music psychology experiments

How to Design a Music and Personality Experiment

At a glance.

A great social experiment idea for students in psychology is exploring how music and personality could be linked. Here are some tips on doing a psychology experiment with music.

Does your taste in music reveal information about your personality? Some researchers have found that people who  prefer certain styles of music  tend to have  specific personality traits . However, other studies have not found links between music preferences and personality, so there is still a lot left to learn from doing such studies.

Exploring the connection between musical tastes and personality traits could be a great topic for your own research. Here’s how to set up a psychological experiment on music and personality.

Getting Started

Before you start  any psychology experiment , discuss your project with your instructor. You may need to get permission from your school's Institutional Review Board before you can proceed.

Once you get the go-ahead, you'll need to narrow your focus to a specific research question and develop a hypothesis. Then, you can begin the process of developing materials and procedures as well as selecting your study participants.

Key Terms and Definitions

These psychology concepts will be important to know as you’re planning your psychology experiment:

• Operational definitions : This includes the procedures, techniques, or methods you will use to change variables in your study.
• Independent variable : This is the variable in your study that you will change.
• Dependent variable : This is the variable in your study that you will observe to see if it is affected by the independent variable. You may have more than one dependent variable.

Possible Research Questions

• Are fast-paced styles of music (such as dance and pop) linked to specific personality traits (such as  extroversion  and high  self-esteem )?
• Are people who like complex musical styles (such as classical) more creative?
• Are people who prefer intense musical styles (such as heavy metal) more assertive?
• Are people who prefer emotional music (like instrumental soundtracks) more reflective?

Develop Your Hypothesis

Once you've picked a research question, the next step is to come up with a hypothesis.

Your  hypothesis  is a specific statement that explains what you predict you will find out in your experiment. For example, your hypothesis for your music and personality study could be that:

• Participants who prefer jazz and classical music will score higher on tests of creativity.
• Participants who prefer fast-paced musical styles will score higher on measures of extraversion.

Planning Your Experiment

You need to carefully plan the steps and procedures you will use in your experiment. There are some key practical questions that you have to answer before you can get started.

First, where will you find participants? You could ask your fellow classmates or seek out volunteers in your school or community.

Next, what materials and tools will you need to collect data on musical preferences and personality? You may need music, headphones, and devices for listening.

How will you assess each participant's musical tastes? The easiest method would be to use a simple questionnaire. You can ask participants to rate different musical styles on a scale from one to 10, with one being least preferred and 10 being most preferred.

You also need to determine how you will measure personality. Are you going to look at specific personality traits, such as emotional stability or extroversion? There are different ways you can approach this experiment, so the choice is up to you. For example, you might choose to look at a single personality dimension, like extraversion or  introversion .

What questions did you decide to explore in your study? Maybe, "Do introverts tend to prefer a specific style of music?" Or, "Are extroverts drawn to faster-paced musical styles?"

You may choose to look at music tastes within the Big Five personality dimensions. Instead of having to come up with a questionnaire, you could have your participants do an existing assessment such as the Ten Item Personality Measure (TIPI).

Collect Data and Analyze Your Results

Once you have collected all the data for your experiment, it is time to analyze your results.

Did you find any evidence to support your hypothesis? Were the results of your experiment statistically significant?

After performing your analysis, you’ll need to report your results according to the format that your instructor has assigned. For example, you may need to write a  psychology lab report  or create a bulletin board presentation.

Examples of Music and Personality Studies 

Here are a few studies on music and personality that could serve as inspiration or references as you create your own:

• Greenberg DM, Wride SJ, Snowden DA, Spathis D, Potter J, Rentfrow PJ. Universals and variations in musical preferences: A study of preferential reactions to Western music in 53 countries .  J Pers Soc Psychol . 2022;122(2):286-309. doi:10.1037/pspp0000397
• Anderson I. “Just the Way You Are”: Linking music listening on spotify and personality . Social Psychological and Personality Science . 2021. doi:10.1177/1948550620923228
• Ewelina Sielska-Badurek, Sobol M, Katarzyna Okulicz-Kozaryn, Paweł Gołda, Cielecka A. Personality traits in singers performing various music styles and with different singing status .  International Journal of Occupational Medicine and Environmental Health . Published online September 25, 2023. doi:10.13075/ijomeh.1896.02099
• Ignacio J. Exploring relations between Big Five personality traits and musical emotions embodied in spontaneous dance . Psychology of Music . 2023. doi:10.1177/03057356221135355
• Qiu L, Chen J, Ramsay JE, Lu J. Personality predicts words in favorite songs .  Journal of Research in Personality . 2019;78:25-35. doi:10.1016/j.jrp.2018.11.004

Devenport SP, North AC. Predicting musical taste: relationships with personality aspects and political orientation . Psychol Music . 2019;47(6):834-847. doi:10.1177/2F0305735619864647

University of Cambridge. Musical preferences unite personalities across the globe .

APA. Institutional review board .

APA. Informed consent .

APA. Operational definitions .

APA. Independent variable .

APA. Dependent variable .

APA. Hypothesis .

Goz Lab. Ten-item personality measure .

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Music moves brain to pay attention, Stanford study finds

August 1, 2007 - By Mitzi Baker

STANFORD, Calif. - Using brain images of people listening to short symphonies by an obscure 18th-century composer, a research team from the Stanford University School of Medicine has gained valuable insight into how the brain sorts out the chaotic world around it.

The research team showed that music engages the areas of the brain involved with paying attention, making predictions and updating the event in memory. Peak brain activity occurred during a short period of silence between musical movements - when seemingly nothing was happening.

Beyond understanding the process of listening to music, their work has far-reaching implications for how human brains sort out events in general. Their findings are published in the Aug. 2 issue of Neuron .

This 20-second clip of a subject's fMRI illustrates how cognitive activity increases in anticipation of the transition points between movements.

