while c-fos It has a crucial influence on synaptic differentiation and learning and memory [4]. Wang Zengxian et al. (2004) found that music enhances neuronal NMDA receptors and mRNA expression of NMDA receptors [7]; NMDA is one of the most critical proteins for long-term effect (LTP) induction, in the hippocampal neural pathway, NMDA receptors play an important role in the triggering of LTP [8].

3. Music and Brain Plasticity

3.1. Brain Plasticity

Music, as an important form of artistic expression, has long been a part of art research. In recent years, with the rapid development of brain imaging technologies such as event-related potential (ERP), electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI), music has gradually been incorporated into cognitive neuroscience. Brain plasticity means that the brain can be modified by the environment and experience, and has the ability to shape the structure and function of the brain under the influence of the external environment and experience.

Animal experiments have found that music can promote brain development in rats and mice, enhance nerve plasticity, and improve their spatial learning and memory. The auditory cortex NMDA receptor is a vital neural connective pathway in mammalian learning and memory processes, including humans. After listening to Mozart’s “Big Piano Sonata”, the expression of NMDA subunit NR2B protein in 2 weeks old mice increased significantly, and the spatial memory ability increased accordingly. In addition, the improvement of memory ability depends on the length of music stimulation time and is related to the up-regulation of NMDA receptor expression in hippocampal formation [8]. The University of California, Berkeley, Diamond, and others have performed a series of well-known experiments in white mice. The results showed that the thickness of the gray matter of white rats in the living environment increased, and the proportion of the cortex in the whole brain increased, and each nerve cell increased by 15%. The study also found that white mice living in a rich environment were 25% more connected than white mice in the normal environment, and they performed better in the test. More importantly, Greenough also found that when the adult mouse responds to a complex environment, the brain also forms new synapses.

Related experiments have also shown that after special training, brain-related cortical representations can change significantly. This shows that the cortical representation area of feeling, movement, language, cognition, etc. is not fixed, but a dynamic structure. Experience or training can reorganize the fine structure of the representative area. This empirically dependent structural reorganization can be used to explain why people or animals learn certain intelligence and motor skills [9].

3.2. The Influence of Music on Brain Plasticity

As we all know, music is the sound art that shapes the artistic image through sound. Whether it is the listening and feeling of various factors such as pitch, tone, rhythm, harmony and melody, or integrating these elements into a complete piece for performance. The auditory cortex in the individual brain plays an important role in monitoring and recognizing, and thus involves complex brain activities such as sound analysis, auditory memory, and auditory scene analysis [10] [11].

Christo Pantev’s research (1998) in Master University shows that musicians are particularly sensitive to piano sounds, mainly because their auditory cortical activity area is significantly enhanced when they hear piano sounds. Those who learn instrumental music before the age of 9 have the largest area of auditory cortex activity, but ordinary people do not have such significant changes [12]. Thomas Elbert (1995) of Konstanz University in Germany reported that the cortical region of the left-handed activity of string players (average age 20 years) is larger than the average person, and the younger the learning instrument is, the more relevant. The area of the cortex is also larger. A comparative study of musicians and non-musicians by Schlaug et al. (1995) found that the left side of the musician’s traverse is significantly larger than the right side, and the traverse is the area in the human brain that processes auditory information. Although the left side of the non-musician cross is larger than the right side, the difference is small, but the difference between musicians is twice that of non-musicians. Schlaug also found that musicians have an average cerebellum that is 5% larger than non-musicians. This shows that finger movement for many years promotes additional nerve growth [13].

The brain is a special structure developed by human beings to adapt to the needs of survival. Its main task is to collect information about the internal and external environment of the body, and to process the information specifically to make decisions and responses that are suitable for the environment and for survival [14]. Music can enhance the interrelationship between EEG signals in each channel and build a network of brain functions, which can significantly improve the activity of the brain.

4. Clinical Study of Music Therapy

Music therapy is a treatment method that enhances the physical and mental health of individuals by using music activities as a medium of treatment. “Music Therapy”, which combines music, medicine and psychology, is a study of the role of music in human function and how to apply music to treat diseases. From a physiological analysis, music therapy is the result of objective stimuli for central nervous system stimulation. When external or internal factors stimulate the hypothalamic and other subcortical centers that are responsible for emotions, it will cause changes in the activity of the emotional nervous system [9].

Stroke is a persistent cerebral hemisphere or brainstem focal neurological deficit caused by acute cerebrovascular circulatory disorder. The domestic morbidity rate is about 30% to 50% [15]. Modern medicine combines the physical and psychological healing of patients. Studies have shown that the use of music therapy in combination with drug therapy has a significant effect on the treatment of senile depression, schizophrenia and preoperative anxiety [16]. Music therapy is divided into active and passive. Passive music therapy is also known as perceptual music therapy; patients mainly listen carefully, wholeheartedly into the music, and feel the beauty of music; and active music therapy is that patients actively participate in music activities, such as singing, using musical instruments. At present, most of the music therapy uses VCD and Walkman, and most of the patients are passively listening. Music therapy for post-stroke depression has been reported more and more in China, especially for the study of national conditions and regional differences, the application of different populations and the efficacy [12] [17] [18] [19].

In the medical field, the results of music therapy in China have been fully affirmed by the academic community. The most widely used neurological disorder in domestic music therapy is the sequela of stroke. The earlier report was Liu Mingjia, the second nursing home of Qingdao Jinan Military Region, Medical Electrotherapy for the Treatment of 60 Cases of Cerebral Thrombosis [12]. Liu Yanping et al. used a combination of susceptibility music therapy and exercise therapy to treat patients with post-stroke limb paralysis. It was found that susceptibility music therapy combined with exercise therapy can improve limb paralysis and reduce muscle tone in stroke patients [3]. Jeong SH et al. showed for the first time that music listening in the early stages of a stroke could enhance cognitive recovery and prevent negative emotions. Cha, Y et al. (2014) investigate the effect of intensive gait training with rhythmic auditory stimulation on postural control and gait performance in individuals with chronic hemiparetic stroke [16].

Twenty patients with chronic hemiparetic stroke participated in this study. Subjects in the Rhythmic auditory stimulation training group (10 subjects) underwent intensive gait training with rhythmic auditory stimulation for a period of 6 weeks (30 min/day, five days/week), while those in the control group (10 subjects) underwent intensive gait training for the same duration. Two clinical measures, Berg balance scale and stroke specific quality of life scale, and a 2-demensional gait analysis system, were used as outcome measure. To provide rhythmic auditory stimulation during gait training, the MIDI Cuebase musical instrument digital interface program and a KM Player version 3.3 were utilized for this study. The results showed that intensive gait training with rhythmic auditory stimulation resulted in significant improvement in scores on the Berg balance scale, gait velocity, cadence, stride length and double support period in affected side, and stroke specific quality of life scale compared with the control group after training.

Music therapy is a planned and purposeful treatment process guided by medical psychology and using music activities as the main body. The specifications of its treatment methods, procedures, and content are still being explored and practiced. Music has a direct impact on the limbic system and brainstem structure through physical and physiological functions. Its melody can invigorate the spirit, stimulate thinking, stimulate normal behavior, improve the emergency response ability of stroke patients, and enable the patient’s original living ability to be exerted [19].

5. Conclusion

Looking back at the past research work, we strongly felt that the relationship between music and the brain has become a frontier field in the study of brain science and music psychology [9]. Undoubtedly, the influence of music on the human brain can be objectively determined by scientific means. Music training has outstanding effects on human brain development as well as cognitive and memory development. Music therapy can reduce the patient’s anxiety level, thereby improving mood and reducing the response to psychological depression. It is widely used in the modern medical field to treat diseases such as stroke depression [20]. In addition, music training also shows significant effect on memory enhancement in a clear molecular level. These studies have further deepened people’s understanding of the value of music education, and made music education show more in the broader development of human development and human potential.

6. The Limitation and Future Work

In future research, the study should incorporate more participants, and groups of participants should be sampled from different schools. This would ensure to reduce the variability of the estimates made from the data collected in the experiment. Sampling from different schools would allow us to make inferences on a wider population.

Conflicts of Interest

The author declares no conflicts of interest regarding the publication of this paper.

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  Journal of the Association of Nigerian Musicologists Journal / Journal of the Association of Nigerian Musicologists / Vol. 18 No. 1 (2024) / Articles (function() { function async_load(){ var s = document.createElement('script'); s.type = 'text/javascript'; s.async = true; var theUrl = 'https://www.journalquality.info/journalquality/ratings/2408-www-ajol-info-janm'; s.src = theUrl + ( theUrl.indexOf("?") >= 0 ? "&" : "?") + 'ref=' + encodeURIComponent(window.location.href); var embedder = document.getElementById('jpps-embedder-ajol-janm'); embedder.parentNode.insertBefore(s, embedder); } if (window.attachEvent) window.attachEvent('onload', async_load); else window.addEventListener('load', async_load, false); })();

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Influence of digital economy on vocal music performance of christian musicians in nigeria, yeside dma odiase, asomdwee walton.

 This paper focuses on the influence of digital economy on vocal performance among Christian musicians. Undoubtedly, there has been a paradigm shift in the performance, production, distribution and promotion of music due to a greater reliance on the internet associated with the experience of the COVID-19 pandemic. As such, the internet has promoted a greater patronage of the digital economy. Thus, the digital economy affords the Christian vocal performer a good opportunity to impact the world globally. Despite these prospects of the digital economy, some Christian vocal performers are oblivious about how to engage in it maximally while some of those involved have fallen into the pit of compromise and the dilution of the gospel message. How then does the Christian participate in the digital economy and make lasting impact while maintaining the integrity of their faith? With Femi Adedeji’s transformative musicology theory as a theoretical framework and a descriptive research design, the researchers highlight some trends in vocal performance and present an overview of the digital economy. They further discuss the influence of digital economy on vocal performance where the benefits and shortfalls are indicated. The way forward for the Christian musician in the midst of a digital economy is presented after which the paper comes to a conclusion. The researchers present among others, findings such as the place of authenticity as an idealistic goal in vocal performance, the trend of glossolalia in Christian vocal performance, opportunities for the Christian musician to perform music of other cultures with its accompanying versatility and opportunities of musical collaborations, and the use of vocal effects as a reinforcement in conveying the message of a song. With these in view, the researchers recommend that the Christian musicians should maximize the opportunities presented by the digital economy for global impact while being cautious not to jettison their faith in the process.

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The Influence of ESG Factors on the Firm Performance

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Highest ocean heat in four centuries places Great Barrier Reef in danger

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Mass coral bleaching on the Great Barrier Reef (GBR) in Australia between 2016 and 2024 was driven by high sea surface temperatures (SST) 1 . The likelihood of temperature-induced bleaching is a key determinant for the future threat status of the GBR 2 , but the long-term context of recent temperatures in the region is unclear. Here we show that the January–March Coral Sea heat extremes in 2024, 2017 and 2020 (in order of descending mean SST anomalies) were the warmest in 400 years, exceeding the 95th-percentile uncertainty limit of our reconstructed pre-1900 maximum. The 2016, 2004 and 2022 events were the next warmest, exceeding the 90th-percentile limit. Climate model analysis confirms that human influence on the climate system is responsible for the rapid warming in recent decades. This attribution, together with the recent ocean temperature extremes, post-1900 warming trend and observed mass coral bleaching, shows that the existential threat to the GBR ecosystem from anthropogenic climate change is now realized. Without urgent intervention, the iconic GBR is at risk of experiencing temperatures conducive to near-annual coral bleaching 3 , with negative consequences for biodiversity and ecosystems services. A continuation on the current trajectory would further threaten the ecological function 4 and outstanding universal value 5 of one of Earth’s greatest natural wonders.

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Like many coral reefs globally, the World Heritage-listed GBR in Australia is under threat 4 , 6 . Mass coral bleaching, declining calcification rates 5 , 7 , outbreaks of crown-of-thorns starfish ( Acanthaster spp.) 8 , severe tropical cyclones 9 and overfishing 10 have placed compounding detrimental pressures on the reef ecosystem. Coral bleaching typically occurs when heat stress triggers the breakdown of the symbiosis between corals and their symbiotic dinoflagellates 11 . Although coral bleaching can occur locally as a result of low salinity, cold waters or pollution, regional and global mass bleaching events, in which the majority of corals in one or more regions bleach at once, are strongly associated with increasing SST linked to global warming 2 .

The first modern observations of mass coral bleaching on the GBR occurred in the 1980s, but these events were less widespread and generally less severe 3 than the bleaching events in the twenty-first century 4 . Stress bands in coral skeletal cores have provided potential evidence for pre-1980s bleaching in the GBR and Coral Sea, such as during the 1877–78 El Niño 12 . However, stress bands are evident in relatively few cores before 1980 (ref. 12 ),  suggesting that severe mass bleaching did not occur in the 1800s and most of the 1900s.

As the oceans have warmed, however, mass coral bleaching events have become increasingly lethal to corals 4 . Coral bleaching on the GBR 1 in 1998 coincided with a strong eastern-Pacific El Niño, and in 2002 with a weak El Niño. El Niño events can induce lower cloud cover and increased solar irradiance over the GBR 13 , increasing the risk of thermal stress and mass bleaching events 14 . In 2004, water temperatures were anomalously warm, and although bleaching occurred in the Coral Sea 15 , it was not widespread in the GBR, probably because there was reduced upwelling and an associated reduced influence of nutrients on symbiotic dinoflagellate expulsion 16 .

However, in the nine January–March periods from 2016 to 2024 (inclusive) there were five mass coral bleaching events on the GBR. Each was associated with high SSTs and affected large sections of the reef. GBR mass bleaching occurred in both 2016 and 2017, influenced by the presence of an El Niño event in 2016, and led to the death of at least 50% of shallow-water (depths of 5–10 m) reef-building corals 4 . Major bleaching events occurred again in quick succession in 2020 and 2022, with the accumulated heat stress for large sections of the GBR reaching levels conducive to widespread bleaching but lower levels of coral mortality 1 . The bleaching event in 2022 occurred, unusually, during a La Niña event, which is typically associated with cooler summer SSTs, higher than average rainfall and higher cloud cover on the GBR 1 . At the time of writing, researchers are assessing the impacts of the 2024 mass bleaching event.

The frequency of recent mass coral bleaching and mortality on the GBR is cause for concern. In 2021, the World Heritage Committee of the United Nations Educational, Scientific and Cultural Organization (UNESCO) drafted 17 a decision to inscribe the GBR on the List of World Heritage in Danger, stating that the reef is “facing ascertained danger”, citing recent mass coral bleaching events and insufficient progress by the State Party (Australia) in countering climate change, improving water quality and land management issues. The committee’s adopted decisions 18 have not included inscription of the ‘in danger’ status, but the draft inscription highlights the seriousness of the recent mass coral bleaching events. Authorities in Australia 5 have noted that climate change and coral bleaching have deteriorated the integrity of the outstanding universal value of the GBR, a defining feature of its World Heritage status.

Although rapidly rising SSTs are attributed to human activities with virtual certainty 19 , understanding the multi-century SST history of the GBR is critical to understanding the influence of SST on mass coral bleaching and mortality in recent decades. Putting aside a problematic attempt to do this 20 , which was discredited 21 , 22 , knowledge of the long-term context for GBR SSTs comes primarily from two multi-century reconstructions based on the geochemistry of coral cores collected from the inner shelf 23 and outer shelf 24 (Flinders Reef) in the central GBR. These reconstructions showed that SSTs in the early 2000s were not unusually high relative to levels in the past three centuries, with five-year mean SSTs (and salinities) estimated to be higher in the 1700s than in the 1900s. However, these records were limited by their relatively coarse five-year sampling resolution and their most recent data point being from the early 2000s. After these studies were published, SSTs in the GBR have continued to rise. Updated analysis of coral data from Flinders Reef provides valuable improved temporal resolution 25 , but interpretations of these records remain limited spatially.

Here, we investigate the recent high SST events in the GBR region in the context of the past four centuries. We combine a network of 22 coral Sr/Ca and δ 18 O palaeothermometer series (Supplementary Tables 1 and 2 ) located in and near to the Coral Sea region to infer spatial mean SST anomalies (SSTAs) for January–March, the months when maximum SST and thermal bleaching are most likely to occur in the Coral Sea 16 , 26 , each year from 1618 to 1995 ( Methods and Supplementary Information ). Anthropogenic climate change began and proceeded entirely within the multi-century lives of some of these massive coral colonies, offering a continuous multi-century record covering the industrial era. We use this 1618–1995 reconstruction and the available 1900–2024 instrumental data to contextualize the modern trend and rank four centuries of January–March SSTAs with greater precision than was previously possible. We then assess the degree of human influence on ocean temperatures in the region using climate model simulations run both with and without anthropogenic forcing.

The instrumental period (1900–present)

Mass coral bleaching on the GBR in 2016, 2017, 2020, 2022 and 2024 during January–March coincided with widespread warm SSTAs in the surrounding seas 1 , including the Coral Sea (Fig. 1a–e , using ERSSTv5 data 27 ). The Coral Sea and GBR have experienced a strong warming trend since 1900 (Fig. 1f ). January–March SSTAs averaged over the GBR are strongly correlated ( ρ  = 0.84, P   ≪  0.01) with those in the broader Coral Sea (Fig. 1f ), including when the long-term warming trend is removed from both time series ( ρ  = 0.69, P  < 0.01; Supplementary Fig. 4 ). Based on the strength of this correlation, we associate high January–March area-averaged Coral Sea SSTAs with increased thermal bleaching risk in the GBR.

a – e , SSTAs (using ERSSTv5 data) for January–March in the Australasian region relative to the 1961–90 average for the five recent GBR mass coral bleaching years: 2016, 2017, 2020, 2022 and 2024. The black box shows the Coral Sea region (4° S–26° S, 142° E–174° E). f , Coral Sea and GBR mean SSTAs for 1900–2024 in January–March relative to the 1961–90 average. The black vertical lines indicate the five recent GBR mass coral bleaching years.