The researchers caught glimpses of the brain in action using functional magnetic resonance imaging, or fMRI, which gives a dynamic image showing which parts of the brain are working during a given activity. The goal of the study was to look at how the brain sorts out events, but the research also revealed that musical techniques used by composers 200 years ago help the brain organize incoming information.

"In a concert setting, for example, different individuals listen to a piece of music with wandering attention, but at the transition point between movements, their attention is arrested," said the paper's senior author Vinod Menon , PhD, associate professor of psychiatry and behavioral sciences and of neurosciences.

"I'm not sure if the baroque composers would have thought of it in this way, but certainly from a modern neuroscience perspective, our study shows that this is a moment when individual brains respond in a tightly synchronized manner," Menon said.

The team used music to help study the brain's attempt to make sense of the continual flow of information the real world generates, a process called event segmentation. The brain partitions information into meaningful chunks by extracting information about beginnings, endings and the boundaries between events.

"These transitions between musical movements offer an ideal setting to study the dynamically changing landscape of activity in the brain during this segmentation process," said Devarajan Sridharan, a neurosciences graduate student trained in Indian percussion and first author of the article.

No previous study, to the researchers' knowledge, has directly addressed the question of event segmentation in the act of hearing and, specifically, in music. To explore this area, the team chose pieces of music that contained several movements, which are self-contained sections that break a single work into segments. They chose eight symphonies by the English late-baroque period composer William Boyce (1711-79), because his music has a familiar style but is not widely recognized, and it contains several well-defined transitions between relatively short movements.

The study focused on movement transitions - when the music slows down, is punctuated by a brief silence and begins the next movement. These transitions span a few seconds and are obvious to even a non-musician - an aspect critical to their study, which was limited to participants with no formal music training.

The researchers attempted to mimic the everyday activity of listening to music, while their subjects were lying prone inside the large, noisy chamber of an MRI machine. Ten men and eight women entered the MRI scanner with noise-reducing headphones, with instructions to simply listen passively to the music.

In the analysis of the participants' brain scans, the researchers focused on a 10-second window before and after the transition between movements. They identified two distinct neural networks involved in processing the movement transition, located in two separate areas of the brain. They found what they called a "striking" difference between activity levels in the right and left sides of the brain during the entire transition, with the right side significantly more active.

In this foundational study, the researchers conclude that dynamic changes seen in the fMRI scans reflect the brain's evolving responses to different phases of a symphony. An event change - the movement transition signaled by the termination of one movement, a brief pause, followed by the initiation of a new movement - activates the first network, called the ventral fronto-temporal network. Then a second network, the dorsal fronto-parietal network, turns the spotlight of attention to the change and, upon the next event beginning, updates working memory.

"The study suggests one possible adaptive evolutionary purpose of music," said Jonathan Berger , PhD, associate professor of music and a musician who is another co-author of the study. Music engages the brain over a period of time, he said, and the process of listening to music could be a way that the brain sharpens its ability to anticipate events and sustain attention.

According to the researchers, their findings expand on previous functional brain imaging studies of anticipation, which is at the heart of the musical experience. Even non-musicians are actively engaged, at least subconsciously, in tracking the ongoing development of a musical piece, and forming predictions about what will come next. Typically in music, when something will come next is known, because of the music's underlying pulse or rhythm, but what will occur next is less known, they said.

Having a mismatch between what listeners expect to hear vs. what they actually hear - for example, if an unrelated chord follows an ongoing harmony - triggers similar ventral regions of the brain. Once activated, that region partitions the deviant chord as a different segment with distinct boundaries.

The results of the study "may put us closer to solving the cocktail party problem - how it is that we are able to follow one conversation in a crowded room of many conversations," said one of the co-authors, Daniel Levitin , PhD, a music psychologist from McGill University who has written a popular book called This Is Your Brain on Music: The Science of a Human Obsession .

Chris Chafe , PhD, the Duca Family Professor of Music at Stanford, also contributed to this work. This research was supported by grants from the Natural Sciences and Engineering Research Council of Canada , the National Science Foundation , the Ben and A. Jess Shenson Fund, the National Institutes of Health and a Stanford graduate fellowship. The fMRI analysis was performed at the Stanford Cognitive and Systems Neuroscience Laboratory .

• Mitzi Baker

About Stanford Medicine

Stanford Medicine is an integrated academic health system comprising the Stanford School of Medicine and adult and pediatric health care delivery systems. Together, they harness the full potential of biomedicine through collaborative research, education and clinical care for patients. For more information, please visit med.stanford.edu .

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The psychological functions of music listening

Thomas schäfer.

1 Department of Psychology, Chemnitz University of Technology, Chemnitz, Germany

Peter Sedlmeier

Christine städtler, david huron.

2 School of Music, Cognitive and Systematic Musicology Laboratory, Ohio State University, Columbus, OH, USA

Why do people listen to music? Over the past several decades, scholars have proposed numerous functions that listening to music might fulfill. However, different theoretical approaches, different methods, and different samples have left a heterogeneous picture regarding the number and nature of musical functions. Moreover, there remains no agreement about the underlying dimensions of these functions. Part one of the paper reviews the research contributions that have explicitly referred to musical functions. It is concluded that a comprehensive investigation addressing the basic dimensions underlying the plethora of functions of music listening is warranted. Part two of the paper presents an empirical investigation of hundreds of functions that could be extracted from the reviewed contributions. These functions were distilled to 129 non-redundant functions that were then rated by 834 respondents. Principal component analysis suggested three distinct underlying dimensions: People listen to music to regulate arousal and mood , to achieve self-awareness , and as an expression of social relatedness . The first and second dimensions were judged to be much more important than the third—a result that contrasts with the idea that music has evolved primarily as a means for social cohesion and communication. The implications of these results are discussed in light of theories on the origin and the functionality of music listening and also for the application of musical stimuli in all areas of psychology and for research in music cognition.

Introduction

Music listening is one of the most enigmatic of human behaviors. Most common behaviors have a recognizable utility that can be plausibly traced to the practical motives of survival and procreation. Moreover, in the array of seemingly odd behaviors, few behaviors match music for commandeering so much time, energy, and money. Music listening is one of the most popular leisure activities. Music is a ubiquitous companion to people's everyday lives.

The enthusiasm for music is not a recent development. Recognizably musical activities appear to have been present in every known culture on earth, with ancient roots extending back 250,000 years or more (see Zatorre and Peretz, 2001 ). The ubiquity and antiquity of music has inspired considerable speculation regarding its origin and function.

Throughout history, scholars of various stripes have pondered the nature of music. Philosophers, psychologists, anthropologists, musicologists, and neuroscientists have proposed a number of theories concerning the origin and purpose of music and some have pursued scientific approaches to investigating them (e.g., Fitch, 2006 ; Peretz, 2006 ; Levitin, 2007 ; Schäfer and Sedlmeier, 2010 ).

The origin of music is shrouded in prehistory. There is little physical evidence—like stone carvings or fossilized footprints—that might provide clues to music's past. Necessarily, hypotheses concerning the original functions of music will remain speculative. Nevertheless, there are a number of plausible and interesting conjectures that offer useful starting-points for investigating the functions of music.

A promising approach to the question of music's origins focuses on how music is used—that is, it's various functions. In fact, many scholars have endeavored to enumerate various musical functions (see below). The assumption is that the function(s) that music is presumed to have served in the past would be echoed in at least one of the functions that music serves today. Of course, how music is used today need have no relationship with music's function(s) in the remote past. Nevertheless, evidence from modern listeners might provide useful clues pertinent to theorizing about origins.

In proposing various musical functions, not all scholars have related these functions to music's presumed evolutionary roots. For many scholars, the motivation has been simply to identify the multiple ways in which music is used in everyday lives (e.g., Chamorro-Premuzic and Furnham, 2007 ; Boer, 2009 ; Lonsdale and North, 2011 ; Packer and Ballantyne, 2011 ). Empirical studies of musical functions have been very heterogeneous. Some studies were motivated by questions related to development. Many related to social identity. Others were motivated by cognitive psychology, aesthetics, cultural psychology, or personality psychology. In addition, studies differed according to the target population. While some studies attempted to assemble representative samples of listeners, others explicitly focused on specific populations such as adolescents. Most studies rely on convenient samples of students. Consequently, the existing literature is something of a hodgepodge.

The aim of the present study is to use the extant literature as a point of departure for a fresh re-appraisal of possible musical functions. In Part 1 of our study, we summarize the results of an extensive literature survey concerning the possible functions of music. Specifically, we identified and skimmed hundreds of publications that explicitly suggest various functions, uses, or benefits for music. We provide separate overviews for the empirical literatures and the theoretical literatures. This survey resulted in just over 500 proposed musical functions. We do not refer to each of the identified publications but concentrate on the ones that have identified either more than one single function of music listening or a single unique function that is not captured in any other publication. In Part 2, we present the results of an empirical study whose purpose was to distill—using principal components analysis (PCA)—the many proposed functions of music listening. To anticipate our results, we will see that PCA suggests three main dimensions that can account for much of the shared variance in the proposed musical functions.

Review of the research on the functions of music

Discussions and speculations regarding the functions of music listening can be found in both theoretical literature concerning music as well as in empirical studies of music. Below, we offer a review of both literatures. The contents of the reviews are summarized in Tables ​ TablesA1, A1 , ​ ,A2. A2 . Table ​ TableA1 A1 provides an overview of theoretical proposals regarding musical function, whereas Table ​ TableA2 A2 provides an overview of empirical studies regarding musical function. Together, the two tables provide a broad inventory of potential functions for music.

Theoretical approaches

Many scholars have discussed potential functions of music exclusively from a theoretical point of view. The most prominent of these approaches or theories are the ones that make explicit evolutionary claims. However, there are also other, non-evolutionary approaches such as experimental aesthetics or the uses-and-gratifications approach. Functions of music were derived deductively from these approaches and theories. In addition, in the literature, one commonly finds lists or collections of functions that music can have. Most of these lists are the result of literature searches; in other cases authors provide no clear explanation for how they came up with the functions they list. Given the aim of assembling a comprehensive list, all works are included in our summary.

Functions of music as they derive from specific approaches or theories

Evolutionary approaches. Evolutionary discussions of music can already be found in the writings of Darwin. Darwin discussed some possibilities but felt there was no satisfactory solution to music's origins (Darwin, 1871 , 1872 ). His intellectual heirs have been less cautious. Miller ( 2000 ), for instance, has argued that music making is a reasonable index of biological fitness, and so a manifestation of sexual selection—analogous to the peacock's tail. Anyone who can afford the biological luxury of making music must be strong and healthy. Thus, music would offer an honest social signal of physiological fitness.

Another line of theorizing refers to music as a means of social and emotional communication. For example, Panksepp and Bernatzky ( 2002 , p. 139) argued that

in social creatures like ourselves, whose ancestors lived in arboreal environments where sound was one of the most effective ways to coordinate cohesive group activities, reinforce social bonds, resolve animosities, and to establish stable hierarchies of submission and dominance, there could have been a premium on being able to communicate shades of emotional meaning by the melodic character (prosody) of emitted sounds.

A similar idea is that music contributes to social cohesion and thereby increases the effectiveness of group action. Work and war songs, lullabies, and national anthems have bound together families, groups, or whole nations. Relatedly, music may provide a means to reduce social stress and temper aggression in others. The idea that music may function as a social cement has many proponents (see Huron, 2001 ; Mithen, 2006 ; Bicknell, 2007 ).