Record temperatures were set in 2016 and 2017 in the Coral Sea, and in 2020 they peaked fractionally below the record high of 2017. The January–March of 2022 was another warm event, the fifth warmest on record at the time. Recent data (ERSSTv5) indicate that 2024 set a new record by a margin of more than 0.19 °C above the previous record for the region. The January–March mean SSTs averaged over the five mass bleaching years during the period 2016–2024 are 0.77 °C higher than the 1961–90 January–March averages in both the Coral Sea and the GBR. The multidecadal warming trend, extreme years and association between GBR and Coral Sea SSTs are similar for the HadISST 28 gridded SST dataset, with some notable differences in the 1900–40 period (Supplementary Fig. 3 ). Furthermore, analysis of modern temperature-sensitive Sr/Ca series from GBR corals for 1900–2017 provides coherent independent evidence of statistically significant multi-decadal warming trends in January–March SSTs in the central and southern GBR (Supplementary Information section  4.2 ).

A multi-century context (1618–present)

Reconstructing Coral Sea January–March SSTs from 1618 to 1995 extends the century-long instrumental record back in time by an additional three centuries (Fig. 2a and Methods ). The reconstruction (calibrated to ERSSTv5) shows that multi-decadal SST variability was a persistent feature in the past. At the centennial timescale, there is relative stability before 1900, with the exception that cooler temperatures prevailed in the 1600s. Warming during the industrial era has been evident since the early 1900s (Fig. 2a ). There is a warming trend for January–March of 0.09 °C per decade for 1900–2024 and 0.12 °C per decade for 1960–2024 (Fig. 1f ) using ERSSTv5 data. Calibrating our reconstruction to HadISST1.1 yields similar results, with some differences in the degree of pre-1900 variability at both multi-decadal and centennial timescales (Supplementary Information section  5.2.6 ).

a , Reconstructed and observed mean January–March SSTAs in the Coral Sea for 1618–2024 relative to 1961–90. Dark blue, highest skill (maximum coefficient of efficiency) reconstruction with the full proxy network; light blue, 5th–95th-percentile reconstruction uncertainty; black, observed (ERSSTv5) data. Red crosses indicate the five recent mass bleaching events. Dashed lines indicate the best estimate (highest skill, red) and 95th-percentile (pink) uncertainty bound for the maximum pre-1900 January–March SSTA. b , Central GBR SSTA for the inner shelf 23 in thick orange and outer shelf 25 (Flinders Reef) in thin orange lines; these series are aligned here (see Methods ) with modern observations of mean GBR SSTAs for January–March relative to 1961–90. Observed data are shown at annual (grey line) and five-year (black line with open circles, plotted at the centre of each five-year period and temporally aligned with the five-year coral series 23 ) resolution. Dashed lines indicate best-estimate pre-1900 January–March maxima for refs. 23 (red) and 25 (pink). Orange shading indicates 5th–95th-percentile uncertainty bounds. Red crosses indicate the five recent mass bleaching events. c , Evaluation metrics for the Coral Sea reconstruction (Supplementary Information section  3.1 ); RE, reduction of error; CE, coefficient of efficiency; Rsq-cal, R-squared in the calibration period; Rsq-ver, R-squared in the verification (evaluation) period. d , Coral data locations relative to source data region (orange box) and Coral Sea region (red box). Coral proxy metadata are given in Supplementary Tables 1 and 2 .

Our best-estimate (highest skill; Methods ) annual-resolution Coral Sea reconstruction (Fig. 2a ), using the full coral network calibrated to the ERSSTv5 instrumental data, indicates that the January–March mean SSTAs in 2016, 2017, 2020, 2022 and 2024 were, respectively, 1.50 °C, 1.54 °C, 1.53 °C, 1.46 °C and 1.73 °C above the 1618–1899 (hereafter ‘pre-1900’) reconstructed average. Using the same best-estimate reconstruction, Coral Sea January–March SSTs during these GBR mass bleaching years were five of the six warmest years the region has experienced in the past 400 years (Fig. 2a ).

By comparing the recent warm events to the reconstruction’s uncertainty range ( Methods ), we quantify, using likelihood terminology consistent with recent reports from the Intergovernmental Panel on Climate Change 19 , that the recent heat extremes in 2017, 2020 and 2024 are ‘extremely likely’ (>95th percentile; Fig. 2a ) to be higher than any January–March in the period 1618–1899. Furthermore, the heat extremes in 2016 and 2022 are (at least) ‘very likely’ (>90th percentile) to be above the pre-1900 maximum. We perform a series of tests that verify that our findings are not simply an artefact of the nature of the coral network itself (Supplementary Information section 5.2 ). In a network perturbation test, we generate 22 subsets of the reconstruction by adding proxy records incrementally in order from the highest to the lowest correlation with the target (Supplementary Information section  5.2.5 ). We confirm that 2017, 2020 and 2024 were ‘extremely likely’ (>95th percentile) to have been warmer than any year pre-1900 (using ERSSTv5 data) for all of these proxy subsets. Furthermore, in 20 of the 22 subsets, 2016 was also ‘extremely likely’ (>95th percentile), rather than ‘very likely’, to be warmer (2022 was ‘extremely likely’ in 14 of the 22 subsets). All our additional tests, including a reconstruction with only Sr/Ca coral data (thereby omitting the possibility of any non-temperature signal in δ 18 O coral on the reconstruction), achieve high reconstruction skill and confirm the extraordinary nature of recent extreme temperatures in the multi-century context (Supplementary Information section  5.2 ). Analyses using HadISST1.1 generally show lower correlations with the coral data and reconstructions with slightly warmer regional SSTs before 1900, along with more-muted centennial and multi-decadal variability in the pre-instrumental period. Nevertheless, the HadISST1.1-calibrated reconstructions show that the recent thermal extremes are well above the best estimate (highest skill) of the pre-1900 maximum of reconstructed January–March SSTAs (Supplementary Fig. 42 ). Furthermore, lower SSTAs (in the HadISST1.1 data) relative to the previous three centuries (as in our reconstructions calibrated to HadISST1.1), coupled with the recently observed mass coral bleaching events, could indicate that long-lived corals have a greater sensitivity to warming than is currently recognized.

Reconstructed regional GBR SSTAs based on a five-year-resolution, multi-century coral δ 18 O record from the central inshore GBR 23 (Fig. 2b ) show similarly strong warming since 1900 but more multi-decadal-to-centennial variability than the Coral Sea reconstruction. Recent five-year mean January–March GBR SSTAs narrowly exceed the best estimate of the maximum pre-1900 five-year mean since the early 1600s (Fig. 2b ). The averages for the five-year periods centred on 2018 and 2022 exceed the pre-1900 maximum by 0.11 °C and 0.06 °C, respectively. Results are similar using the five-year-resolution Flinders Reef (central outer shelf) 24 record (Supplementary Fig. 24 ), although its interpretation is limited by the lack of uncertainty estimates available for that record. Our Coral Sea reconstruction incorporates an updated (annual resolution) record from Flinders Reef 25 , which indicates similar centennial trends (thin orange line in Fig. 2b ) and shows that the recent high January–March SSTA events have approached the estimated local pre-1900 maximum SSTA. Although contiguous multi-century cores from within the GBR are limited in their spatial extent, twentieth-century warming is evident in these records.

The extraordinary nature of the recent Coral Sea January–March SSTs in the context of the past 400 years is further illustrated by comparing the ranked temperature anomalies (Fig. 3 ) for the combined reconstructed and instrumental period from 1618–2024, incorporating reconstruction uncertainty ( Methods ). The mass coral bleaching years of 2016, 2017, 2020, 2022 and 2024, and the heat event of 2004, stand out as the warmest events across the whole 407-year record. The warmest three years (2024, 2017 and 2020) exceed the upper uncertainty bound (95th percentile) of the warmest reconstructed January–March in the pre-1900 period (pink (upper) dashed line in Fig. 3 ); 2016, 2004 and 2022 exceed the 90th percentile bound (red (lower) dashed line in Fig. 3 ). The warming trend is clear in the association between the ascending rank of the temperature anomalies and the year (shown as the colour of the filled circles in Fig. 3 ). Despite high interannual variability, 78 of the warmest 100 January–March periods between 1618 and 2024 occurred after 1900, and the 23 warmest all occur after 1900. The warmest 20 January–March periods all occur after 1950, coinciding with accelerated global warming.

Ranked January–March SSTAs for 1618–2024 relative to 1961–90 (coloured circles) from the best-estimate (highest skill, full coral network) reconstruction (1618–1899) and instrumental (ERSSTv5) data (1900–2024). The year is indicated by the colour of the filled circles. The 5th–95th-percentile uncertainty bounds of the pre-1900 reconstructed SSTAs are shown by small grey dots. The year labels indicate the warmest six years on record, five of which were mass coral bleaching years on the GBR. The pink (upper) dashed line indicates the 95th-percentile uncertainty bound of the maximum pre-1900 reconstructed SSTA; the red (lower) dashed line indicates the 90th-percentile limit.

Assessing anthropogenic influence

Using climate model simulations from the most recent (sixth) phase of the Coupled Model Intercomparison Project 29 (CMIP6), we assess the human influence on January–March SSTAs in the Coral Sea. The model simulations are from two experiments in the Detection and Attribution Model Intercomparison Project (DAMIP) 30 . The first set of simulations represents historical climate conditions, including both the natural and human influences on the climate system over the 1850–2014 period (‘historical’; red in Fig. 4 ). The second experiment is a counterfactual climate that spans the same period and uses the same models but includes only natural influences on the climate, omitting all human influences (‘historical-natural’; blue in Fig. 4 ). The historical experiment includes anthropogenic emissions of greenhouse gases and aerosols, stratospheric ozone changes and anthropogenic land-use changes; the historical-natural experiment does not. Variations in natural climate forcings, such as from volcanic eruptions and solar variability, are incorporated in both experiments. We include models that have a transient climate response (the global mean surface-temperature anomaly at the time of a doubling of atmospheric CO 2 concentration) in the range 1.4–2.2 °C, which is deemed ‘likely’ by the science community 31 ( Methods and Supplementary Information ).

Climate-model simulations of Coral Sea January–March SSTAs relative to the 1850–1900 average for the period 1850–2014, for models within the ‘likely’ range for their transient climate response 31 . The blue line (median) and light blue shading (5th–95th-percentile limits) are from the ‘historical-natural’ climate model simulations (no anthropogenic climate forcing); the red line and light red shading are from the ‘historical’ simulations (anthropogenic influences on the climate included) using the same set of climate models. The climate-model-derived time of emergence of anthropogenic climate change, shown by the grey and black vertical lines (1976 and 1997), is when the ratio of the climate change signal to the standard deviation of noise/variability 32 across model ensemble members first rises above 1 and 2, respectively. All models are represented equally in the model ensemble.

It is only with the incorporation of anthropogenic influences on the climate that the model simulations capture the modern-era warming of the Coral Sea January–March SSTA (Fig. 4 ). The median of the historical simulations has statistically significant warming trends of 0.05 °C, 0.10 °C and 0.15 °C per decade for the periods from 1900, 1950 and 1970 to 2014, respectively; the equivalent historical-natural trends are smaller in magnitude than ±0.01 °C per decade. To further explore the centennial-scale trends, we use a bootstrap ensemble ( Methods ) of the two sets of 165-year simulations from 1850–2014. We found that 100% of the historical bootstrap ensemble has statistically significant positive trends ( Methods ) for 1900–2014, but this value is 0% for the historical-natural ensemble. The observed (ERSSTv5) mean SSTA for 2016–2024 of 0.60 °C relative to 1961–90 is warmer than any nine-year sequence in the 7,095 simulated years in the historical-natural experiments from models with transient climate responses in the ‘likely’ range 31 .

We also use the simulations to estimate the time of emergence of the anthropogenic influence on January–March Coral Sea SSTAs above the natural background variability. The anthropogenic warming signal 32 increases from near zero in 1900 to around 0.5 standard deviations of the variability (‘noise’) in 1960. The climate change signal-to-noise ratio then increases rapidly from 1960 to 2014, exceeding 1.0 in 1976, 2.0 in 1997 and around 2.8 by 2014, the end of these simulations (Fig. 4 , Methods and Supplementary Fig. 50 ). Anthropogenic impacts on the climate are virtually certain to be the primary driver of this long-term warming in the Coral Sea.

Previously, our knowledge of the SST history of the GBR and the Coral Sea region has been highly dependent on instrumental observations, with the exception of the five-year-resolution multi-century coral Sr/Ca and U/Ca SST reconstructions from the two point locations in the central GBR 23 , 24 , an update at one of these locations 25 , seasonal resolution ‘floating’ (in time) chronologies from the GBR in the Holocene 33 , 34 and point SST estimates further back in time 35 . Thus, the context of recent warming trends in the Coral Sea and GBR and their relation to natural variability on decadal to centennial timescales is largely unknown without reconstructions such as the one we developed here.

Our coral proxy network is located mostly beyond the GBR, in the Coral Sea, and some series are located outside the Coral Sea region (Fig. 2d ). The selection of the Coral Sea as a study region allowed for a larger sample of contributing coral proxy data than exists for the GBR. However, coral bleaching on the GBR can be influenced by factors other than large-scale SST, including local oceanic and atmospheric dynamics that can modulate the occurrence and severity of thermal bleaching and mortality events 13 . Nonetheless, warming of seasonal SSTs over the larger Coral Sea region is likely to prime the background state and increase the likelihood of smaller spatio-temporal-scale heat anomalies. Furthermore, where we use only the five-year resolution series directly from the GBR to reconstruct GBR SSTAs, we draw similar conclusions about the long-term trajectory of SSTAs as for our full coral network (Fig. 2b and Supplementary Fig. 24 ). Furthermore, short modern coral series from within the GBR, analysed in this study, document a multi-decadal warming signal that is coherent with instrumental data (Supplementary Figs. 29 and 30 ). Nonetheless, additional high-resolution, multi-century, temperature-sensitive coral geochemical series from within the GBR would help unravel the local and remote ocean–atmosphere contributions to past bleaching events and reduce uncertainties.

The focus on the larger Coral Sea study region also takes advantage of the global modelling efforts of CMIP6. The large number of ensemble members available for CMIP6 means that greater climate model diversity, and therefore greater certainty in our attribution analysis, is possible compared with most single model analyses. There is also a methodological benefit in having high replication of the same experiments run with multiple climate models. However, coarse-resolution global-scale models do not accurately simulate smaller-scale processes, such as inshore currents and mesoscale eddies in the Coral Sea or the Gulf of Carpentaria, which probably affect local surface temperatures and variations in nutrient upwelling in the GBR 36 , 37 . Upwelling on the GBR is linked to the strength of the East Australian Current 16 , the southward branch of the South Pacific subtropical gyre. The CMIP-scale models we use do capture these gyre dynamics. The models show that the East Australian Current is expected to increase in strength as the climate continues to warm through this century 38 , and this may lead to more nutrient inputs that can exacerbate coral sensitivity to rising heat stress 39 , 40 . As well as focusing our model analysis on the larger Coral Sea region, we use a three-month time step. In doing so, we minimize the impact of model spatio-temporal resolution on our inferences about the role of anthropogenic greenhouse-gas emissions on the SST conditions that give rise to GBR mass bleaching.

Remaining uncertainties

We present analyses and interpretations that are as robust as possible given currently available data and methods. However, several sources of remaining uncertainty mean that future reconstructions of past Coral Sea and GBR SSTs could differ from those presented here. Although bias corrections are applied to observational SST datasets such as ERSST and HadISST, these datasets probably retain biases, especially for the period during and before 1945 (ref. 41 ), and these may not be fully accounted for in the uncertainty estimates 42 . Because our reconstructions are calibrated directly to these datasets, future observational-bias corrections are likely to improve proxy-based reconstructions.

Reconstructions of SST that use coral δ 18 O records may be susceptible to the influence of changes in the coral δ 18 O–SST relationship on time periods longer than the instrumental training period, along with non-SST changes in the δ 18 O of seawater, which can covary with salinity. As such, new coral records of temperature-sensitive trace-element ratios such as Sr/Ca, Li/Mg or U/Ca may prove influential in future efforts to distinguish between changes in past temperature and hydroclimate. Owing to the limited availability of multi-century coral data from within the GBR itself, the reconstructed low-frequency variability of GBR SSTs in recent centuries is likely to change as more temperature proxy data become available. It is also likely that new sub-annual resolution records would aid in removing potential signal damping or bias from our use of some annual-resolution records to reconstruct seasonal SSTAs.

Ecological consequences

With global warming of 0.8–1.1 °C above pre-industrial levels 19 there has been a marked increase in mass coral bleaching globally 43 . Even limiting global warming to the Paris Agreement’s ambitious 1.5 °C level would be likely to lead to the loss of 70–90% of corals that are on reefs today 44 . If all current international mitigation commitments are implemented, global mean surface temperature is still estimated to increase in the coming decades, with estimates varying between 1.9 °C (ref. 45 ) and 3.2 °C (ref. 46 ) above pre-industrial levels by the end of this century. Global warming above 2 °C would have disastrous consequences for coral ecosystems 19 , 44 and the hundreds of millions of people who currently depend on them.

Coral reefs of the future, if they can persist, are likely to have a different community structure to those in the recent past, probably one with much less diversity in coral species 4 . This is because mass bleaching events have a differential impact on different coral species. For example, fast-growing branching and tabulate corals are affected more than slower-growing massive species because they have different thermal tolerance 4 . The simplification of reef structures will have adverse impacts on the many thousands of species that rely on the complex three-dimensional structure of reefs 4 . Therefore, even with an ambitious long-term international mitigation goal, the ecological function 4 of the GBR is likely to deteriorate further 5 before it stabilizes.

Coral adaptation and acclimatization may be the only realistic prospect for the conservation of some parts of the GBR this century. However, although adaptation opportunities may be plausible to some extent 47 , they are no panacea because evolutionary changes to fundamental variables such as temperature take decades, if not centuries, to occur, especially in long-lived species such as reef-building corals 48 . There is currently no clear evidence of the real-time evolution of thermally tolerant corals 48 . Most rapid changes depend on a history of exposure to key genetic types and extremes, and there are limitations to genetic adaptation that prevent species-level adaptation to environments outside of their ecological and evolutionary history 19 . Model projections also indicate that rates of coral adaptation are too slow to keep pace with global warming 49 . In a rapidly warming world, the temperature conditions that give rise to mass coral bleaching events are likely to soon become commonplace. So, although we may see some resilience of coral to future marine heat events through acclimatization, thermal refugia are likely to be overwhelmed 50 . Global warming of more than 1.5 °C above pre-industrial levels will probably be catastrophic for coral reefs 44 .

Our new multi-century reconstruction illustrates the exceptional nature of ocean surface warming in the Coral Sea today and the resulting existential risk for the reef-building corals that are the backbone of the GBR. The reconstruction shows that SSTs were relatively cool and stable for hundreds of years, and that recent January–March ocean surface heat in the Coral Sea is unprecedented in at least the past 400 years. The coral colonies and reefs that have lived through the past several centuries, and that yielded the valuable Sr/Ca and δ 18 O data on which our reconstruction is based, are themselves under serious threat. Our analysis of climate-model simulations confirms that human influence is the driver of recent January–March Coral Sea surface warming. Together, the evidence presented in our study indicates that the GBR is in danger. Given this, it is conceivable that UNESCO may in the future reconsider its determination that the iconic GBR is not in danger. In the absence of rapid, coordinated and ambitious global action to combat climate change, we will likely be witness to the demise of one of Earth’s great natural wonders.

Instrumental observations

The Coral Sea and GBR area-averaged monthly SSTAs relative to 1961–90 for January–March are obtained from version 5 of the Extended Reconstructed Sea Surface Temperature dataset (ERSSTv5) 27 . We compare our results using ERSSTv5 with those generated using the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST1.1) 28 . We use only post-1900 instrumental SST observations here. Although gridded datasets have some coverage before 1900, ship-derived temperature data in the region for that period are too sparse to be reliable for calibrating our reconstruction (Supplementary Information section  1.2 ). The regional mean for the GBR is computed using the seven grid-cell locations used by the Australian Bureau of Meteorology (Supplementary Information section  1.1 ). We define the Coral Sea region as the ocean areas inside 4° S–26° S, 142° E–174° E.

Coral-derived temperature proxy data

We use a network of 22 published and publicly available sub-annual and annual resolution temperature-sensitive coral geochemical series (proxies; Fig. 2d , Supplementary Tables 1 and 2 , and Supplementary Fig. 5a–v ) from the western tropical Pacific in our source data region (4° N–27° S, 134° E–184° E) that cover at least the period from 1900 to 1995. Of these 22 series, 16 are δ 18 O, which are in per mil (‰) notation relative to Vienna PeeDee Belemnite (VPDB) 51 ; the remaining six are Sr/Ca series. The coral data are used as predictors in the reconstruction of January–March mean SSTAs in the Coral Sea region. We apply the inverse Rosenblatt transformation 52 , 53 to the coral data to ensure that our reconstruction predictors are normally distributed. Sub-annually resolved series are converted to the annual time step by averaging across the November–April window. This maximizes the detection of the summer peak values, allowing for some inaccuracy in sub-annual dating and the timing of coral skeleton deposition 54 , 55 . A small fraction (less than 0.8%) of missing data is infilled using the regularized expectation maximization (RegEM) algorithm 56 (Supplementary Information section  2.3 ), after which the proxy series are standardized such that each has a mean of zero and a standard deviation of one over their common 1900–1995 period.

Reconstruction method

To produce our Coral Sea reconstruction, we use nested principal component regression 57 (PCR), in which the principal components of the network of 22 coral proxies are used as regressors against the target-region January–March SSTA relative to the 1961–90 average. We perform the reconstructions separately for each nest of proxies, where a nest is a set of proxies that cover the same time period. The longest nest dates back to 1618, when at least two series are available. The nests allow for the use of all coral proxies over the full time period of their coverage. The 96-year portion of the instrumental period (1900–1995) that overlaps with the reconstruction period is used for calibration and evaluation (or equivalently, verification) against observations. We reconstruct regional SSTAs from the principal components of the coral network of δ 18 O and Sr/Ca data, rather than their local SST calibrations, to minimize the number of computational steps and to aid in representing the full reconstruction uncertainty.

Principal component analysis (PCA) is used to reduce the dimensionality of the proxy matrix, as follows. Let P ( t , r ) denote the palaeoclimate-data matrix during the time period t  = 1,..., n at an annual time step for proxy series r  = 1,..., p . PCA is undertaken on this matrix during the calibration period, P cal . We obtain the principal component coefficients matrix P coeff ( r , e ) for principal components e  = 1,..., n PC and principal component scores P score ( t , e ), which are representations of the input matrix P cal in the principal component space. P score is truncated to include n PC,use principal components to form \({P}_{{\rm{score}}}^{{\prime} }\) such that the variance of the proxy network explained by the n PC,use principal components is greater than \({\sigma }_{{\rm{expl}}}^{2}\) (which we set to 95%). Reconstruction tests in which \({\sigma }_{{\rm{expl}}}^{2}\) is varied from 70% to 95% show that our results are not strongly sensitive to this choice, and tests based on lag-one autoregressive noise for \({\sigma }_{{\rm{expl}}}^{2}\) from 50% to 99% further support this choice (Supplementary Information section  3.2 ). These principal components are used as predictors against which the Coral Sea January–March instrumental SSTAs are regressed. We regress the standardized SSTA target data during the calibration period, I cal , against the retained principal components of the predictor data, \({P}_{{\rm{score}}}^{{\prime} }\) :

Thus, we obtain n PC,use estimates of the regression coefficients γ e with gaussian error term ε t  ~  N (0, \({\sigma }_{N}^{2}\) ). The principal components are extended back into the pre-instrumental period by multiplying the entire proxy matrix P ( t , p ) with the truncated principal component coefficient matrix \({P}_{{\rm{coeff}}}^{{\prime} }\) ( t , e ) to obtain \({Q}_{{\rm{coeff}}}^{{\prime} }\) :

The reconstruction proceeds with the fitted regression coefficients γ e and extended coefficient matrix \({Q}_{{\rm{coeff}}}^{{\prime} }\) to obtain a reconstruction time series R m ( t ) for a given nest of proxy series

The standardized reconstruction R m ( t ) is then calibrated to the instrumental data such that the standard deviation and mean of the reconstruction and target during the calibration interval are equal. As well as obtaining reconstructions for each nest of available proxies, we compute stitched reconstructions S c ( t ) for each calibration period c , which include at each time step the reconstructed data for the proxy nest with maximum coefficient of efficiency 58 , 59 (Supplementary Information section  3.1 ). This procedure is performed for contiguous calibration intervals between 60 and 80 years duration between 1900 and 1995, with interval width and location increments of two years, reserving the remaining data in the overlapping period for independent evaluation, and for all proxy nests. The reconstruction error is modelled with a lag-one autoregressive process fitted to the residuals. We evaluate the capacity of our reconstruction method to achieve spurious skill from overfitting by performing a test in which we replace the coral data with synthetic noise (Supplementary Information section  3.2i ). We find that reconstructions based on synthetic noise achieve extremely low or zero skill and as more noise principal components are included in the regression, the evaluation metrics indicate declining skill. Our reconstruction and evaluation methods therefore guard against the potential for spurious skill.

Pseudo-proxy reconstructions

Our reconstruction method is further evaluated by using a pseudo-proxy modelling approach based on the Community Earth System Model (CESM) Last Millennium Experiment (LME) 60 , for which there are 13 full-forcing ensemble members covering the period 850–2005. We use the pseudo-proxy reconstructions to evaluate our reconstruction method and coral network in a fully coupled climate-model environment. We form pseudo-proxies by extracting from each LME ensemble member the SST and sea surface salinity (SSS) from the 1.5° × 1.5° grid cell located nearest to our coral data. We then apply proxy system models in the form of linear regression models, basing δ 18 O on both SST and SSS, and Sr/Ca on SST only (Supplementary Information section  3.3 ). We set the spatial and temporal availability of the pseudo-coral network to match that of the coral network. We then apply our PCR reconstruction and evaluation procedure to the pseudo-proxy network, taking advantage of the availability of the modelled Coral Sea SSTA data across the multi-century period of 1618–2005, which allows for the evaluation of the pseudo-proxy reconstruction over this entire time period. We first test our method using a ‘perfect proxy’ approach (with no proxy measurement error) before superimposing synthetic noise on the pseudo-proxy time series, evaluating our methodology at two separate levels of measurement error, quantified by signal-to-noise ratios of 1.0 and 4.0. The evaluation metrics for these tests indicate that our coral network and reconstruction method obtain skilful reconstructions of Coral Sea SSTAs in the climate-model environment (Supplementary Figs. 17b , 18 , 20b , 21 , 22b and 23 ).

Comparison with independent coral datasets

We use two multi-century five-year-resolution coral series from the central GBR 23 , 24 (Fig. 2b and Supplementary Fig. 24 ) and a network of sub-annual and annual resolution modern coral series (dated from 1900 onwards but not covering the full 1900–1995 period) from 44 sites in the GBR (Supplementary Information section  4.2 ) for independent evaluation of coral-derived evidence for warming in the region. We estimate five-year GBR SSTAs (Fig. 2b ) by aligning the post-1900 mean and variance of the proxy and instrumental (ERSSTv5) data.

Reconstruction sensitivity to non-SST influences

Of the 22 available coral series, 16 are records of δ 18 O, a widely used measure of the ratio of the stable isotopes 18 O and 16 O. In the tropical Pacific Ocean, δ 18 O is significantly correlated with SST 61 , 62 , 63 , 64 . Coral δ 18 O is also sensitive to the δ 18 O of seawater 65 , which can reflect advection of different water masses and/or changes in freshwater input, such as from riverine sources or precipitation, which in turn co-vary with SSS. Thus, it is generally considered that the main non-SST contributions to coral δ 18 O are processes that co-vary with SSS 62 , 66 . Our methodology minimizes the influence of non-temperature impacts on the reconstruction by exploiting the contrast in spatial heterogeneity between SST and SSS in January–March (Supplementary Information section  5.1 ). SSS is spatially inhomogeneous in the tropical Pacific 66 , 67 , leading to low coherence in SSS signals across our coral network. By contrast, the strong and coherent SST signal across our coral network locations and the Coral Sea region leads to principal components that are strongly representative of SST variations. This produces a skilful reconstruction of SST, as determined by evaluation against independent observations, and low correlations with SSS across the Coral Sea region (Supplementary Fig. 31 ).

Although the likelihood of non-SST influences on our SST reconstruction is low, we nonetheless test the sensitivity of our reconstruction and its associated interpretations to the possibility of these influences on the coral data. The tests compute the correlations between our best-estimate SSTA reconstruction (highest coefficient of efficiency) and observations of SSS, along with a series of additional reconstructions based on subsets of our coral network. The correlations between our highest coefficient of efficiency January–March Coral Sea SSTA reconstruction and January–March SSS are mapped for the Coral Sea and its neighbouring domain using three instrumental SSS datasets (Supplementary Fig. 31 ). Correlations are not statistically significant over most of the domain. Noting differing spatial correlation patterns between the instrumental SSS datasets 68 , which also cover different time periods (Supplementary Information section  5.1 ), we undertake six sensitivity tests using subsets of the coral network (Supplementary Information section  5.2 ). We use the following combinations of coral series: (1) the full network of 22 δ 18 O and Sr/Ca series (Figs. 2a and 3 ); (2) a subset of the six available Sr/Ca series (Supplementary Figs. 32 – 33 ), to test how the reconstruction is influenced by the inclusion of coral δ 18 O records; (3) a fixed nest subset of the five longest coral series, extending back to at least 1700 (Supplementary Figs. 34 – 35 ), to test for the potential influence of combining series of differing lengths (from our splicing of portions of the best reconstructions from each nest); (4) a subset of the ten coral series that are most strongly correlated with the target (Supplementary Figs. 36 and 37 ), to test how our reconstruction is influenced by the inclusion of coral series that are less strongly correlated with our target; (5) a subset of coral series that excludes the six records that are reported to potentially include biological mediation or non-climatic effects, or have low correlation with the target (Supplementary Figs. 38 and 39 ), to test their influence on the reconstruction; and (6) a network perturbation test comprising 22 separate subsets of proxies, in which proxy records are added incrementally in order of highest to lowest correlation with the target, starting with a single coral series and increasing the number of included proxies to all 22 series in our network (Supplementary Information section  5.2.5 ), to systematically quantify the influence of gradually including more coral datasets on our reconstruction and its interpretations.

The evaluation metrics (Fig. 2c and Supplementary Figs. 32b , 34b , 36b and 38b ) indicate a skilful reconstruction back to 1618 for the reconstructions based on the Full, Sr/Ca only, Long, Best-10 and OmitBioMed networks. These reconstructions explain 82.7%, 80.6%, 77.6%, 79.8% and 80.4% (R-squared values) of the variance in January–March SSTAs, respectively, in the independent evaluation periods (using ERSSTv5b). All coral subsets in the network perturbation test produce skilful reconstructions (Supplementary Fig. 40 ). The highest-skill reconstructions for all subsets in the network perturbation test align with our key interpretations (Supplementary Figs. 41 and 42 ). Together, our sensitivity tests show that the coral network, observational data and reconstruction methodology are a sound basis for reconstructing Coral Sea January–March SSTAs in past centuries and contextualizing recent high-SST events ( Supplementary Information ).

Climate-model attribution ensembles and experiments

The multi-model attribution analysis used here is based on simulations from CMIP6. We analyse simulations from the historical experiment (including natural and anthropogenic influences for 1850–2014) and the historical-natural experiment (natural-only forcings for 1850–2014). We select climate models for which monthly surface temperature is available in at least three historical and historical-natural simulations (Supplementary Table 5 ). All model simulations are interpolated to a common regular 1.5° × 1.5° latitude–longitude grid. January–March SSTAs relative to 1961–90 are calculated for each simulation. The full historical all-forcings ensemble is composed of 14 models with 268 simulations for 1850–2014. The natural-only ensemble is composed of the same 14 models with 95 individual simulations. A subset of climate models in the CMIP6 ensemble are considered by the science community to be ‘too hot’, simulating warming in response to increased atmospheric carbon dioxide concentrations that is larger than that supported by independent evidence 31 . We omit these models from our analysis by including only models with a transient climate response in the ‘likely’ range 31 of 1.4–2.2 °C. Our results are not strongly sensitive to this selection (Supplementary Information section  6.3 ). The ten remaining models yield a total of 25,410 years from 154 historical ensemble members and 7,095 years from 43 historical-natural ensemble members. We weight the models equally in our analysis using bootstrap sampling. We report linear trends based on simple linear regression models fitted with ordinary least squares. The statistical significance of linear trends is assessed using the Spearman’s rank correlation test 69 .

Time of emergence of the anthropogenic impact

We assess the anthropogenic influence on SSTAs in the Coral Sea region by starting with the assumption that any anthropogenic influence on SSTAs in the Coral Sea is indistinguishable from natural variability at the commencement of the model experiments. We measure the impact of anthropogenic influence on the climate in the region using a signal-to-noise approach 32 , 70 . We calculate the anthropogenic ‘signal’ as the mean of the difference between the smoothed (using a 41-year Lowess filter) modelled historical Coral Sea SSTA and the mean smoothed modelled historical-natural SSTA. Our ‘noise’ is the standard deviation of the difference between the modelled historical SSTA and its smoothed time series (Supplementary Information section  6 ).

Methods additionally rely on Supplementary Information and refs. 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 .