A novel evolutionary theory is offered by Falk ( 2004a , b ) who has proposed that music arose from humming or singing intended to maintain infant-mother attachment. Falk's “putting-down-the-baby hypothesis” suggests that mothers would have profited from putting down their infants in order to make their hands free for other activities. Humming or singing consequently arose as a consoling signal indicating caretaker proximity in the absence of physical touch.

Another interesting conjecture relates music to human anxiety related to death, and the consequent quest for meaning. Dissanayake ( 2009 ), for example, has argued that humans have used music to help cope with awareness of life's transitoriness. In a manner similar to religious beliefs about the hereafter or a higher transcendental purpose, music can help assuage human anxiety concerning mortality (see, e.g., Newberg et al., 2001 ). Neurophysiological studies regarding music-induced chills can be interpreted as congruent with this conjecture. For example, music-induced chills produce reduced activity in brain structures associated with anxiety (Blood and Zatorre, 2001 ).

Related ideas stress the role music plays in feelings of transcendence. For example, (Frith, 1996 , p. 275) has noted that: “We all hear the music we like as something special, as something that defies the mundane, takes us “out of ourselves,” puts us somewhere else.” Thus, music may provide a means of escape. The experience of flow states (Nakamura and Csikszentmihalyi, 2009 ), peaks (Maslow, 1968 ), and chills (Panksepp, 1995 ), which are often evoked by music listening, might similarly be interpreted as forms of transcendence or escapism (see also Fachner, 2008 ).

More generally, Schubert ( 2009 ) has argued that the fundamental function of music is its potential to produce pleasure in the listener (and in the performer, as well). All other functions may be considered subordinate to music's pleasure-producing capacity. Relatedly, music might have emerged as a safe form of time-passing—analogous to the sleeping behaviors found among many predators. As humans became more effective hunters, music might have emerged merely as an entertaining and innocuous way to pass time during waking hours (see Huron, 2001 ).

The above theories each stress a single account of music's origins. In addition, there are mixed theories that posit a constellation of several concurrent functions. Anthropological accounts of music often refer to multiple social and cultural benefits arising from music. Merriam ( 1964 ) provides a seminal example. In his book, The anthropology of music , Merriam proposed 10 social functions music can serve (e.g., emotional expression, communication, and symbolic representation). Merriam's work has had a lasting influence among music scholars, but also led many scholars to focus exclusively on the social functions of music. Following in the tradition of Merriam, Dissanayake ( 2006 ) proposed six social functions of ritual music (such as display of resources, control, and channeling of individual aggression, and the facilitation of courtship).

Non-evolutionary approaches. Many scholars have steered clear of evolutionary speculation about music, and have instead focused on the ways in which people use music in their everyday lives today. A prominent approach is the “uses-and-gratifications” approach (e.g., Arnett, 1995 ). This approach focuses on the needs and concerns of the listeners and tries to explain how people actively select and use media such as music to serve these needs and concerns. Arnett ( 1995 ) provides a list of potential uses of music such as entertainment, identity formation, sensation seeking, or culture identification.

Another line of research is “experimental aesthetics” whose proponents investigate the subjective experience of beauty (both artificial or natural), and the ensuing experience of pleasure. For example, in discussing the “recent work in experimental aesthetics,” Bullough ( 1921 ) distinguished several types of listeners and pointed to the fact that music can be used to activate associations, memories, experiences, moods, and emotions.

By way of summary, many musical functions have been proposed in the research literature. Evolutionary speculations have tended to focus on single-source causes such as music as an indicator of biological fitness, music as a means for social and emotional communication, music as social glue, music as a way of facilitating caretaker mobility, music as a means of tempering anxiety about mortality, music as escapism or transcendental meaning, music as a source of pleasure, and music as a means for passing time. Other accounts have posited multiple concurrent functions such as the plethora of social and cultural functions of music found in anthropological writings about music. Non-evolutionary approaches are evident in the uses-and-gratifications approach—which revealed a large number of functions that can be summarized as cognitive, emotional, social, and physiological functions—and the experimental aesthetics approach, whose proposed functions can similarly be summarized as cognitive and emotional functions.

Functions of music as they derive from literature research

As noted, many publications posit musical functions without providing a clear connection to any theory. Most of these works are just collections of functions of music from the literature. Not least, there are also accounts of such collections where it remained unclear how the author(s) came up with the functions contained. Some of these works refer to only one single function of music—most often because this functional aspect was investigated not with the focus on music but with a focus on other psychological phenomena. Yet other works list extensive collections of purported musical functions.

Works that refer to only one single functional aspect of music include possible therapeutic functions for music in clinical settings (Cook, 1986 ; Frohne-Hagemann and Pleß-Adamczyk, 2005 ), the use of music for symbolic exclusion in political terms (Bryson, 1996 ), the syntactic, semantic, and mediatizing use of film music (Maas, 1993 ), and the use of music to manage physiological arousal (Bartlett, 1996 ).

The vast majority of publications identify several possible musical functions, most of which—as stated above—are clearly focused on social aspects. Several comprehensive collections have been assembled, such as those by Baacke ( 1984 ), Gregory ( 1997 ), Ruud ( 1997 ), Roberts and Christenson ( 2001 ), Engh ( 2006 ), and Laiho ( 2004 ). Most of these studies identified a very large number of potential functions of music.

By way of summary, there exists a long tradition of theorizing about the potential functions of music. Although some of these theories have been deduced from a prior theoretical framework, none was the result of empirical testing or exploratory data-gathering. In the ensuing section, we turn to consider empirically-oriented research regarding the number and nature of potential musical functions.