Data availability

The ERSSTv5 instrumental SST data are available from the US National Oceanic and Atmospheric Administration at https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html . The HadISST1.1 data are available from the UK Met Office at https://www.metoffice.gov.uk/hadobs/hadisst/ . The original coral palaeoclimate data are available at the links provided in Supplementary Table 2 . Land areas for maps are obtained from the Mapping Toolbox v.23.2 in Matlab v.2023b and the Global Self-consistent, Hierarchical, High-resolution Geography (GSHHS) Database at https://www.soest.hawaii.edu/pwessel/gshhg/ through the m_map toolbox by R. Pawlowicz, available at https://www.eoas.ubc.ca/%7Erich/map.html . Prepared data from the coral geochemical series, reconstructions and climate models that support the findings of this study are available at: https://doi.org/10.24433/CO.4883292.v1 .

Code availability

The code that supports the findings of this study is available and can be run at : https://doi.org/10.24433/CO.4883292.v1 .

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Acknowledgements

We acknowledge the originators of the coral data cited in Supplementary Tables 1 and 2 ; S. E. Perkins-Kirkpatrick and the deceased G. J. van Oldenborgh 105 for contributions to an earlier version of this manuscript; E. P. Dassié and J. Zinke for discussions and data; R. Neukom for advice on an earlier version of the reconstruction code; and B. Trewin and K. Braganza for advice about the Bureau of Meteorology GBR SST time series. B.J.H. and H.V.M. acknowledge support from an Australian Research Council (ARC) SRIEAS grant, Securing Antarctica’s Environmental Future (SR200100005), and ARC Discovery Project DP200100206. A.D.K. acknowledges support from an ARC DECRA (DE180100638) and the Australian government’s National Environmental Science Program. B.J.H. and A.D.K. acknowledge an affiliation with the ARC Centre of Excellence for Climate Extremes (CE170100023). H.V.M. acknowledges support from an ARC Future Fellowship (FT140100286). A.K.A. acknowledges support from an Australian government research training program scholarship and an AINSE postgraduate research award. Funding was provided to B.K.L. by the Vetlesen Foundation through a gift to the Lamont-Doherty Earth Observatory. Grants to B.K.L. enabled the generation of coral oxygen isotope and Sr/Ca data from Fiji that were used in our reconstruction (US National Science Foundation OCE-0318296 and ATM-9901649 and US National Oceanic and Atmospheric Administration NA96GP0406). We acknowledge the support of the NCI facility in Australia and the World Climate Research Programme’s working group on coupled modelling, which is responsible for CMIP. We thank the climate-modelling groups for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provided coordinating support and led the development of software infrastructure in partnership with the Global Organisation for Earth System Science Portals.

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Benjamin J. Henley, Helen V. McGregor & Ariella K. Arzey

Securing Antarctica’s Environmental Future, University of Wollongong, Wollongong, New South Wales, Australia

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Benjamin J. Henley

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Andrew D. King & David J. Karoly

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Andrew D. King

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Ove Hoegh-Guldberg

Australian Institute of Marine Science, Townsville, Queensland, Australia

Janice M. Lough

ARC Centre of Excellence for Coral Reef Studies and School of Earth Sciences, University of Western Australia, Crawley, Western Australia, Australia

Thomas M. DeCarlo

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Contributions

B.J.H., H.V.M. and A.D.K. conceived the study and developed the methodology. B.J.H. did most of the analysis. A.K.A. contributed analysis of modern coral data (Supplementary Information section  4.2 ). T.M.D. contributed analysis of instrumental data coverage (Supplementary Information section  1.2 ). B.K.L. contributed sub-annual coral data. B.J.H. and H.V.M. led the preparation of the manuscript, with contributions from A.D.K., O.H.-G., A.K.A., D.J.K., J.M.L., T.M.D. and B.K.L. Generative artificial intelligence was not used in any aspect of this study or manuscript.

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Henley, B.J., McGregor, H.V., King, A.D. et al. Highest ocean heat in four centuries places Great Barrier Reef in danger. Nature 632 , 320–326 (2024). https://doi.org/10.1038/s41586-024-07672-x

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Study on the attack of concrete by external sulfate under electric fields.

1. Introduction

2. materials and methods, 2.1. experimental raw materials, 2.1.1. cement, 2.1.2. coarse aggregate, 2.1.3. fine aggregate, 2.1.4. chemical reagents, 2.1.5. concrete mix proportion, 2.2. experimental methods, 2.2.1. experimental equipment, 2.2.2. experimental procedures, 2.2.3. specimen molding, 2.2.4. evaluation criteria, 2.2.5. scanning electron microscopy (sem) test, 3.1. surface characteristics, 3.2. mass loss, 3.3. analysis of experimental results on sulfate attack on concrete under electric field, 4. discussion, 4.1. experimental results analysis, 4.1.1. influence of water–cement ratio on the experiment, 4.1.2. impact of the frequency of electric field on the experiment, 4.1.3. impact of age on the experiment, 4.1.4. impact of different immersion methods, 4.2. microscopic analysis of ordinary concrete specimens, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Liu, H.; Shi, N.; Han, K.; Fu, X.; Fang, Y. Study on the Attack of Concrete by External Sulfate under Electric Fields. Coatings 2024 , 14 , 1008. https://doi.org/10.3390/coatings14081008

Liu H, Shi N, Han K, Fu X, Fang Y. Study on the Attack of Concrete by External Sulfate under Electric Fields. Coatings . 2024; 14(8):1008. https://doi.org/10.3390/coatings14081008

Liu, Huanqin, Nuoqi Shi, Kaizhao Han, Xu Fu, and Yuexin Fang. 2024. "Study on the Attack of Concrete by External Sulfate under Electric Fields" Coatings 14, no. 8: 1008. https://doi.org/10.3390/coatings14081008

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Music-Evoked Emotions—Current Studies

Hans-eckhardt schaefer.

1 Tübingen University, Institute of Musicology, Tübingen, Germany

2 Institute of Functional Matter and Quantum Technology, Stuttgart University, Stuttgart, Germany

Associated Data

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

Introduction

Basic discussions of music center about questions such as: What actually is music? How can we understand music? What is the effect of music on human beings? Music is described as multidimensional and researchers have categorized it by its arousal properties (relaxing/calming vs. stimulating), emotional quality (happy, sad, peaceful), and structural features (as, e.g., tempo, tonality, pitch range, timbre, rhythmic structure) (Chanda and Levitin, 2013 ). One can ask the question how to recognize and describe the concretely beautiful in music. Efforts have been undertaken to answer this question (Eggebrecht, 1991 ), e.g., by discussing the beauty of the opening theme of the second movement of Mozart's piano concerto in d minor (KV 466). In this formal attempt to transform music into a descriptive language, particular sequences of tones and rhythmical structures have been tentatively ascribed to notions such as “flattering” or “steady-firm” (Eggebrecht, 1991 ). From the viewpoint of a composer, Mozart himself obviously was aware of the attractiveness of this beauty-component in music, stating that his compositions should be “…angenehm für die Ohren…” of the audience “…natürlich ohne in das Leere zu fallen…” (…pleasing for the ear… (of the audience) …naturally without falling into the shallow…) (see Eggebrecht, 1991 ). In modern and contemporary music, however, formal attempts of understanding are useless because form and self-containedness are missing (Zender, 2014 ). Thus, in atonality and in the emancipation of noise, a tonal center is absent, by simultaneous appearance of different rhythmic sequences the regular meter is demolished, and in aleatory music the linear order of musical events is left open.

A few earlier comments on the understanding of the interplay between music and man may be quoted here: “…there is little to be gained by investigation of emotion in music when we have little idea about the true fundamental qualities of emotion” (Meyer, 1956 ). “…music is so individual that attempts to provide a systematic explanation of the interaction might well be ultimately fruitless—there may be no systematic explanation of what happens when individuals interact with music” (Waterman, 1996 ). “Die Qualitäten und die Inhalte ihrer (der Komponisten) Musik zu beschreiben ist unmöglich. Eben deshalb werden sie in Klang gefasst, weil sie sonst nicht erfahrbar sind” (To describe the qualities and content of their (of the composers) music is impossible. Exactly for this reason they are expressed in musical sound, otherwise they are not communicable) (Maurer, 2014 ). Some historical comments on music-evoked emotions are compiled in section Historical Comments on the Impact of Music on People of this study.

The advent of brain-imaging technology with high spatial resolution (see principles section Experimental Procedures for Tomographic Imaging of Emotion in the Brain) gave new impact to interdisciplinary experimental research in the field of music-evoked emotions from the physiological and molecular point of view. With the broader availability of magnetic resonance imaging (MRI, first demonstrated in 1973; Lauterbur, 1973 ) and positron emission tomography (PET, first demonstrated 1975; Ter-Pogossian, 1975 ) since about two decades for studying both music listeners and performing musicians, a wealth of music-evoked brain activation data has been accomplished which is discussed in section Experimental Results of Functional (tomographic) Brain Imaging (fMRI, PET) together with psychoendocrinological and molecular markers. Due to the refinement of the more phenomenological measuring techniques, such as electroencephalography (EEG) and magnetoencephalography [MEG, section Electro- and Magnetoencephalography (EEG, MEG)], skin conductance response and finger temperature measurements (section Skin Conductance Response (SCR) and Finger Temperature) as well as goose bump development (section Goose Bumps—Piloerection), emotions can be measured with high temporal resolution. Genetic studies of musical heredity are reported in section Is There a Biological Background for the Attractiveness of Music?—Genomic Studies and recent theoretical approaches of musical emotions in section Towards a Theory of Musical Emotions. Some therapeutic issues of music are discussed in section Musical Therapy for Psychiatric or Neurologic Impairments and Deficiencies in Music Perception prior to the remarks concluding this study with an outlook. A brief outline of the psychological discussion of music-evoked emotion is given in the online Supplementary Material section.

Historical comments on the impact of music on people

The effects of music on man have been considered phenomenologically from antiquity to the nineteenth century mainly from the medical point of view according to Kümmel ( 1977 ) which will be preferentially referred to in the brief historical comments of the present section.

The only biblical example of a healing power of music refers to King Saul (~1,000 BC) who was tormented by an evil spirit and relief came to him when David played the lyre (1. Sam. 16, 14-23). In Antiquity, Pythagoras (~570-507 BC) was said to substantially affect the souls of people by diatonic, chromatic, or enharmonic tunes (see Kümmel, 1977 ). Platon (428-348 BC) in his Timaios suggested for the structure of the soul the same proportions of the musical intervals which are characteristic for the trajectories of the celestial bodies (see Kümmel, 1977 ). This concept of a numeral order of music and its effect on man was transferred to the Middle Ages, e.g., by Boethius (480-525). The Greek physician Asklepiades (124-60 BC) was said to have used music as a remedy for mental illness where the application of the Phrygian mode was considered to be particularly adequate for brightening up depressive patients. Boethius emphasized that music has to be correlated to the category of “moralitas” because of its strong effect on individuals. In his treatise De institutione musica he stated that “…music is so naturally united with us that we cannot be free from it even if we so desired….” Since the ninth century, music took a strong position in the medicine of the Arabic world and the musician was an assisting professional of the physician. According to Arabic physicians, music for therapeutic purposes should be “pleasant,” “dulcet,” “mild,” “lovely,” “charming,” and in the course of the assimilation of the Arabic medicine, the Latin West took over the medical application of music. Johannes Tinctoris (1435-1511) listed 20 effects of music, such as, e.g., that music banishes unhappiness, contributes to a cheerful mood, and cures diseases. In addition, music was supposed to delay aging processes. Agrippa von Nettesheim (1486-1535) was convinced that music can maintain physical health and emboss a moral behavior. He discusses in his treatise De occulta philosophia (Agrippa von Nettesheim, 1992 ) the powerful and prodigious effects of music. From his list of 20 different musical effects—adapted to the sequence of effects established by Johannes Tinctoris (1435-1511) (Schipperges, 2003 ) a brief selection should be presented here:

• (1) Musica Deum delectat
• (7) Musica tristitiam repellit
• (13) Musica homines laetificat
• (14) Musica aegrotos sanat
• (17) Musica amorem allicit etc.

These effects could be translated into nowadays notions as religiosity (1), depression (7), joy (13), therapy (14), and sexuality (17).

Agrippa points out the alluring effects of music on unreasoning beasts: “…ipsas quoque bestias, serpentes, volucres, delphines, ad auditum suae modulationis provocat…magna vis est musica” (It stirs the very beasts, even serpents, birds and dolphins, to want to hear its melody…great is the power of music).

The physician of Arnstadt, Johann Wittich (1537-1598) summarized the requirement for good health concisely: “Das Hertz zu erfrewen/und allen Unmuht zu wenden/haben sonderliche große Krafft diese fünff Stück (To rejoice the heart/ and reverse all discontent/five things have particularly great power):

• Gottes Wort (The word of God).
• Ein gutes Gewissen (A clear conscience).
• Die Musica (Music).
• Ein guter Wein (good wine).
• Ein vernünftig Weib (A sensible wife).”

René Descartes (1596-1650) formulated a fairly detailed view of the effects of music: The same music which stimulates some people to dancing may move others to tears. This exclusively depends on the thoughts which are aroused in our memory. In the medical encyclopedia of Bartolomeo Castelli of 1682 it is stated that music is efficient for both the curing of diseases and for maintaining health. A famous historical example for a positive impact of music on mental disorders is the Spanish King Philipp V (1683-1746) who—due to his severe depressions—stopped signing official documents and got up from his bed only briefly and only by night. In 1737, his wife Elisabeth Farnese (1692-1766, by the way a descendant of Pope Paul III and Emperor Karl V) appointed the famous Italian castrato singer Carlo Broschi Farinelli (1705-1782) to Madrid. Over 10 years, Farinelli performed every night (in total 3,600 times) four arias in order to banish the black melancholia from the kings mind until the king himself “…die Musik lernet…” (…learns music…) (see Kümmel, 1977 ). With his singing, Farinelli succeeded in agitating the king to partial fulfillment of his governmental duties and an occasional appearance in the governmental council. The king's favorite aria was Quell' usignolo with a difficult coloratura part (see Figure ​ Figure1) 1 ) of Geminiano Giacomelli's (1692-1740) opera Merope (1734).

Extract from the aria Quell' usignolo of Geminiano Giacomelli's (1692-1740) opera Merope (1734) sung by Carlo Broschi Farinelli (1705-1782) for Philipp V (1683-1746), king of Spain (Haböck, 1923 ). Reprinted with permission from Haböck ( 1923 ) © 1923 Universal Edition.

The widely known Goldberg Variationen composed by J. S. Bach in 1740 may be considered, as reported by Bach biographer J. N. Forkel (1749-1818), as therapeutic music. H. C. von Keyserlingk, a Russian diplomat, asked Bach for “…einige Clavierstücke für seinen Adlatus Johann Gottlieb Goldberg,…die so sanften und etwas munteren Charakters wären, daß er dadurch in seinen schlaflosen Nächten ein wenig aufgeheitert werden könnte…” (… a number of clavier pieces for his personal assistant J. G. Goldberg…which should be of such gentle and happy character that he be somewhat cheered in his sleepless nights…). Bach chose a variations composition because of the unchanged basic harmony, although he initially had regarded a piece of this technique as a thankless task (see Kümmel, 1977 ).

In 1745 the medicine professor E. A. Nicolai (1722-1802) of Jena University started to report on more physical observations: “… wenn man Musik höre richten sich die Haare …in die Höhe, das Blut bewegt sich von aussen nach innen, die äusseren Teile fangen an kalt zu werden, das Herz klopft geschwinder und man hohlt etwas langsamer und tiefer Athem” (…when one hears music the hair stands on end (see section Goose Bumps—Piloerection), the blood is withdrawn from the surface, the outer parts begin to cool, the heart beats faster, and one breathes somewhat slower and more deeply). The French Encyclopédie of 1765 listed the diseases for which music was to be employed therapeutically: Pathological anxieties, the bluster of mental patients, gout pain, melancholia, epilepsy, fever, and plague. The physician and composer F. A. Weber (1753-1806) of Heilbronn, Germany assessed in 1802 the health effects of music more reluctantly: “Nur in Übeln aus der Klasse der Nervenkrankheiten läßt sich von…der Musik etwas Gedeihliches erhoffen. Vollständige Impotenz ist durch Musik nicht heilbar…Allein als Erwärmungsmittel erkaltender ehelicher Zärtlichkeit mag Musik vieles leisten” (Only in afflictions of the class of nervous diseases can …something profitable be expected from music. Complete impotence is not curable by music. …But as a means of rekindling marital tenderness music may achieve considerable results). The French psychiatrist J. E. D. Esquirol (1772-1840, see Charland, 2010 ) started to perform numerous experiments with the application of music to single patients or to groups. He, however, stated that the effect of music was transient and disappeared when the music ended. This change of thinking is also visible in the essay by Eduard Hanslick (1825-1904) Vom musikalisch Schönen (1854): “Die körperliche Wirkung der Musik ist weder an sich so stark, noch so sicher, noch von psychischen und ästhetischen Voraussetzungen so unabhängig, noch endlich so willkürlich behandelbar, dass sie als wirkliches Heilmittel in Betracht kommen könnte” (The physical effect of music is as such neither sufficiently strong, consistent, free from psychic and aesthetic preconditions nor freely usable as to allow its use as a real medical treatment).

With the rise of the experimental techniques of natural sciences in the medicine of the late nineteenth century, the views, patterns, and notions as determined by musical harmony began to take a backseat. It should be mentioned here that skepticism with regard to the effects of music arose in early times. In the third century Quintus Serenus declared the banishing of fever by means of vocals as pure superstition. In 1650 Athanasius Kircher wrote: “Denn dass durch (die Musik) ein Schwindsüchtiger, ein Epileptiker oder ein Gicht-Fall…geheilt werden können, halte ich für unmöglich.” (For I hold it for impossible that a consumptive, an epileptic or a gout sufferer …could be cured by music).

The mechanisms of hearing

Sound waves are detected by the ear and converted into neural signals which are sent to the brain. The ear has three divisions: The external, the middle, and the inner ear (see Figure ​ Figure2A). 2A ). The sound waves vibrate the ear drum which is connected to the ear bones (malleus, incus, and stapes) in the middle ear that mechanically carry the sound waves to the frequency-sensitive cochlea (35 mm in length, Figure ​ Figure2B) 2B ) with the basilar membrane in the inner ear. Here, making use of the cochlear hair cells (organ of Corti), the sound waves are converted into neural signals which are passed to the brain via the auditory nerve (Zenner, 1994 ). For each frequency, there is a region of maximum stimulation, or resonance region, on the basilar membrane. The spatial position x along the basilar membrane of the responding hair cells and the associated neurons determine the primary sensation of the pitch. A change in frequency of a pure tone causes a shift of the position of the activated region. This shift is then interpreted as a change in pitch (see Roederer, 2008 ) effect and laser studies allowed for a precise measurement of the movement of the basilar membrane (see Roederer, 2008 ).

Anatomy of the ear. Reprinted with permission from William E. Brownell © 2016. (B) Components of the inner ear. Reprinted with permission from © 2016 Encyclopedia Britannica. (C) Confocal micrographs of rat auditory hair cells. Scale bar: 1 μm. The protein myosin XVa is localized to the stereocilia tips (Rzadzinska et al., 2004 ). Reprinted with permission from Rzadzinska et al. ( 2004 ) © 2016 Bechara Kachar.

The cochlear hair cells assist in relaying sound to the brain. The about 20,000 hair cells in the human ear are covered by stereocilia (see Figure ​ Figure2C), 2C ), giving them a hairy look. The stereocilia of the hair cell, which is sitting on the basilar membrane, are the primary structures used in sound transduction. With acoustic stimulation, the stereocilia bend which causes a signal that goes to the auditory nerve (see Figure ​ Figure2A) 2A ) and eventually to the auditory cortex allowing sound to be processed by the brain.

At loudest sound the bending amplitude of the stereocilia is about their diameter of 200 nm (a nanometer nm is a millionth of a mm) and at auditory threshold the movement is about 1 nm or, in the order of the diameter of small molecules (Fettiplace and Hackney, 2006 ), i.e., close to the thermal equilibrium fluctuations of the Brownian motion in the surrounding lymphatic liquid (Roederer, 2008 ).

The bending of the stereocilia initiates an uptake of potassium ions (K + ) which in turn opens voltage-dependent calcium ion (Ca + ) channels. This causes neurotransmitter release at the basal end of the hair cell, eliciting an action potential in the dendrites of the auditory nerve (Gray, 0000 ).

The action speed of the hair cells is incredibly high to satisfy the amazing demands for speed in the auditory system. Signal detection and amplification must be preferentially handled by processes occurring within one hair cell. The acoustic apparatus cannot afford the “leisurely pace” of the nervous system that works on a time scale of several milliseconds or more.

Specific experimental techniques for studying musical emotion and discussion of the results

Emotionally relevant musical stimuli.

Emotional relevance of music is ascribed, e.g., to enharmonic interchange, starting of a singing voice, the climax of a crescendo, a downward quint, or in general a musically unexpected material (Spitzer, 2003, 2014 ). Four musical parameters for the activation of emotions appear to be particularly prominent in the literature (Kreutz et al., 2012 ): musical tempo, consonance, timbre, and loudness. Musical tempo could influence cardiovascular dynamics. The category of consonance could be associated with activation in the paralimbic and cortical brain areas (Blood and Zatorre, 2001 ) whereas dissonances containing partials with non-integer (irrational) frequency ratios may give rise to a sensation of roughness. The loudness or the physical sound pressure seems to be of relevance to psychoneuroendocrinological responses to music. Thus, crescendo leads to specific modulation of cardiovascular activity (see Kreutz et al., 2012 ), such as musical expectancy and tension (Koelsch, 2014 ). Musical sounds are often structured in time, space, and intensity. Several structural factors in music give rise to musical tension: consonance or dissonance, loudness, pitch, and timber can modulate tension. Sensory consonance and dissonance are already represented in the brainstem (Tramo et al., 2001 ) and modulate activity in the amygdala.

The stability of a musical structure also contributes to tension, such as a stable beat or its perturbation (for example, by an accelerando or a ritardando, syncopations, off-beat phrasings, etc.) (Koelsch, 2014 ). The stability of a tonal structure in tonal music also contributes to tension. Moving away from the tonal center creates tension and returning to it evokes relaxation. Figure ​ Figure3 3 illustrates how the entropy of the frequency of the occurrence of tones and chords determines the stability of a tonal structure and thus the ease, or the difficulty, of establishing a tonal center. Additionally, the extent of a structural context contributes to tension. Figure ​ Figure3 3 shows the probabilities of certain chords following other chords in Bach chorales. The red bars indicate that after a dominant the next chord is most likely to be a tonic. The uncertainty of the predictions for the next chord (and thus the entropy of the probability distribution for the next chord) is low during the dominant, intermediate during the tonic, and relatively high during the submediant. Progressive tones and harmonies thus create an entropic flux that gives rise to constantly changing (un)certainties of predictions. The increasing complexity of regulations, and thus the increase of entropic flux, requires an increasing amount of knowledge about the musical regularities to make precise predictions about upcoming events. Tensions emerge from the suspense about whether a prediction proves true (Koelsch, 2014 ). Tensions and release may be important for a religious chorale as metaphors for sin and redemption (Koelsch, 2014 ).

This graph shows the context-dependent bigram probabilities for the corpus of Bach chorales. Blue bars show probabilities of chord functions following the tonic (I), green bars following the submediant (vi), and red bars following a dominant (V). The probability for, e.g., a tonic (I) following a dominant (V) is high, the entropy is low (Koelsch, 2014 ). Reprinted with permission from Koelsch ( 2014 ) © 2014 Nature Publishing Group.

Tension can be further modulated by a structural breach. The emotional effects of the violations of predictions, which can be treated in analogy to the free energy of a system (Friston and Friston, 2013 ) includes surprise. Irregular unexpected chord functions, with rating of felt tensions, evoke skin conductance responses, activity changes in the amygdala and the orbitofrontal cortex while listening to a piece of classical piano music (see Koelsch, 2014 ).

Anticipatory processes can also be evoked by structural cues, for example by a dominant in a Bach chorale with a high probability being followed by a tonic (see Figure ​ Figure3), 3 ), or a dominant seventh chord which has a high probability for being followed by a tonic, thus evoking the anticipation of release. Such anticipation of relaxation might envolve dopaminergic activity in the dorsal striatum (Koelsch, 2014 ).

Another effect arising from music is emotional contagion. Music can trigger psychological processes that reflect emotion: “happy” music triggers the zygomatic muscle for smiling, together with an increase in skin conductance and breathing rate, whereas “sad” music activates the corrugator muscle. Interestingly, there seems to be an acoustic similarity between expression of emotion in Western music and affective prosody (see Koelsch, 2014 ).

Experimental procedures for tomographic imaging of emotion in the brain

Magnetic resonance imaging (mri) and functional magnetic resonance imaging (fmri).

Magnetic resonance imaging (see Reiser et al., 2008 ) can show anatomy and in some cases function (fMRI). Studies on the molecular level have been reported recently (Xue et al., 2013 ; Liu et al., 2014 ). In a magnetic resonance scanner (Figure ​ (Figure4A) 4A ) the magnetic moments of the hydrogen nuclei (protons) are aligned (Figure ​ (Figure4A) 4A ) by a strong external magnetic field (usually 1.5 Tesla) that is generated in a superconducting coil cooled by liquid helium. Magnetic resonance of the proton magnetic moments—a quantum mechanical phenomenon—can be initiated by exciting the proton spin system to precession resonance (Figure ​ (Figure4A) 4A ) by means of radio-frequency (RF) pulses of some milliseconds duration. This gives rise to a voltage signal with the resonance frequency ω 0 (Larmor frequency) which decays with the relaxation times T1 (longitudinal or spin-lattice relaxation time) and T2 (transversal or spin-spin relaxation time) which are characteristic for different chemical surroundings (see Figure ​ Figure4B 4B ).

(A) Principles of magnetic resonance tomography (Birbaumer and Schmidt, 2010 ). (a) The patient is moved into the center of the MRI scanner. (b) A strong homogeneous magnetic field aligns the magnetic moments of the protons in in the patient's body. (c) An RF-pulse excites the proton magnetic moments to precession which gives rise to an alternating voltage signal in the detector. (d) After the switching-off the RF-pulse the proton magnetic moments relax to the initial orientation. The relaxation times (see B ) are measured. Reprinted with permission from Birbaumer and Schmidt ( 2010 ) © 2010 Springer. (B) Nuclear magnetic relaxation times T1 (top) and T2 (bottom) of hydrogen nuclei for various biological materials (Schnier and Mehlhorn, 2013 ). Reprinted with permission from Schnier and Mehlhorn ( 2013 ) © 2013 Phywe Systeme. (C) Spatial encoding of the local magnetic resonance information (Birbaumer and Schmidt, 2010 ). Due to a slicing (left) and finally a three-dimensional structuring (right) by means of gradient fields, the resonance frequency and the relaxation times can be assigned to a particular pixel. Reprinted with permission from Birbaumer and Schmidt ( 2010 ) © 2010 Springer.

A necessary condition for image generation is the exact information about the magnetic resonance signal's spatial origin. This spatial information is generated by additional site-dependent magnetic fields, called magnetic field gradients, along the three spatial axes. Due to these field gradients—much smaller in magnitude than the homogeneous main field—the magnetic field is grid-like (see Figure ​ Figure4C) 4C ) slightly different in each volume element (voxel). As a consequence, the application of an RF pulse with the frequency ω' excites only the nuclear magnetic moment ensemble in voxels where the Larmor frequency ω 0 —given by the local magnetic field strength—matches the resonance condition. The signal intensity which is determined by the number of nuclear spins and the relaxation times characteristic for the particular tissue (Figure ​ (Figure4B) 4B ) is assigned in this spatial encoding procedure to an element (pixel) in the three-dimensional image. The MRI scanner (Figure ​ (Figure4A) 4A ) comprising the homogeneous magnetic field, the RF systems, and the gradient fields is controlled by a computer including fast Fourier-transform algorithms for frequency analysis.

Functional magnetic resonance imaging (fMRI) is based on the effect that in the case of activation of neurons by, e.g., musical stimuli, an oxygen (O 2 )-enrichment occurs in oxyhemoglobin which gives rise to an enhancement of the relaxation time T2 (Birbaumer and Schmidt, 2010 ) of the protons of this molecule and an enhancement of the magnetic resonance signal. This effect which enables active brain areas to be imaged is called BOLD (blood oxygen level dependent) effect.

By an increase of the magnetic field strength, the signal-to-noise ratio and thereby the spatial resolution can be enhanced.

Positron emission tomography (PET)

PET imaging is based on the annihilation of positrons with electrons of the body. The positrons are emitted from proton-rich radioactive atomic nuclei (see Table ​ Table1) 1 ) which are embedded in specific biomolecules (Figure ​ (Figure5A). 5A ). The positron-electron annihilation process gives rise to two high-energy (0.511 MeV) annihilation photons (Figure ​ (Figure5B) 5B ) which can be monitored by radiation detectors around the body of the patient and thereby identify the site of the radioactive element. In a PET camera or PET scanner many detectors are implemented (Figure ​ (Figure5B) 5B ) allowing for tomographic imaging with good spatial resolution of about 4 mm.

PET isotopes produced by high energy protons in a cyclotron accelerator.

see http://en.wikipedia.org/wiki/Positron_emission_tomography ; downloaded 22.12. 14 .

(A) Chemical formulae of two compounds doped with the positron emitters 18 F (left. http://de.wikipedia.org/wiki/Fluordesoxyglucose ; 19.12.14) and 11 C (right; http://www.ncbi.nlm.nih.gov/books/NBK23614/ 19.12.14) for PET scans. (B) Principles of positron emission tomography (PET). Left: A positron is emitted from a radioactive nucleus and annihilated with electrons of the tissue emitting two colinear annihilation photons which are monitored by radiation detectors and checked for coincidence. Right: Multi-detector PET scanner taking images (slices) of the concentration of positron emitting isotopes in the brain and thereby measuring the emotional activity of brain sections (Birbaumer and Schmidt, 2010 ). Reprinted with permission from Birbaumer and Schmidt ( 2010 ) © 2010 Springer.

Making use of fluorodeoxyglucose ( 18 F-FDG) doped with the radioactive fluorine isotope 18 F (Figure ​ (Figure5A), 5A ), the local sugar metabolism in neurologically activated areas of the brain can be monitored (Figure ​ (Figure5B). 5B ). After injection of 18 F-FDG into a patient, a PET scanner (Figure ​ (Figure5B) 5B ) can form a three-dimensional image of the 18 F-FDG concentration in the body. For specifically probing molecular changes in postsynaptic monoamine receptors such as the dopamine receptor D 2 and the serotonin receptor 5-HT 2A , 11 C-N-methyl-spiperone (11C-MNSP, Figure ​ Figure5A) 5A ) doped with the positron-emitting carbon isotope 11 C can be used. It should be pointed out here that the combination of MRI/PET (Bailey et al., 2014 ) represents an innovative imaging modality.

Experimental results of functional (tomographic) brain imaging (fMRI, PET)

Movements during listening to music.

Music is a universal feature of human societies, partly owing to its power to evoke strong emotions and influence moods. Understanding of neural correlates of music-evoked emotions has been invaluable for the understanding of human emotions (Koelsch, 2014 ).

Functional neuroimaging studies on music and emotion, such as fMRI and PET (see Figure ​ Figure6A) 6A ) show that music can modulate the activity in brain structures that are known to be crucially involved in emotion, such as the amygdala and nucleus accumbens (NAc). The nucleus accumbens plays an important role in the mesolimbic system generating pleasure, laughter, reward but also fear, aggression, impulsivity, and addiction. The mesolimbic system is additionally intensely involved in emotional learning processes. Drugs can in this system effectuate the release of the neurotransmitter dopamine (Figure ​ (Figure6B). 6B ). Neurotransmitters such as dopamine, serotonin, adrenaline, noradrenaline, or acetylcholine are biochemicals (see Figure 6B) which diffuse across a chemical synapse, bind to a postsynaptic receptor opening a sodium ion (Na + ) channel to transfer the excitation of a neuron to the neighboring neuron.

(A) Neural correlates of music-evoked emotions. A meta-analysis of brain-imaging studies that shows neural correlates of music-evoked emotions. A meta-analysis is a statistical analysis of a lager set of the analyses of earlier data. The meta -analysis indicates clusters of activities derived from numerous studies (for references see Koelsch, 2014 ) in the amygdala (SF, LB), the hippocampal formation (a), the left caudate nucleus with a maximum in the nucleus accumbens (NAc, b), pre-supplementary motor area (SMA), rostral cingulated zone (RCZ), orbifrontal cortex (OFC), and mediodorsal thalamus (MD, c), as well as in auditory regions (Heschls gyrus HG) and anterior superior temporal gyrus (aSTG, d). Additional limbic and paralimbic brain areas may contribute to music-evoked emotions. For details see Koelsch ( 2014 ). Reprinted with permission from Koelsch ( 2014 ) © 2014 Nature Publishing Group. (B) Structural formula of dopamine ( http://de.wikipedia.org/wiki/Dopamin ) downloaded19.12.14.

A meta-analysis of functional neuroimaging studies (fMRI, PET) of music-evoked emotions is shown in Figure ​ Figure6A, 6A , including studies of music of intense pleasure, consonant or dissonant music, happy or sad music, joy- or fear-evoking music, muzak, expectancy violations, and music-evoked tension (for references see Koelsch, 2014 ).

In response to music, changes of the activity of the amygdala, the hippocampus, the right central striatum, the auditory cortex, the pre-supplementary motor area, the cingulate cortex, and the orbitofrontal cortex are observed (Figure ​ (Figure6A). 6A ). In the following, the role of the amygdala, the nucleus accumbens and the hippocampus in music-evoked emotion is briefly discussed in more detail.

The amygdala is central in the emotion network and can regulate and modulate this network. It processes emotions such as happiness, anxiety, anger, annoyance, and, additionally assesses the impression of facial expression and thereby contributes to communication, social behavior, and memory (Kraus and Canlon, 2012 ). It, moreover, releases a number of neurotransmitters such as dopamine and serotonin, and effectuates reflexes such as being scared (Kraus and Canlon, 2012 ). The amygdala receives input from the central auditory system (Kraus and Canlon, 2012 ) and the sensory systems, and its pathways to the hypothalamus affect the sympathetic neuronal system for the release of hormones via the hypothalamus-pituitary-adrenal (HPA)-axis but also the parasympathetic neuronal system (Kraus and Canlon, 2012 ). The hormone cortisol and the neuropeptide endorphine have been observed in musical tasks 20 years ago (see Kreutz et al., 2012 ).