Empirical investigations

A number of studies have approached the functions of music from an empirical perspective. Two main approaches might be distinguished. In the first approach, the research aim is to uncover or document actual musical functioning. That is, the research aims to observe or identify one or more ways in which music is used in daily life. In the second approach, the research goal is to infer the structure or pattern underlying the use of music. That is, the research aims to uncover potential basic or fundamental dimensions implied by the multiple functions of music. This is mostly done using PCA or factor analyses or cluster analyses that reduce a large number of functions to only a few basic dimensions. In some cases, the analyses are run exploratively whereas in other cases, they are run in a confirmatory way, that is—with a predefined number of dimensions. The empirical studies can be categorized according to several criteria (see Table ​ TableA2). A2 ). However, when discussing some of the most important works here, we will separate studies where respondents were asked for the functions of music in open surveys from studies where the authors provided their own collections of functions, based on either literature research or face validity.

Surveys about the functions music can have

A number of studies have attempted to chronicle the broad range of musical functions. Most of these studies employed surveys in which people were asked to identify the ways in which they make use of music in their lives. In some studies, expert interviews were conducted in order to identify possible functions. Table ​ TableA2 A2 provides a summary of all the pertinent studies including their collections of functions and—where applicable—their derived underlying dimensions. We will restrict our ensuing remarks to the largest and most comprehensive studies.

Chamorro-Premuzic and Furnham ( 2007 ) identified 15 functions of music among students and subsequently ran focus groups from which they distilled three distinct dimensions: emotional use, rational use, and background use. Some of the largest surveys have been carried out by Boer ( 2009 ). She interviewed more than a thousand young people in different countries and assembled a comprehensive collection of musical functions. Using factor analysis, she found 10 underlying dimensions: emotion, friends, family, venting, background, dancing, focus, values, politic, and culture. (Lonsdale and North, 2011 , Study 1) pursued a uses-and-gratifications approach. They identified 30 musical uses that could be reduced to six distinct dimensions. In a related study employing a larger sample, the same authors came up with eight distinct dimensions: identity, positive and negative mood management, reminiscing, diversion, arousal, surveillance, and social interaction (Lonsdale and North, 2011 , Study 4). When interviewing older participants, Hays and Minichiello ( 2005 ) qualitatively identified six dimensions: linking, life events, sharing and connecting, wellbeing, therapeutic benefits, escapism, and spirituality.

The various surveys and interview studies clearly diverge with regard to the number of different musical functions. Similarly, the various cluster and factor analyses often end up producing different numbers of distinct dimensions. Nevertheless, the results are often quite similar. On a very broad level, there are four categories that appear consistently: social functions, emotional functions, cognitive or self-related functions, and physiological or arousal-related functions (see also Hargreaves and North, 1999 ; Schäfer and Sedlmeier, 2009 , 2010 ).

Empirical studies using predefined collections of functions of music

Apart from the open-ended surveys and interview methods, a number of studies investigating musical functions begin with researcher-defined collections or even categories/dimensions. Some of these predefined collections or categories/dimensions were simply borrowed from the existing published research, whereas others were derived from specific theoretical perspectives.

Empirical studies on functions of music emerging from specific theoretical approaches. Some of the above mentioned theoretical approaches to the functionality of music have been investigated in empirical studies. Boehnke and Münch ( 2003 ) developed a model of the relationship of adolescents' development, music, and media use. They proposed seven functions of music that relate to the developmental issues of young people (such as peer group integration, physical maturation, or identity development). In two studies with a large number of participants, Lonsdale and North ( 2011 ) applied the model of media gratification (from McQuail et al., 1972 ) and used a collection of 30 functions of music they assembled from literature research and interviews. In both studies, they ran factor analyses—reducing the number of functions to six dimensions and eight dimensions, respectively. Lehmann ( 1994 ) developed a situations-functions-preference model and proposed that music preferences emerge from the successful use of music to serve specific functions for the listener, depending on the current situation. Lehmann identified 68 ways in which people use music, from which he was able to reduce them to 15 music reception strategies (Rezeptionsweisen) such as compensation/escapism, relaxation, and identification. Misenhelter and Kaiser ( 2008 ) adopted Merriam's ( 1964 ) anthropological approach and attempted to identify the functions of music in the context of music education. They surveyed teachers and students and found six basic functions that were quite similar to the ones proposed by Merriam ( 1964 ). Wells and Hakanen ( 1997 ) adopted Zillmann's ( 1988a , b ) mood management theory and identified four types of users regarding the emotional functions of music: mainstream, music lover, indifferent, and heavy rockers.

Empirical studies on functions of music emerging from literature research. A number of studies have made use of predefined musical functions borrowed from the existing research literature. The significance of these functions and/or their potential underlying structure has then been empirically investigated using different samples. As mentioned, not all of those studies tried to assemble an exhaustive collection of musical functions in order to produce a comprehensive picture of the functions of music; but many studies were focused on specific aspects such as the emotional, cognitive, or social functions of music.

Schäfer and Sedlmeier ( 2009 ) collected 17 functions of music from the literature and found functions related to the management of mood and arousal as well as self-related functions to be the ones that people highly ascribe to their favorite music. Tarrant et al. ( 2000 ) used a collection of 10 functions of music from the literature and factor analyzed them resulting in three distinct dimensions of music use: self-related, emotional, and social.

Sun and Lull ( 1986 ) collected 18 functions of music videos and were able to reduce them to four dimensions: social learning, passing time, escapism/mood, and social interaction. Melton and Galician ( 1987 ) identified 15 functions of radio music and music videos; and Greasley and Lamont ( 2011 ) collected 15 functions of music, as well. Ter Bogt et al. ( 2011 ) collected 19 functions of music from the literature and used confirmatory factor analysis to group them into five dimensions. In a clinical study with adolescents, Walker Kennedy ( 2010 ) found 47 functions of music that could be reduced to five dimensions.

By way of summary, extant empirical studies have used either an open approach—trying to capture the variety of musical functions in the course of surveys or questionnaire studies—or predefined collections of functions as they resulted from specific theoretical approaches or from literature research. These different approaches have led to quite heterogeneous collections of possible musical functions—from only few functions posited by a specific hypothesis, to long lists arising from open surveys. Moreover, although the many attempts to distill the functions of music to fewer dimensions have produced some points of agreement, the overall picture remains unclear.