Fear conditioning is mediated by synaptic plasticity in the amygdala (Koelsch et al., 2006 ). It may affect the auditory cortex and its plasticity (learning) by a thalamus-amygdala-cullicular feedback circuit (Figure ​ (Figure7A). 7A ). Neuronal pathways between the hippocampus and the amygdala allow for a direct interaction of emotion and declarative verbally describable memory and vice versa (Koelsch et al., 2006 ).

(A) Main pathways underlying autonomic and muscular responses to music. The cortex (AC) also projects to the orbifrontal cortex (OFC) and the cingulated cortex (projections not shown). Moreover, the amygdala (AMYG), the OFC and the cingulated cortex send numerous projections to the hypothalamus (not shown) and thus also exert influence on the endocrine system. ACC, anterior cingulate cortex; CN, cochlear nuclei; IC, inferior colliculus; M1, primary motor cortex; MCC, middle cingulate cortex; MGB, medial geniculate body; NAc, nucleus accumbens; PMC, premotor cortex; RCZ, rostral cingulated zone; VN, vestibular nuclei (Koelsch, 2014 ). Reprinted with permission from Koelsch ( 2014 ) © 2014 Nature Publishing Group. (B) Hippocampus. Reprinted with permission from Annie Krusznis © 2016.

The superficial amygdala is sensitive to faces, sounds, and music that is perceived as pleasant or joyful. Functional connections between the superficial amygdala, the nucleus accumbens (Figure ​ (Figure7A), 7A ), and the mediodorsal thalamus are stronger during joy-evoking music than during fear-evoking music. The laterobasal amygdala shows activity changes during joyful or sad music. The connection of the amygdala to the hypothalamus affects the sympathetic neuronal system for the release of corticosteroid hormones via the HPS-axis and also affects the parasympathetic neural system (Kraus and Canlon, 2012 ). Functional magnetic resonance imaging (fMRI) (Koelsch et al., 2006 ) evidenced music-induced activity changes in the amygdala, ventral striatum and the hippocampal formation without the experience of “chills.” The study compared the brain responses of joyful dance-tunes by A. Dvorak and J. S. Bach (Figure ​ (Figure8) 8 ) played by professional musicians with responses to electronically manipulated dissonant (unpleasant) variations of these tunes. Unpleasant music induced increases of the blood-oxygen-level dependent (BOLD) signals in the amygdala and the hippocampus in contrast to pleasant music giving rise to BOLD decreases in these structures. In a PET experiment (Blood and Zatorre, 2001 ) the participants' favorite CD music was used in order to induce “chills” or “shivers down the spine.” Increased chill intensity was observed in brain regions ascribed to reward and emotion such as the nucleus accumbens (NAc), in the anterior cingulate cortex (ACC) and the orbitofrontal cortex (see Figure ​ Figure7A). 7A ). Decreases of the blood flow were observed in the amygdala and the anterior hippocampal formation with increasing chill intensity.

Joyful instrumental dance-tunes of major-minor tonal music by Dvorak ( 1955 ) and Bach ( 1967 ) used from commercially available CDs as pleasant stimuli in Koelsch et al. ( 2006 ). Reprinted with permission from Bach ( 1967 ) © 1967 Bärenreiter.

These observations demonstrated the modulation of the activities of the brain core structures ascribed to emotion processing by music. Furthermore, they gave direct support to the phenomenological efforts in music-therapeutic approaches for the treatment of disorders such as depression and anxiety because these disorders are partly ascribed to dysfunctions of the amygdala and presumably of the hippocampus (Koelsch and Stegemann, 2012 ) (see section Musical Therapy for Psychiatric or Neurologic Impairments and Deficiencies in Music Perception).

Nucleus accumbens (NAc)

The activities observed by functional neuroimaging in this brain section (see Figure ​ Figure7A) 7A ) are initiated by “musical frissons,” involving experiences of shivers or goose bumps. This brain section is sensitive to primary rewards (food, drinks, or sex), consuming the rewards, and to addiction. This shows that music-evoked pleasure is associated with the activation of a phylogenetically old reward network that functions to ensure the survival of the individual and the species. The network seems to be functionally connected with the auditory cortex: while listening to music the functional connectivity between the nucleus accumbens and the auditory cortex predicts whether individuals will decide to buy a song (Salimpoor et al., 2013 ).

A PET study on musical frissons (Blood and Zatorre, 2001 ) making use of the radioactive marker 11 C-raclopride to measure the release of the neurotransmitter dopamine at synapses indicated that neural activity in the ventral and dorsal striatum involves increased dopamine availability, probably released by dopaminergic neurons in the ventral tegmental area (VTA). This indicates that music-evoked pleasure is associated with activation of the mesolimbic dopaminergic reward pathway.

Hippocampus

A number of studies on music-evoked emotions has reported activity changes in the hippocampus (see Figure ​ Figure7B), 7B ), in striking contrast to the monetary or erotic rewards which do not activate the hippocampus (see Koelsch, 2014 ). This suggests that music-evoked emotions are not related to reward alone. Hippocampal activity was associated in some studies with music-evoked tenderness, peacefulness, joy, frissons or sadness and both, positive or negative emotions (for references see Koelsch, 2014 ). There is mounting evidence that the hippocampus is involved in emotion due to its role in the hippothalamus-pituitary-adrenal (HPA) axis stress response. The hippocampus appears to be involved in music-evoked positive emotions that have endocrine effects (see section Psychoneuroendocrinology—Neuroendocrine and Immunological Markers) associated with a reduction of emotional stress effectuated by a lowering of the cortisol (C 21 H 30 O 5 ) level which controls the carbon hydrate, fat, and protein metabolisms.

Another emotional function of the hippocampus in humans, beyond stress regulation, is the formation and maintenance of social attachments, such as, e.g., love. The evocation of attachment-related neurological activities by music appears to confirm the phenomenologically observed social functions of music establishing, maintaining, and strengthening social attachments. In this sense, music is directly related to the fulfillment of basic human needs, such as contact and communication, social cohesion and attachment (Koelsch, 2014 ). Some researchers even speculate that the strengthening of inter-individual attachments could have been an important adaptive function of music in the evolution of humans (Koelsch, 2014 ).

The prominent task of the hippocampal-auditory system is the long-term auditive memory. The downloading from the music memory activates the hippocampus predominantly on the right hemisphere (Watanabe et al., 2008 ). The hippocampus is, due to its projections to the amygdala, also involved in the emotional processing of music (Mitterschiffthaler et al., 2007 ). fMRI studies show an activation of the right hippocampus and the amygdala by sad music but not by happy or neutral music (Koelsch et al., 2006 ). Functional neuroimaging studies investigated how music influences and interacts with the processing of visual information (see Koelsch, 2014 ). These studies show that a combination of films or images with music expressing joy, fear, or surprise increase BOLD responses in the amygdala or the hippocampus (see Koelsch, 2014 ).

The hippocampus finds projections from the frontal, temporal and parietal lobes, as well as from the parahippocampal and the perirhinal cortices. The amygdala can modify the information storage processes of the hippocampus but, inversely, the reactions generated in the amygdala by external stimuli can be influenced by the hippocampus. These synergetic effects can contribute to the long-term storage of emotional events which is supported by the plasticity of the two units, enabling the acquisition of experience.

The degree of overlap between music-evoked emotions and so-called everyday emotions remains to be specified. Some musical emotions may appear in everyday life, such as surprise or joy. Some emotions are sought in music because they might be rare in everyday life, such as transcendence or wonder and some so-called moral emotions of everyday life, such as shame or guilt are lacking in music (Koelsch, 2014 ).

The molecular level of music-evoked neural processes can be achieved by making use of PET scans employing biomolecules doped with radioactive positron emitters. By using 11 C-N-methyl-spiperone ( 11 C-NMSP, see Figure ​ Figure5A) 5A ) as an antagonist binding the postsynaptic dopamine receptor 2 (D 2 ) and the serotonin receptor 5-hydroxytriptamine2A (5-HT 2A , see Figure ​ Figure9A), 9A ), acute changes of these neurotransmitter receptors in response to frightening music could be demonstrated (Zhang et al., 2012 ). Thus, the binding of 11 C-NMSP directly reflects the postsynaptic receptor level. Because the antagonist 11 C-NMSP binds predominantly D 2 in the striatum and 5-HT 2A in the cortex the antagonist can be used to map these receptors directly and simultaneously in the same individual (Watanabe, 2012 ). It is hypothesized (Zhang et al., 2012 ) that emotional processing of fear is mediated by the D 2 and the 5-HT 2A receptors. Frightening music is reported (Zhang et al., 2012 ) to rapidly arouse emotions in listeners that mimic those from actual life-threatening experiences.

(A) 5-hydroxytryptamine (serotonin) receptor 2A (5-HT 2A ), G protein coupled; diameter of the protein alpha-helix ~0.5 nm https://en.wikipedia.org/wiki/5-HT2A_receptor downloaded 4. 10. 2016. (B) PET images showing decrease in 11 C-NMSP binding clusters (arrows) in a subject listening to frightening music: right caudate head, right frontal subgirus, and right anterior cingulated (A); left lateral globus pallidus and left caudate body (B); right anterior cingulated (C); and right superior temporal gyrus, right claustrum, and right amygdala. (D) (Zhang et al., 2012 ). Reprinted with permission from Zhang et al. ( 2012 ) © 2012 SNMMI. (C) PET images showing increase in 11C-NMSP binding clusters (arrows) in a subject listening to frightening music: right frontal lobe and middle frontal gyrus (A); right fusiform gyrus and right middle occipital gyrus (B); right superior occipital gyrus, right middle occipital gyrus (C); and left middle temporal gyrus (D) (Zhang et al., 2012 ). Reprinted with permission from Zhang et al. ( 2012 ) © 2012 SNMMI.

However, studies of the underlying mechanisms for perceiving danger created by music are limited. The musical stimulus in the investigations on frightening music (Zhang et al., 2012 ) discussed here was selected from the Japanese horror film Ju-On which is widely accepted as one of the scariest and most influential movies ever made (Shimizu, 2004 ). The film music (see The Grudge theme song https://www.youtube.com/watch?v=1dqjXyIu02s ) has been composed by Shiro Sato.

For the PET scans (see Figures 9B,C ) 11 C-NMSP-activities of 740 MBq (20 mCi) were used. In the course of frightening music significant decreases in 11 C-NMSP binding was observed in the limbic and paralimbic brain regions in four clusters (Figure ​ (Figure9B): 9B ): In the right caudate head, the right frontal subgyral region, and the right anterior cingulate region (A); the left lateral globus pallidus and left caudate body (B); the right anterior cingulate region (C); and the right superior temporal gyrus, right claustrum, and right amygdala (D). Increased 11 C-NMSP accumulation (Figure ​ (Figure9C) 9C ) was found in the cerebral cortex, in the right frontal lobe and the middle frontal gyrus (A); the right fusiform gyrus and the right middle occipital gyrus (B); the right superior occipital gyrus, the right middle occipital gyrus, and the superior occipital gyrus (C); and the left middle temporal gyrus (D).

The decrease in the caudate nucleus in response to frightening music indicates that frightening music triggers a downregulation of postsynaptic D 2. This suggests that the caudate nucleus is involved in a wide range of emotional processes evoked by music (Zhang et al., 2012 ). The finding that the 11 C-NMSP binding decreases significantly (Figure ​ (Figure9B) 9B ) during frightening music demonstrates the musical triggering of the monoamine receptors in the amygdala. It is assumed (Zhang et al., 2012 ) that changes of 11 C-NMSP binding (Figures 9B,C ) mainly reflect 5-HT 2A levels in the cortex, where 5-HT 2A overdensity is thought to be involved in the pathogenesis of depression (Eison and Mullins, 1996 ).

It should be additionally pointed out that the 11 C-NMSP PET study (Zhang et al., 2012 ) found the right hemisphere to have superiority in the processing of auditory stimuli and the defense reaction.

Movements of performing musicians

Brain activation of professional classical singers has been monitored by fMRI during overt singing and imagined singing of an Italian aria (Kleber et al., 2007 ). Overt singing (Figure 10A ) involved bilateral primary (A1) and secondary sensorimotor areas (SMA) and auditory cortices with Broca's and Wernike's areas but also areas associated with speech and language.

(A) Overt singing. The activation maps show activations of the bilateral sensorimotor cortex and the cerebellum, the bilateral auditory cortex, Broca's and Wernicke's areas, medulla, thalamus, and ventral striatum but also ACC and insula were activated. Coordinates of cuts are given above each slice (Kleber et al., 2007 ). Reprinted with permission from Kleber et al. ( 2007 ) © 2007 Elsevier. (B) Mental rehearsal of singing (imaginary singing). Activation of typical imagery regions such as sensorimotor areas (SMA), premotor cortex areas, thalamus, basal ganglia, and cerebellum. Areas processing emotions showed intense activation (ACC and insula, hippocampus, amygdala, and ventrolateral prefrontal cortex). Coordinates of cuts are given above each slice (Kleber et al., 2007 ). Reprinted with permission from Kleber et al. ( 2007 ) © 2007 Elsevier.

Activation in the gyri of Heschl occurred in both hemispheres, together with the subcortical motor areas (cerebellum, thalamus, medulla and basal ganglia) and slight activation in areas of emotional processing (anterior cingulate cortex, anterior insula). Imagined singing (Figure 10B ) effectuated cerebral activation centered in fronto-parietal areas and bilateral primary and secondary sensorimotor areas. No activation was found in the primary auditory cortex or in the auditory belt area. Regions processing emotion showed intense activation (anterior cingulate cortex—ACC, insula, hippocampus, and amygdala).

Performing music in one's mind is a technique commonly used by professional musicians to rehearse. Composers write music regardless of the presence of a musical instrument, as, e.g., Mozart or Schubert did (see Kleber et al., 2007 ). Singing of classical music involves technical-motor and emotional engagement in order to communicate artistic, emotional, and semantic aspects of the song. A tight regulation of pitch, meter, and rhythm as well as an increased sound intensity and vocal range, vibrato and a dramatic expression of emotion are indispensible. Motor aspects of these requirements are reflected in a fine laryngeal motor control and a high involvement of the thoracic muscles during singing. The aria used in this study (Kleber et al., 2007 ) comprises text, rhythm, and melody which make the bilateral activation of A1 plausible.

For the study of music-evoked emotions during performing in the fMRI scanner the bel canto aria Caro mio ben by Tommaso Giordani (1730-1806) has been used (Kleber et al., 2007 ).

Interestingly, most areas involved in motor processing were activated both during overt singing and imaginary singing, a finding that may demonstrate the significance of imagined rehearsal. The basal ganglia which were active in both overt and imaginary singing may be involved in the modulation of the voice. The overt singing task activated only the ACC and the insula which were both also activated during imaginary singing. The ACC is involved in the recall of emotions (Kleber et al., 2007 )—a capability which is important for both overt and imaginary performance. The activation of the insula seems to reflect the intensity of the emotion. The amygdala which was only activated by imagined singing is known to be involved in passive avoidance or approach tasks. This is reported (Kleber et al., 2007 ) to be consistent with the observation that the amygdala was not active during overt singing. Imagined singing activated a large fronto-parietal network, indicating increased involvement of working memory processes during mental imagery which in turn may indicate that imagined singing is less automatized than overt singing (Kleber et al., 2007 ). Areas processing emotions showed also enhanced activation during imagined singing which may reflect increased emotional recall during this task.

An overview of the sensory-motor control of the singing voice has been given based on fMRI research of somatosensory and auditory feedback processing during singing in comparison to theoretical models (Zarate, 2013 ).

Movement organization that enables skilled piano performance has been recently reviewed, including the advances in diagnosis and therapy of movement disorders (Furuya and Altenmüller, 2013 ).

Psychoneuroendocrinology—neuroendocrine and immunological markers

Psychoneuroendocrinology (PNE) aims at the study of the musical experiences leading to hormonal changes in the brain and the body. These effects may be similar to those effectuated by pharmacological substances. In addition to investigating psychiatric illnesses and syndromes, PNE investigates more positive experiences such as the neurobiology of love (see Kreutz et al., 2012 ). In contrast to the neuronal system which transmits its messages by electrical signals, the endocrinal system makes use of biomolecules, such as hormones in order to communicate with the target organs which are equipped with specific receptors for these hormones (see Birbaumer and Schmidt, 2010 ).

For considering the neuroendocrine and immunological molecular markers which could be released during music-evoked emotion, the three interrelated systems regulating hormonal stress responses should be briefly introduced:

The hypothalamic-pituitary-adrenocortical axis (HPA). This axis is initiated by a stimulus in the brain area of the hypothalamus giving rise to the release of the corticotropin releasing factor (CRF) which in turn leads to the release of adrenocorticotropic hormone (ACTH) and beta-endorphin from the pituitary into the circulation. ACTH then stimulates the synthesis and release of cortisol and of testosterone from the adrenal cortex.

Beta-endorphin (see Figure ​ Figure11) 11 ) is a hormone where increased concentration levels are associated with situative stress. Delivering special relaxation music to coronary patients leads to significant decrease of beta-endorphin concentration with a simultaneous reduction of blood pressure, anxiety and worry. Music therapy can also be effective before and during surgeries in operating theaters, again due to a reduction of the beta-endorphin level (see Kreutz et al., 2012 ).