The structure among the functions of music

With each successive study of musical functions, the aggregate list of potential uses has grown longer. Questionnaire studies, in particular, have led to the proliferation of possible ways in which music may be relevant in people's lives. Even if one sidesteps the question of possible evolutionary origins, the multitude of hundreds of proposed functions raises the question of whether these might not be distilled to a smaller set of basic dimensions.

As noted earlier, previous research appears to converge on four dimensions: social functions (such as the expression of one's identity or personality), emotional functions (such as the induction of positive feelings), cogni tive or self-related functions (such as escapism), and arousal-related functions (such as calming down or passing time). These four dimensions might well account for the basic ways in which people use music in their daily lives.

Notice that cluster analysis and PCA/factor analysis presume that the research begins with a range of variables that ultimately capture all of the factors or dimensions pertaining to the phenomenon under consideration. The omission of even a single variable can theoretically lead to incomplete results if that variable proves to share little variance in common with the other variables. For example, in studying the factors that contribute to a person's height, the failure to include a variable related to developmental nutrition will led to deceptive results; one might wrongly conclude that only genetic factors are important. The validity of these analyses depends, in part, on including a sufficient range of variables so that all of the pertinent factors or dimensions are likely to emerge.

Accordingly, we propose to address the question of musical functions anew, starting with the most comprehensive list yet of potential music-related functions. In addition, we will aim to recruit a sample of participants covering all age groups, a wide range of socio-economic backgrounds, and pursue our analysis without biasing the materials to any specific theory.

Fundamental functions of music—a comprehensive empirical study

The large number of functions of music that research has identified during the last decades has raised the question of a potential underlying structure: Are there functions that are more fundamental and are there others that can be subsumed under the fundamental ones? And if so, how many fundamental functions are there? As we have outlined above, many scientists have been in search of basic distinct dimensions among the functions of music. They have used statistical methods that help uncover such dimensions among a large number of variables: factor analyses or cluster analyses.

However, as we have also seen, the approaches and methods have been as different as the various functions suggested. For instance, some scholars have focused exclusively on the social functions of music while others have been interested in only the emotional ones; some used only adolescent participants while others consulted only older people. Thus, these researchers arrived at different categorizations according to their particular approach. To date, there is still no conclusive categorization of the functions of music into distinct dimensions, which makes psychological studies that rely on the use of music and its effects on cognition, emotion, and behavior still difficult (see also Stefanija, 2007 ). Although there exist some theoretically driven claims about what fundamental dimensions there might be (Tarrant et al., 2000 ; Laiho, 2004 ; Schubert, 2009 ; Lonsdale and North, 2011 ), there has been no large-scale empirical study that analyzed the number and nature of distinct dimensions using the broad range of all potential musical functions—known so far—all at once.

We sought to remedy this deficiency by assembling an exhaustive list of the functions of music that have been identified in past research and putting them together in one questionnaire study. Based on the research reviewed in the first part of this study, we identified more than 500 items concerned with musical use or function. Specifically, we assembled an aggregate list of all the questions and statements encountered in the reviewed research that were either theoretically derived or used in empirical studies. Of course, many of the items are similar, analogous, or true duplicates. After eliminating or combining redundant items, we settled on a list of 129 distinct items. All of the items were phrased as statements in the form “I listen to music because … ” The complete list of items is given in Table ​ TableA3, A3 , together with their German versions as used in our study.

Participants were asked to rate how strongly they agreed with each item-statement on a scale from 0 ( not at all ) to 6 ( fully agree ). When responding to items, participants were instructed to think of any style of music and of any situation in which they would listen to music. In order to obtain a sample that was heterogeneous with regard to age and socioeconomic background, we distributed flyers promoting the Internet link to our study in a local electronics superstore. Recruitment of participants was further pursued via some mailing lists of German universities, students from comprehensive schools, and members of a local choir. As an incentive, respondents got the chance to win a tablet computer. A total of 834 people completed the survey. Respondents ranged from 8 to 85 years of age ( M = 26, SD = 10.4, 57% female).

Notice that in carrying out such a survey, we are assuming that participants have relatively accurate introspective access to their own motivations in pursuing particular musical behaviors, and that they are able to accurately recall the appropriate experiences. Of course, there exists considerable empirical research casting doubt on the accuracy of motivational introspection in self-report tasks (e.g., Wilson, 2002 ; Hirstein, 2005 ; Fine, 2006 ). These caveats notwithstanding, in light of the limited options for gathering pertinent empirical data, we nevertheless chose to pursue a survey-based approach.

Principal component analysis revealed three distinct dimensions behind the 129 items (accounting for about 40% of the variance), based on the scree plot. This solution was consistent over age groups and genders. The first dimension (eigenvalue: 15.2%) includes statements about self-related thoughts (e.g., music helps me think about myself), emotions and sentiments (e.g., music conveys feelings), absorption (e.g., music distracts my mind from the outside world), escapism (e.g., music makes me forget about reality), coping (e.g., music makes me believe I'm better able to cope with my worries), solace (e.g., music gives comfort to me when I'm sad), and meaning (e.g., music adds meaning to my life). It appears that this dimension expresses a very private relationship with music listening. Music helps people think about who they are, who they would like to be, and how to cut their own path. We suggest labeling this dimension self-awareness . The second dimension (eigenvalue: 13.7%) includes statements about social bonding and affiliation (e.g., music helps me show that I belong to a given social group; music makes me feel connected to my friends; music tells me how other people think). People can use music to feel close to their friends, to express their identity and values to others, and to gather information about their social environment. We suggest labeling this dimension social relatedness . The third dimension (eigenvalue: 10.2%) includes statements about the use of music as background entertainment and diversion (e.g., music is a great pastime; music can take my mind off things) and as a means to get into a positive mood and regulate one's physiological arousal (e.g., music can make me cheerful; music helps me relax; music makes me more alert). We suggest labeling this dimension arousal and mood regulation . All factor loadings are reported in Table ​ TableA3 A3 .

In order to analyze the relative significance of the three derived dimensions for the listeners, we averaged the ratings for all items contained in each dimension (see Figure ​ Figure1). 1 ). Arousal and mood regulation proved to be the most important dimension of music listening closely followed by self-awareness. These two dimensions appear to represent the two most potent reasons offered by people to explain why they listen to music, whereas social relatedness seems to be a relatively less important reason (ranging below the scale mean). This pattern was consistent across genders, socioeconomic backgrounds, and age groups. All differences between the three dimensions are significant (all p s < 0.001). The reliability indices (Cronbach's α) for the three dimensions are α = 0.97 for the first, α = 0.96 for the second, and α = 0.92 for the third dimension.

The three distinct dimensions emerging from 129 reasons for listening to music . Error bars are 95% confidence intervals. Self-awareness: M = 3.59 ( SE = 0.037); social relatedness: M = 2.01 ( SE = 0.035); arousal and mood regulation: M = 3.78 ( SE = 0.032).

General discussion

Since the earliest writing on the psychology of music, researchers have been concerned with the many ways in which people use music in their lives. In the first part of this paper, we reviewed literature spanning psychological, musicological, biological, and anthropological perspectives on musical function. The picture that emerged from our review was somewhat confusing. Surveying the literature from the past 50 years, we identified more than 500 purported functions for music. From this list, we assembled a somewhat catholic list of 129 non-redundant musical functions. We then tested the verisimilitude of these posited functions by collecting survey responses from a comparatively large sample. PCA revealed just three distinct dimensions: People listen to music to achieve self-awareness , social relatedness , and arousal and mood regulation . We propose calling these the Big Three of music listening.

In part one of our study we noted that several empirical studies suggest grouping musical functions according to four dimensions: cognitive, emotional, social/cultural, and physiological/arousal-related functions. This raises the question of how our three-dimensional result might be reconciled with the earlier work. We propose that there is a rather straightforward interpretation that allows the four-dimensional perspective to be understood within our three-dimensional result. Cognitive functions are captured by the first dimension (self-awareness); social/cultural functions are captured by the second dimensions (social relatedness); physiological/arousal-related functions are captured by the third dimension (arousal and mood regulation); and emotional functions are captured by the first and third dimensions (self-awareness + arousal and mood regulation). Notably—as can be seen with the items in Table ​ TableA3—there A3 —there is a dissociation of emotion-related and mood-related functions. Emotions clearly appear in the first dimension (e.g., music conveys feelings; music can lighten my mood; music helps me better understand my thoughts and emotions), indicating that they might play an important role in achieving self-awareness, probably in terms of identity formation and self-perception, respectively. However, the regulation of moods clearly appears in the third dimension (e.g., music makes me cheerful; music can enhance my mood; I'm less bored when I listen to music), suggesting that moods are not central issues pertaining to identity. Along with the maintenance of a pleasant level of physiological arousal, the maintenance of pleasant moods is an effect of music that might rather be utilized as a “background” strategy, that is, not requiring a deep or aware involvement in the music. The regulation of emotions, on the other side, could be a much more conscious strategy requiring deliberate attention and devotion to the music. Music psychology so far has not made a clear distinction between music-related moods and emotions; and the several conceptions of music-related affect remain contentious (see Hunter and Schellenberg, 2010 ). Our results appear to call for a clearer distinction between moods and emotions in music psychology research.

As noted earlier, a presumed evolutionary origin for music need not be reflected in modern responses to music. Nevertheless, it is plausible that continuities exist between modern responses and possible archaic functions. Hence, the functions apparent in our study may echo possible evolutionary functions. The three functional dimensions found in our study are compatible with nearly all of the ideas about the potential evolutionary origin of music mentioned in the introduction. The idea that music had evolved as a means for establishing and regulating social cohesion and communication is consistent with the second dimension. The idea of music satisfying the basic human concerns of anxiety avoidance and quest for meaning is consistent with the first dimension. And the notion that the basic function of music could have been to produce dissociation and pleasure in the listener is consistent with the third dimension.

In light of claims that music evolved primarily as a means for promoting social cohesion and communication—a position favored by many scholars—the results appear noteworthy. Seemingly, people today hardly listen to music for social reasons, but instead use it principally to relieve boredom, maintain a pleasant mood, and create a comfortable private space. Such a private mode of music listening might simply reflect a Western emphasis on individuality: self-acknowledgement and well-being appear to be more highly valued than social relationships and relatedness (see also Roberts and Foehr, 2008 ; Heye and Lamont, 2010 ).

The results of the present study may be of interest to psychologists who make use of music as a tool or stimulus in their research. The way people usually listen to music outside the laboratory will surely influence how they respond to musical stimuli in psychological experiments. For those researchers who make use of music in psychological studies, some attention should be paid to how music is used in everyday life. The three dimensions uncovered in this study can provide a parsimonious means to identify the value a person sets on each of three different types of music use. It is also conceivable that individual patterns of music use are related to personality traits, a conjecture which may warrant future research.

With regard to music cognition, the present results are especially relevant to studies about aesthetic preferences, style or genre preferences, and musical choice. Recent research suggests that musical functions play an important role in the formation and development of music preferences (e.g., Schäfer and Sedlmeier, 2009 ; Rentfrow et al., 2011 ). It will be one of the future tasks of music cognition research to investigate the dependence of music preference and music choice on the functional use of music in people's lives.

By way of summary, in a self-report study, we found that people appear to listen to music for three major reasons, two of which are substantially more important than the third: music offers a valued companion, helps provide a comfortable level of activation and a positive mood, whereas its social importance may have been overvalued.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Overview of theoretical contributions that have derived, proposed, or addressed more than one function or functional aspect of music listening .