Neuroendocrine and immunological molecular markers released during music- evoked emotion (see Kreutz et al., 2012 ). The molecular masses are given in kDa = 1.66 × 10 −24 kg. http://en.wikipedia.org/wiki/Beta-endorphin#mediaviewer/File:Betaendorphin.png ; http://de.wikipedia.org/wiki/Cortisol ; http://de.wikipedia.org/wiki/Testosteron ; http://de.wikipedia.org/wiki/Prolaktin ; http://de.wikipedia.org/wiki/Oxytocin ; http://en.wikipedia.org/wiki/Immunoglobulin_A downloads 20.12.2014.

Cortisol (see Figure ​ Figure11) 11 ) is a hormone where high levels of concentration are associated with psychological and physiological stresses. Listening to classical choral, meditative, or folk music significantly reduces the cortisol level, however, increases have been detected for listeners exposed to Techno (see Kreutz et al., 2012 ). Individual differences were evidenced in listening experiments where music students responded with increases and biology students with decreases of the cortisol levels. Changes of the cortisol concentration can also be induced by actively singing. In clinical context, exposure to music has been shown to reduce cortisol levels during medical treatment. In gender studies cortisol reductions were found in females in contrast to males, exhibiting increases. Little is known about the sustainability of these effects over a longer period of time (see Kreutz et al., 2012 ).

Testosterone (see Figure ​ Figure11), 11 ), a sex hormone, appears to be of particular relevance to music. Darwin ( 1871 ; see Kreutz et al., 2012 ) suggests music as originating from sexual selection. Female composers showed above average and male composers below average testosterone levels which has initiated discussions whether physiologically androgynous individuals are on a higher level of creativity.

Secretory immunoglobulin A (sIgA; see Figure ​ Figure11) 11 ) is an antibody considered as a molecular marker of the local immune system in the respiratory tract and as a first line of defense against bacterial and viral infections. High levels of sIgA may exert positive effects and low levels may be characteristic for chronic stress. Significant increases of sIgA concentrations were observed in response to listening to relaxation music or musak. Increases of the sIgA concentration were observed from rehearsal to public performance of choral singers (Kreutz et al., 2012 ).

Another study investigated the concentration of prolactin (see Figure ​ Figure11) 11 ) while listening to music of Hans-Werner Henze. The concentration of prolactin which is a hormone with important regulatory functions during pregnancy decreased in response to Henze (Kreutz et al., 2012 ).

It should be summarized that the neuroendocrine changes reflecting the psychophysiological processes in response to music appear to be complex but might promise favorable effects with respect to health implications deserving enhanced research activities.

The simpatho-adrenomedullary system is part of the sympathetic nervous system executing fight and flight responses. By, e.g., stress activation, norepinephrine is released. Sympathetic enervations of the medulla of the adrenal glands give rise to the secretion of the catecholamines (dopamine, epinephrine, norepinephrine). Since this works by nervous operation of the adreanal gland it responds much faster than the HPA which is regulated by hormonal processes.

The endogeneous opioid system is related to the HPA axis and can influence the ACTH and cortisol levels in the blood (see Kreutz et al., 2012 ). None of these three responses is specific to one kind of challenge and the response delays vary to a great deal.

There is an increasing interest in PNE research for studying musical behavior due to the increasing specificity of neuroendocrinological research technologies. It is likely that musical behaviors significantly influence neurotransmitter processes.

Whether music processing can be associated with the processing of, e.g., linguistic sound is a matter of debate (Kreutz et al., 2012 ). However, functional imaging brain studies suggest that the perception of singing is different of the perception of speech since singing evokes stronger activations in the subcortical regions which are associated with emotional processing (see Kreutz et al., 2012 ).

Experiments are suggested (Chanda and Levitin, 2013 ) that aim to uncover the connection between music, the neurochemical changes in the following health domains

• Reward, motivation, and pleasure,
• Stress and arousal,
• Immunity, and
• Social affiliation,

and the neurochemical systems

• Dopamine and opioids,
• Cortisol, adrenocorticotropic hormone (ACTH)
• Serotonin, and
• And the “love” drug oxytocin (see Figure ​ Figure11 11 ).

Electro- and magnetoencephalography (EEG, MEG)

Electroencephalography (eeg) and event-related brain potentials (erp).

This technique yields valuable information on the brain—behavior relationship on much shorter time scales (ms) than tomography, however, with limited spatial information.

Measurements of electrical potentials are performed making use of an array of voltage probes on the scalp. The EEG arises due to electrical potential oscillations in the brain, i.e., by excitatory postsynaptic potentials. Cortical afferences of the thalamus activate the apical dendrities (see Figure ​ Figure12). 12 ). Compensating extracellular electrical currents (Figure ​ (Figure12) 12 ) generate measurable potentials on the scalp with characteristic oscillations in the frequency range of about 4–15 Hz (Birbaumer and Schmidt, 2010 ). Event-related brain potentials (ERPs) are of particular interest in the present context of considering music-evoked emotions (Neuhaus, 2013 ). By synchronized averaging of many measurements, the ERPs are extracted from noise showing a sequence of characteristic components which can be ascribed to separate phases of cognitive processes. Slow negative potentials (100–600 ms) are thought to be generated by cortical cholinergic synapses with high synchronization of pulses at the apical dendrites (see Figure ​ Figure12). 12 ). Positive potentials may be due to a decrease of the synchronization of the thalamic activity (Birbaumer and Schmidt, 2010 ).

Negative surface slow brain potentials on the skalp are generated by extracellular currents (red dashed arrows) which arise due to the electrical activation of apical dendrites by thalamocortical afferences (Birbaumer and Schmidt, 2010 ). Reprinted with permission from Birbaumer and Schmidt ( 2010 ) © 2010 Springer.

The interpretation of single ERP components as correlates of processing specific information is on a phenomenological stage. Up to 300 ms the components are ascribed to unconscious (autonomous) processing. Changes of consciousness can be attributed to components from 300 ms and higher (Birbaumer and Schmidt, 2010 ).

An impressive neurocognitive approach to musical form perception has been presented recently by ERP studies (Neuhaus, 2013 ). The study investigates the listeners' chunking abilities of two eight-measure theme types AABB and ABAB for pattern similarity (AA) and pattern contrast (AB). In the experiments a theme type of eight measures in length (2+2+2+2), often found in the Classical and Romantic periods, was used. In addition to behavioral rating considerations, ERP measurements were performed while non-musicians listened. The advantage of ERP, compared to the more direct neuroimaging techniques such as PET and fMRI, is the good time resolution in range of about 10 ms.

The experiments were performed on 20 students without musical training. The tunes were presented in various transpositions so that the tonality has not to be considered as an independent parameter. Each melody of the AABB or ABAB form types used the harmonic scheme tonic—dominant—tonic. The melodies with an average duration of 10.8 s and form part length of 2.7 s were presented from a programmable keyboard with a tempo of 102.4 BPM. The brain activity was measured making use of 59 Ag/AgCl electrodes with an impedance below 5 Ω.

In the behavioral studies the sequence ABAB is more often assessed as non-sequential than the sequence AABB. The tendency to recognize chunk form parts was high with the two following aspects coinciding: Rhythmic contrasts in A and B and when the melodic contour was upward- downward.

In grand average ERPs, an anterior negative shift N300 for immediate AA sequences as well as for non-immediate repetitions ABA or ABAB of similar form parts was observed suggesting pattern matching at phrase onsets based on rhythmical similarity. In the discussion of the grand average the most interesting feature is the negative shift in the time range 300–600 ms with a maximum in the fronto-central brain. This is ascribed to recognition of pattern similarity at phrase onsets with exactly the same rhythmical structure. The maximum amplitudes measured in the frontal parts of the brain suggest that non-expert listeners use the frontal part working memory for musical pattern recognition processes.

Magnetoencephalography (MEG)

Weak magnetic fields which can be detected on the scalp are generated by the electrical currents in the brain (Figure 13A ). By measuring these magnetic fields by a highly sensitive detector (Figure 13B ), a tomographic image (MEG) of the brain activities can be reconstructed. The brain comprises about 2 × 10 10 cells and about 10 14 synapses. The dendritic current in the cell (see Figure 13A ) generally flows perpendicular to the cortex (Figure 13A ). In the case of the sulcus, this gives rise to a magnetic field in parallel to the scalp which is suggested to be detected outside when about 100,000 cells contribute, e.g., in the auditory cortex, with a spatial resolution of about 2–3 mm (Vrba and Robinson, 2001 ).

(A) Origin of the MEG signal. (a) Coronal section of the human brain with the cortex in dark color. The electrical currents flow roughly perpendicular to the cortex. (b) In the convoluted cortex with the sulci and gyri the currents flow either radially or tangentially (c) or radially (d) in the head. (e) The magnetic fields generated by the tangential currents can be detected outside the head (Vrba and Robinson, 2001 ). Reprinted with permission from Vrba and Robinson ( 2001 ) © 2001 Elsevier. (B) (a) Magnetoencephalography facility containing 150 magnetic field sensors. (b) SQUIDs (superconducting quantum interference devices) and sensors immersed for cooling in liquid helium contained in a Dewar vessel (cross section) (Birbaumer and Schmidt, 2010 ). Reprinted with permission from Birbaumer and Schmidt ( 2010 ) © 2010 Springer. (C) Cortical stimulation by pure and piano tones . Left : Medial–lateral coordinates are shown for single equivalent current dipoles fitted to the field patterns evoked by pure sine tones and piano tones in control subjects. The inset defines the coordinate system of the head. Right : Equivalent current dipoles (ECD) shift toward the sagittal midline along the medial–lateral coordinate as a function of the frequency of the tone. Ant–post, anterior–posterior; med–lat, medial–lateral; inf–sup, inferior–superior (Pantev et al., 1998 ). Reprinted with permission from Pantev et al. ( 1998 ) © 2001 Nature Publishing Group.

The brain magnetic fields (10 −13 Tesla) are much smaller than the earth magnetic field (6.5 × 10 −5 Tesla) and much smaller than the urban magnetic noise (10 −6 Tesla) (Vrba and Robinson, 2001 ). The only detectors resolving these small fields are superconducting quantum interference devices (SQUIDs) based on the Josephson effect (see Figure 13B ). The SQUIDs are coupled to the brain magnetic fields using combinations of superconducting coils called flux transformers (primary sensors, see Figure 13B ).

One of the most successful methods for noise elimination is the use of synthetic higher-order gradiometers. A number of approaches is available for image reconstruction of the MEG signals. Present MEG systems incorporate several hundred sensors in a liquid helium helmet array (see Figure 13B ).

By MEG scanning, neuronal activation in the brain can be monitored locally (Vrba and Robinson, 2001 ). Acoustic stimuli are processed in the auditory cortex by neurons that are aggregated into “tonotopic” maps according to their specific frequency tunings (see Pantev et al., 1998 ). In the auditory cortex, the tonotopic representation of the cortical sources corresponding to tones with different spectral content distributes along the medial-lateral axis of the supratemporal lane (see Figure 13C , left), with the medial-lateral center of the cortical activation shifting toward the sagittal midline with increasing frequency (see Figure 13C , right). This shift is less pronounced for a piano tone than for a pure sine tone. In this study, it could be additionally shown that dipole moments for piano tones are enhanced by about 25% in musicians compared with control subjects who had never played an instrument (Pantev et al., 1998 ). In the evaluation of the MEG data, for each evoked magnetic field a single equivalent current dipole (ECD) of about 50 nA was derived by a fit. From that a contribution of ~150,000 dendrites to this magnetic field can be estimated (Pantev et al., 1998 ). The coordinates of the dipole location were calculated satisfying the requirements of an anatomical distance of the ECD to the midsagittal plane of >2 cm and an inferior-superior value of >2 cm.

Skin conductance response (SCR) and finger temperature

In a study of the relationship of the temporal dynamics of emotion and the verse-chorus form of five popular “heartbreak” songs, the listeners' skin conductance responses (SCR; Figure 14A ) and finger temperatures (Figure 14B ) were used to infer levels of arousal and relaxation, respectively (Tsai et al., 2014 ). The passage preceding the chorus and the entrance of the chorus evoked two significant skin conductance responses (see Figure 14A ). These two responses may reflect the arousal associated with the feelings of “wanting” and “liking,” respectively. Brain-imaging studies have shown that pleasurable music activates the listeners' reward system and serves as an abstract reward (Blood and Zatorre, 2001 ). The decrease of the finger temperature (Figure 14A ) within the first part of the songs indicated negative emotions in the listeners, whereas the increases of the finger temperature within the second part may reflect a release of negative emotions. These findings may demonstrate the rewarding nature of the chorus and the cathartic effects associated with the verse-chorus form of heart-break songs.

(A) The median curve of the skin conductance response (SCR) amplitude around the entrance of the chorus. The first downbeat was set to t = 0 s (Tsai et al., 2014 ). The two peaks are ascribed to the two closely related phases of listening experience: anticipatory “wanting” and hedonic “liking” of rewards. Reprinted with permission from Tsai et al. ( 2014 ) © 2014 Sage. (B) The u-shaped time-dependence of the finger temperatures of the listeners during presentation of the five songs. The end of the first chorus (see full dots) devides each song into two parts with a decrease of the finger temperature in the first part and an increase in the second part (Tsai et al., 2014 ). Reprinted with permission from Tsai et al. ( 2014 ) © 2014 Sage. The symbols *** and * indicate that the two peaks are significantly larger than the control data.

Goose bumps—piloerection

The most common psychological elicitors of piloerection or chills are moving music passages, or scenes in movies, plays, or books (see Benedek and Kaernbach, 2011 ). Other elicitors may be heroic or nostalgic moments, or physical contact with other persons. In Charles Darwin's seminal work on The expression of emotions in Man and Animals (1872), he already acknowledged that “…hardly any expressive movement is so general as the involuntary erection of the hairs…” (Darwin, 1872 ). Musical structures for triggering goose bumps or chills are considered to be crescendos, unexpected harmonies, or the entry of a solo voice, a choir, or a an additional instrument. It thus was concluded that piloerection may be a useful indicator which marks individual peaks in emotional arousal. Recently optical measuring techniques have been developed for monitoring and analyzing chills by means of piloerection (Benedek et al., 2010 ).

Additional experimental studies had shown that chills gave rise to higher skin conduction, increased heart and respiratory rates, and an enhancement of skin temperature (see Benedek and Kaernbach, 2011 ). Positron emission tomography correlated to musical chills showed a pattern typical for processes involved in reward, euphoria, and arousal, including ventral striatum, midbrain, amygdala, orbitofrontal cortex, and ventral medial prefrontal cortex (see Benedek and Kaernbach, 2011 ).

In the studies of piloerection as an objective and direct means of monitoring music-evoked emotion, music pieces ranging from 90 s (theme of Pirates of the Caribbean ) to 300 s ( The Scientist ). Film audio tracks ( Knocking on Heavens Door, Dead Poets Society ) ranging from 141 to 148 s were employed. All musical stimuli were averaged to the same root mean square power (RMS), so that they featured equal average power.

Half of the musical stimuli ( My Heart will go on by Celine Dion, Only Time by Enya, and film tracks of Armageddon and Braveheart ) was pre-selected by the experimenter and half, with stronger stimulation, was self-selected by the 50 participants. The stimuli were presented via closed Beyerdynamic DT 770 PRO head-phones (Heilbronn, Germany) at an average sound pressure level of 63 dB. The procedure was approved by the Ethics Committee of the German Psychological Society (Benedek and Kaernbach, 2011 ). The sequence of a measurement is depicted in Figure 15A .

(A) Time-dependence of the relative piloerection intensity of a single experiment, including a baseline period (30 s), stimulus description (20 s) and stimulus presentation (variable duration). The initial stable level of piloerection intensity indicates no visible piloerection. In this experiment, piloerection occurs shortly after the onset of stimulus presentation; after some time it fades away. The asterisk marks the first detected onset of piloerection. This time is used for the short-term physiological response (Benedek and Kaernbach, 2011 ). Reprinted with permission from Benedek and Kaernbach ( 2011 ) © 2011 Elsevier. (B) Procedure of piloerection quantification without (top row) and with visible piloerection (bottom row). From B (bottom) a two-dimensional spatial Fourier transform is computed (C, shown for the frequency range ±1.13 mm −1 ) which is converted to a one-dimensional spectrum of spatial frequency. The maximum spectral power in the 0.23–0.75 mm −1 range (D) is considered as a correlate of the piloerection intensity (Benedek et al., 2010 ). Reprinted with permission from Benedek et al. ( 2010 ) © 2010 Wiley. (C) Time dependence of the short-term response of physiological measurements for a time slot of −15 s to +15 s around the first onset of piloerection. Dark bars indicate significant deviations from zero, white bars indicate non-significant deviations. ISCR-integrated skin conductance response, SCL-skin conductance level, HR-heart rate, PVA-pulse volume amplitude, RR-respiration rate, RD- respiration depth (Benedek and Kaernbach, 2011 ). Reprinted with permission from Benedek and Kaernbach ( 2011 ) © 2011 Elsevier.

The formation of piloerection on the forearm was monitored by a video scanner with a sampling rate of 10 Hz, with simultaneous measurements of the skin conductance response and the increased heart and respiratory rates. By means of the Gooselab software the spatial Fourier transform (Figure 15B ) of a video scan (Figure 15B ) is derived which is a measure of the intensity of piloerection.

Piloerection could not always be detected objectively when indicated by the participant and was sometimes detected without an indication by the participant.