Overview about empirical studies that have identified and/or investigated more than one function or functional aspect of music listening .

In some places, we could only provide exemplary functions because either the total number of functions was too large to be displayed here or not all functions were given in the original publications .

The 129 statements referring to the functions of music exhaustively derived from past research, together with their means, standard deviations, and factor loadings (varimax rotated) .

Dimension 1, self-awareness; Dimension 2, social relatedness; Dimension 3, arousal and mood regulation .

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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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• Review Article
• Published: 29 March 2022

Music in the brain

• Peter Vuust   ORCID: orcid.org/0000-0002-4908-735X 1 ,
• Ole A. Heggli   ORCID: orcid.org/0000-0002-7461-0309 1 ,
• Karl J. Friston   ORCID: orcid.org/0000-0001-7984-8909 2 &
• Morten L. Kringelbach   ORCID: orcid.org/0000-0002-3908-6898 1 , 3 , 4  

Nature Reviews Neuroscience volume  23 ,  pages 287–305 ( 2022 ) Cite this article

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• Neuroscience

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

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Acknowledgements

Funding was provided by The Danish National Research Foundation (DNRF117). The authors thank E. Altenmüller and D. Huron for comments on early versions of the manuscript.

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Peter Vuust, Ole A. Heggli & Morten L. Kringelbach

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Patterns of pitched sounds unfolding over time, in accordance with cultural conventions and constraints.

The combination of multiple, simultaneously pitched sounds to form a chord, and subsequent chord progressions, a fundamental building block of Western music. The rules of harmony are the hierarchically organized expectations for chord progressions.

The structured arrangement of successive sound events over time, a primary parameter of musical structure. Rhythm perception is based on the perception of duration and grouping of these events and can be achieved even if sounds are not discrete, such as amplitude-modulated sounds.

Mathematically, the expected values or means of random variables.

The ability to extract statistical regularities from the world to learn about the environment.

In Western music, the organization of melody and harmony in a hierarchy of relations, often pointing towards a referential pitch (the tonal centre or the tonic).

A predictive framework governing the interpretation of regularly recurring patterns and accents in rhythm.

The output of a model generating outcomes from their causes. In predictive coding, the prediction is generated from expected states of the world and compared with observed outcomes to form a prediction error.

The subjective experience accompanying a strong expectation that a particular event will occur.

An enactive generalization of predictive coding that casts both action and perception as minimizing surprise or prediction error (active inference is considered a corollary of the free-energy principle).

A quantity used in predictive coding to denote the difference between an observation or point estimate and its predicted value. Predictive coding uses precision-weighted prediction errors to update expectations that generate predictions.

Expectations of musical events based on prior knowledge of regularities and patterns in musical sequences, such as melodies and chords.

Expectations of specific events or patterns in a familiar musical sequence.

Short-lived expectations that dynamically shift owing to the ongoing musical context, such as when a repeated musical phrase causes the listener to expect similar phrases as the work continues.

The inverse variance or negative entropy of a random variable. It corresponds to a second-order statistic (for example, a second-order moment) of the variable’s probability distribution or density. This can be contrasted with the mean or expectation, which constitutes a first-order statistic (for example, a first-order moment).

(MMN). A component of the auditory event-related potential recorded with electroencephalography or magnetoencephalography related to a change in different sound features such as pitch, timbre, location of the sound source, intensity and rhythm. It peaks approximately 110–250 ms after change onset and is typically recorded while participants’ attention is distracted from the stimulus, usually by watching a silent film or reading a book. The amplitude and latency of the MMN depends on the deviation magnitude, such that larger deviations in the same context yield larger and faster MMN responses.

(fMRI). A neuroimaging technique that images rapid changes in blood oxygenation levels in the brain.

In the realm of contemporary music, a persistently repeated pattern played by the rhythm section (usually drums, percussion, bass, guitar and/or piano). In music psychology, the pleasurable sensation of wanting to move.

The perceptual correlate of periodicity in sounds that allows their ordering on a frequency-related musical scale.

Also known as tone colour or tone quality, the perceived sound quality of a sound, including its spectral composition and its additional noise characteristics.

The pitch class containing all pitches separated by an integer number of octaves. Humans perceive a similarity between notes having the same chroma.

The contextual unexpectedness or surprise associated with an event.

In the Shannon sense, the expected surprise or information content (self-information). In other words, it is the uncertainty or unpredictability of a random variable (for example, an event in the future).

(MEG). A neuroimaging technique that measures the magnetic fields produced by naturally occurring electrical activity in the brain.

A very small electrical voltage generated in the brain structures in response to specific events or stimuli.

Psychologically, consonance is when two or more notes sound together with an absence of perceived roughness. Dissonance is the antonym of consonance. Western listeners consider intervals produced by frequency ratios such as 1:2 (octave), 3:2 (fifth) or 4:3 (fourth) as consonant. Dissonances are intervals produced by frequency ratios formed from numbers greater than 4.

Stereotypical patterns consisting of two or more chords that conclude a phrase, section or piece of music. They are often used to establish a sense of tonality.

(EEG). An electrophysiological method that measures electrical activity of the brain.

A method of analysing steady-state evoked potentials arising from stimulation or aspects of stimulation repeated at a fixed rate. An example of frequency tagging analysis is shown in Fig.  1c .

A shift of rhythmic emphasis from metrically strong accents to weak accents, a characteristic of multiple musical genres, such as funk, jazz and hip hop.

In Aristotelian ethics, refers to a life well lived or human flourishing, and in affective neuroscience, it is often used to describe meaningful pleasure.

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Vuust, P., Heggli, O.A., Friston, K.J. et al. Music in the brain. Nat Rev Neurosci 23 , 287–305 (2022). https://doi.org/10.1038/s41583-022-00578-5

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Published : 29 March 2022

Issue Date : May 2022

DOI : https://doi.org/10.1038/s41583-022-00578-5

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