Piloerection starts with the onset of music (Figure 15A ), then increases with a time constant of ~20 s and then fades off (time constant about 10 s). An analysis of the time constants of piloerection and of the kinetics of the simultaneously monitored physiological reactions (Figure 15C ), should provide us with specific information on the neuronal and muscular processes contributing. This has not been discussed up to now. In the physiological quantities (Figure 15C ) studied simultaneously with piloerection, a significant increase in skin conductance response, in heart rate, and in respiration depth has been observed. This demonstrates that a number of subsystems of the sympathetic neuronal system can be activated by music and that in particular listening to film sound tracks initiates a physiological state of intense arousal (Benedek and Kaernbach, 2011 ). Based on the experimental studies of piloerection and physiological quantities (Benedek and Kaernbach, 2011 ), two models of piloerection are discussed (Benedek and Kaernbach, 2011 ): On the one hand, it had been argued that the appearance of piloerection may mark a peak in emotional arousal (see Grewe et al., 2009 ). On the other hand, the psychobiological model (Panksepp, 1995 ) conceives emotional piloerection as an evolutionary relic of thermoregulatory response to an induced sensation of coldness and links it with the emotional quality of sadness (separation call hypothesis) (Panksepp, 1995 ). By comparing the physiological patterns of the two approaches to the experimental results, the authors (Benedek and Kaernbach, 2011 ) favor the separation call hypothesis (Panksepp, 1995 ) to the hypothesis of peak arousal (Grewe et al., 2009 ).

Is there a biological background for the attractiveness of music?—genomic studies

In a recent genomic study, the correlation of the frequency of the listening to music and the availability of the arginine vasopressin receptor 1A (AVPR1A) gene or haplotype (with a length of 1,472 base pairs) has been investigated. A haplotype is a collection of particular d eoxyribonucleic acid (DNA) sequences in a cluster of tightly-linked genes on a chromosome that are likely to be inherited together. In this sense, a haplotype is a group of genes that a progeny inherits from one parent [ http://en.wikipedia.org/wiki/Haplotype ]. The AVPR1A gene encodes for a receptor molecule amino peptide that mediates the influence of the arginine vasopressin (AVP) hormone in the brain which plays an important role in memory and learning [ http://en.wikipedia.org/wiki/Haplotype ]. AVPR1A has been shown to modulate the social cognition and behavior, including social bonding and altruism in humans (Wallum et al., 2008 ). However, in contrast to that, the AVPR1A gene has also been referred to as the “ruthlessness gene” (Hopkin, 2008 ).

Recently an association of the AVPR1A gene with musical aptitude and with creativity in music, e.g., composing and arranging of music, has been reported (see Ukkola-Vuoti et al., 2011 ). In this study (Ukkola-Vuoti et al., 2011 ) a total of 31 Finnish families with 437 family members (mean age 43 years) participated. The musical aptitude of the individuals was tested by means of the Karma test. In this test, which does not depend on training in music, musical aptitude is defined as the ability of auditory structuring (Karma, 2007 ). In addition, the individual frequency of music listening was registered. Genomic DNA was extracted from peripheral blood of the individuals for the determination of the AVPR1A gene. The AVPR1A gene showed strongest association with current active music listening which is defined as attentive listening to music, including attending concerts. No dependence of the musical aptitude was discovered. These results appear to indicate a biological background for the attractiveness of music. The association with the AVPR1A gene suggests that listening to music is related to the neural pathways affecting attachment behavior and social communication (Ukkola-Vuoti et al., 2011 ).

Towards a theory of musical emotions

In a recent overview (Juslin, 2013 ) aimed at a unified theory of musical emotions, a framework is suggested that tries to explain both the everyday emotions and aesthetic emotions, and yields some outlines for future research. This model comprises eight mechanisms for emotion by music—referred to as BRECVEMA: Brain stem reflexes, Rhythmic entrainment, Evaluative conditioning, Contagion, Visual imagery, Episodic memory, Musical expectancy, and Aesthetic judgment. The first seven mechanisms (BRECVEM) arousing the everyday emotions, are each correlated (see Juslin, 2013 ) to the evolutionary order, the survival value of the brain functions, the information focus, the mental representation, the key brain regions identified experimentally, the cultural impact, the ontogenetic development, the induced effect, the temporal focus of the effect, the induction speed, the degree of volitional influence, the availability of consciousness, and the dependence of musical structure.

Of particular significance is the addition of a mechanism corresponding to aesthetic judgments of music, in order to better account for typical appreciation emotions such as admiration and awe.

Aesthetic judgments have not received much attention in psychological research to date (Juslin, 2013 ) since aesthetic and stylistic norms and ideas change over time in society. Though it may be difficult to characterize aesthetic judgments, some preliminaries are offered (Juslin, 2013 ) as to how a psychological theory of aesthetic judgment in music experience might look like.

Some pieces of music will invite an aesthetic attitude of the listener due to perceptual inputs by sensory impressions, due to more knowledge-based cognitive inputs, or due to emotional inputs. Some criteria that may underlie listeners' aesthetic judgments of music are suggested (Juslin, 2013 ) such as beauty, wittiness, originality, taste, sublimity, expression, complexity, use as art, artistic skill, emotion arousal, message, representation, and artistic intention. Certain criteria such as expression, emotional arousal, originality, skill, message, or beauty were considered as more important than others (see Figure 16A ) and different listeners tend to focus on different criteria (see Figure 16B ). With its multi-level framework of everyday emotions and aesthetic judgment, the study (Juslin, 2013 ) might help to explain the occurrence of mixed emotions such as bitter-sweet combinations of joy and melancholy.

(A) Mean values and standard errors for listeners' ratings of criteria for aesthetic value of music. (B) Individual ratings of criteria for aesthetic value of music by four subjects (see Juslin, 2013 ). Reprinted with permission from Juslin ( 2013 ) © 2013 Elsevier.

This discussion suggests (Juslin, 2013 ) that researchers have to elaborate specific experimental paradigms that reliably arouse specific emotions in listeners through each of the mechanisms mentioned, including the empirical exploration of candidate-criteria for aesthetic value, similarly to what has been performed for various BRECVEM mechanisms. Empirical research so far has primarily focused on the beauty criterion (see Juslin, 2013 ). Developments of hypotheses for the criteria such as style appreciation, neural correlates of perceived expressivity in music performances, or perceptual correlates of novelty appear feasible (Juslin, 2013 ). An additional possibility could be the use of a neurochemical interference strategy (Chanda and Levitin, 2013 ; Juslin, 2013 ). It has been shown that blocking of a specific class of amino acid receptors in the amygdala can interfere with the acquisition of evaluative conditioning (see Juslin, 2013 ) discussed within BRECVEM. Interactions between BRECVEM mechanisms and aesthetic judgments have yet to be investigated.

Musical therapy for psychiatric or neurologic impairments and deficiencies in music perception

Mounting evidence indicates that making music or listening to music activates a multitude of brain structures involved in cognitive, sensorimotor, and emotional processing (see Koelsch and Stegemann, 2012 ). The present knowledge on the neural correlates of music-evoked emotions and their health-related autonomic, endocrinological, and immunological effects could be used as a starting point for high-quality investigations of the beneficial effects of music on psychological and physiological health (Koelsch and Stegemann, 2012 ).

Music-evoked emotions can give rise to autonomic and endocrine responses as well as to motoric expression of motion (facial expression). The evidence that music improves health and well-being through the engagement of neurochemical systems for (i) reward, motivation and pleasure; (ii) stress and arousal; (iii) immunity; and (iv) social affiliation has been reviewed (Chanda and Levitin, 2013 ). From these observations, criteria for the potential use of music in therapy should be derived.

Dysfunctions and structural abnormalities in, e.g., the amygdala, hippocampus, thalamus, nucleus accumbens, caudate, and cingulate cortex are characteristic in pychiatric and neurological disorders, such as depression, anxiety, stress disorder, Parkinson's disease, schizophrenia, and neurodegenerative diseases. The findings that music can change the activity in these structures should encourage high-quality studies (see Koelsch, 2014 ) of the neural correlates of the therapeutic effects of music in order to provide convincing evidence for these effects (Drevets et al., 2008 ; Maratos et al., 2008 ; Omar et al., 2011 ). The activation of the amygdala and the hippocampal formation by musical chills as demonstrated in PET scans (Blood and Zatorre, 2001 ) may give direct support to the phenomenological efforts in music-therapeutic approaches for the treatment of disorders such as depression and anxiety because these disorders are partly ascribed to dysfunctions of the amygdala and presumably of the hippocampus (Koelsch and Stegemann, 2012 ).

Another condition in which music should have therapeutic effects is autism spectrum disorder (ASD). Functional MRI studies show (Caria et al., 2011 ) that individuals with ASD exhibit relatively intact perception and processing of music-evoked emotions despite their deficit in the ability to understand emotions in non-musical social communication (Lai et al., 2012 ). Active music therapy can be used to develop communication skills since music involves communication capabilities (Koelsch, 2014 ).

With regard to neurodegenerative disorders, some patients with Alzheimer's disease (AD) have almost preserved memory of musical information for, e.g., familiar or popular tunes. Learning of sung lyrics might lead to better retention of words in AD patients and anxiety levels of these patients can be reduced with the aid of music. Because of colocalization of memory functions and emotion in the hippocampus, future studies are suggested to more specifically investigate how music is preserved in AD patients and how it can ameliorate AD effects (Cuddy et al., 2012 ) and other neurodegenerative diseases such as Parkinson's disease (Nombela et al., 2013 ). In addition, music-therapeutical efforts for cancer (Archie et al., 2013 ) or stroke (Johansson, 2012 ) have been reported.

Music has been shown to be effective for the reduction of worries and anxiety (Koelsch and Stegemann, 2012 ) as well as for pain relief in clinical settings with, however, minor effects compared to analgesic drugs (see Koelsch, 2014 ). Deficiencies in music perception are reported for patients with cerebral degeneration or damage (Koelsch, 2014 ). Recognition of music expressing joy, sadness, anger, or fear is impaired in patients with frontotemporal lobar degeneration or damage of the amygdala (Koelsch, 2014 ). Patients with lesions in the hippocampus find dissonant music pleasant in contrast to healthy controls who find dissonance unpleasant. The degree of overlap between music-evoked emotions and so-called everyday emotions remains to be specified.

Conclusions and outlook

As shown by tomographic imaging (fMRI, PET), which exhibits a high spatial resolution, activation of various brain areas can be initiated by musical stimuli. Some of these areas can be correlated to particular functions such as motor or auditive functions activated by non-musical stimuli. In the case of fMRI, emotion processing is identified by the more general feature of local energy consumption. Imaging of emotional processing on a molecular level can be achieved by PET, where specific molecules such as 11 C-NMSP have been employed (Zhang et al., 2012 ) for a targeted investigation of synaptic activity (Zhang et al., 2012 ). A powerful combination of specific detection of molecules and tomographic imaging of the brain could arise from a future development of Raman tomography (Demers et al., 2012 ). Raman scattering provides specific information on the characteristic properties of molecules, such as vibrational or rotational modes.

Development of the technically demanding tomographic methods (fMRI, PET, MEG) for easy use would be highly desirable for the investigation of the emotions of performing musicians or even the astounding sensations of composers while composing, as, e.g., expressed by Ennio Morricone, composer of the music of the film Once upon a time in the West (Spiel mir das Lied vom Tod, 1968): “Vermutlich hat der Komponist, während er ein Stück schreibt, nicht mal die Kontrolle über seine eigenen Emotionen” (Morricone, 2014, Jun 1 ). (The composer, when witing a piece, is probably not even in control of his own emotions). Jörg Widmann, composer of the contemporary opera Babylon (2012), formulates: “Man gerät beim Schreiben in extreme Zustände, kann nicht schlafen, macht weiter in einer Art Rausch – und Rausch ist womöglich der klarste Zustand überhaupt.” (Widmann, 2014, August 20 ) (When composing one gets into extreme states, cannot sleep, continues in a sort of drunkenness—and drunkenness is perhaps the clearest possible state).

Future studies on a targeted molecular level may deepen the understanding of music-evoked emotion. Novel microscopy technologies for investigating single molecules are emerging. The rapid fusion of synaptic vesicles for neurotransmission after optical stimulation has been observed by cryo electron microscopy (Chemistry Nobel Prize 2017) with an electron energy of 200 keV where radiation damage appears tolerable and on a time scale of 15 ms (Watanabe et al., 2013 ) (see Figure 17A ). Radiation damage can be entirely suppressed by combining electron holography and coherent electron diffraction imaging in a low- energy (50–250 eV) lens-less electron microscope with a spatial resolution of 0.2 nm (Latychevskaia et al., 2015 ). Of particular interest is the in vivo optical imaging of neurons (see Figure 17B ) in the brain by STED (stimulated emission depletion) optical microscopy techniques (Chemistry Nobel Prize 2014) with a lateral resolution of 67 nm (Berning et al., 2012 ). The dynamics of the neuron spine morphology on a 7-min time scale (Figure 17B ) potentially reflect alterations in the connectivity in the neural network characteristic for learning processes, even in the adult brain.

(A) Representative cryo electron micrographs of fusing vesicles (see arrows) in mouse hippocampal synapses at 15 ms (c) and 30 ms (d) after light onset (Watanabe et al., 2013 ). Reprinted with permission from Watanabe et al. ( 2013 ) © 2013 Nature Publishing Group. (B) STED (stimulated emission depletion) microscopy in the molecular layer of the somatosensory cortex of a mouse with EYFP-labeled neurons. (A) Anesthetized mouse under the objective lens. (B) Projected volumes of dendritic and axonal structures reveal (C) temporal dynamics of spine morphology with (D) an approximately four-fold improved spatial resolution compared with diffraction limited imaging. The curve is three-pixel-wide line profile fitted to raw data with a Gaussian. Scale bars, 1 μm (Berning et al., 2012 ). Reprinted with permission from Berning et al. ( 2012 ) © 2012 AAAS.

In addition, neurochemical interference strategies could be promising for future research as discussed in section Musical Therapy for Psychiatric or Neurologic Impairments and Deficiencies in Music Perception. For example, blocking of a specific class of amino acid receptors in the amygdala can interfere with the acquisition of evaluative conditioning (Juslin, 2013 ). In fact, studies of the neurochemistry of music may be the next great frontier (Chanda and Levitin, 2013 ), particularly as researchers try to investigate claims about the effects of music on health, where neurochemical studies are thought to be more appropriate than neuroanatomical studies (Chanda and Levitin, 2013 ).

The number of reports on beneficial effects of music on reward, motivation, pleasure, stress, arousal, immunity and social affiliation is mounting and the following issues could have future impact (Chanda and Levitin, 2013 ): (i) Rigorously matched control conditions in postoperative or chronic pain trials, including controls such as speeches, TV, comedy recordings etc. (ii) Experiments to uncover the neurochemical basis of pleasure and reward, such as through the use of the opioid antagonist naloxone in order to discover whether musical pleasure is subserved by the same chemical system as other forms of pleasure (Chanda and Levitin, 2013 ). (iii) Experiments to uncover the connection between oxytoxin (see Figure ​ Figure11), 11 ), group affiliation, and music (Chanda and Levitin, 2013 ). (iv) Investigation of the contribution of stress hormones, vasopressin, dopamine, and opioids in biological assays and pharmacological interventions together with neuroimaging (Chanda and Levitin, 2013 ).

The investigation of particular BRECVEM mechanisms (see section Musical Therapy for Psychiatric or Neurologic Impairments and Deficiencies in Music Perception) could be intensified through specific experiments. The interaction between BRECVEM mechanisms and aesthetic judgments has yet to be explored (Juslin, 2013 ). For an empirical exploration of candidate criteria for aesthetic judgment one has to map the characteristics of separate aesthetic criteria, as has been done with various BRECVEM mechanisms. Empirical research so far has focused on the beauty criterion (see Juslin, 2013 ) The more phenomenological measuring techniques such as encephalographic methods (EEG, MEG), skin conductance, and finger temperature or goose bump development characterized by a high time resolutions of 10 ms to 1 s are powerful tools for future observation of the dynamics and kinetics of emotional processing, where MEG can provide good time resolution together with moderate spatial resolution (Vrba and Robinson, 2001 ).

In addition to short-term studies, high-quality long-term studies would be desirable for the assessment of therapeutic efficacy over months in analogy to the year-long efforts of Carlo Farinelli for King Philipp V of Spain (see Section Historical Comments on the Impact of Music on People).

Author contributions

H-ES selected the topic, performed the literature retrieval, and wrote the manuscript.

Conflict of interest statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer AF declared a shared affiliation, with no collaboration, with the author HS to the handling Editor.

Acknowledgments

The present study has been stimulated by a discussion with Hans-Christoph Rademann, Internationale Bachakademie Stuttgart. Continuous support of Thomas Schipperges, University of Tübingen is highly appreciated. The author is indebted to Christiane Neuhaus, University of Hamburg; Hans-Peter Zenner, University of Tübingen; Klaus Scheffler, Max Planck Institute of Biological Cybernetics and University of Tübingen; Hubert Preissl, Helmholtz Center Munich at the University of Tübingen; Boris Kleber, Sunjung Kim, and Julian Malcolm Clarke, University of Tübingen; and Bernd-Christoph Kämper and Ulrike Mergenthaler, University of Stuttgart for most competent discussions. Bettina Dietrich carefully read the manuscript.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnins.2017.00600/full#supplementary-material

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