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How to Design a Music and Personality Experiment

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

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

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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Psychology of Music

Research in the Psychology of Music uses psychological theories and methods to interpret and understand musical sounds, musical behaviours, and the effects of music. The subject is strongly inter-disciplinary, and generally combines empirical data collection, through observation, experiments, surveys or otherwise, with theoretical innovation. The scope of research in Sheffield ranges from fundamental questions related to music perception and cognition to applications of music psychology in everyday life. The breadth of research is reflected in its three main research units – Music, Mind, Machine in Sheffield, Music & Wellbeing, and Sheffield Performer & Audience Research Centre.

The University of Sheffield has the longest established and biggest grouping of music psychology expertise in the UK. In any single year we have around 12 research students working on psychology of music or music education projects, over 30 students on our three taught MA programmes, and a number of research assistants and post-doctoral scholars. We have strong links with the Department of Psychology and other cognate departments, through joint supervision of postgraduate and undergraduate research projects, and through research collaborations between staff.

Psychology of Music is an active research area and has seen considerable growth in the UK in recent years. Sheffield is an important contributor to the area both at a national and international level through research networks and collaborations, participation in and organisation of international conferences and events, contributions to the international research literature, and by educating music psychologists who come from across the world. These connections benefit staff and students and ensure that research and teaching are conducted at the highest internationally competitive level.

I think one of the best things about studying music psychology at the University of Sheffield is feeling surrounded by a community of lecturers and fellow students who are passionate about this topic. This sense of community, along with the specialised facilities to carry out my research, always made me feel that my research interests and initiatives were supported, and they made my time as a PhD student not only academically productive, but very enjoyable. Julian Cespedes PhD researcher

Examples of funded research projects

• Music in the workplace (AHRC)
• Teaching and learning of expressive music performance (AHRC)
• Music perception in hearing impaired listeners (WRoCAH)
• Dropping in and dropping out – exploring experiences of lapsed and partial arts engagement (AHRC)
• Earworms (tunes that stick in our heads) as we age (British Academy)
• Demystifying music review (Swiss National Science Foundation)
• Music to support sleep (Experimental Psychological Society)
• Space and embodiment in headphone listening (WRoCAH)
• Cross-modal perception of music (British Academy)
• Expressive nonverbal communication in ensemble performance (WRoCAH Network)

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Music psychology in education, performance and wellbeing ma.

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Explore fundamental questions about music and its central place in our lives on the longest established music psychology programme in the UK. Our interdisciplinary approach offers a unique perspective on music and rigorous training in research techniques.

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Become part of our community of talented postgraduate students. Join us at our online open day on Wednesday 27 November 2024 .

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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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Zatorre, R. J., Chen, J. L. & Penhune, V. B. When the brain plays music: auditory–motor interactions in music perception and production. Nat. Rev. Neurosci. 8 , 547–558 (2007). A seminal review of auditory–motor coupling in music .

Article   CAS   PubMed   Google Scholar  

Koelsch, S. Toward a neural basis of music perception–a review and updated model. Front. Psychol. 2 , 110 (2011).

Article   PubMed   PubMed Central   Google Scholar  

Maes, P. J., Leman, M., Palmer, C. & Wanderley, M. M. Action-based effects on music perception. Front. Psychol. 4 , 1008 (2014).

Koelsch, S. Brain correlates of music-evoked emotions. Nat. Rev. Neurosci. 15 , 170–180 (2014). In this review, the author shows how music engages phylogenetically old reward networks in the brain to evoke emotions, and not merely subjective feelings .

Vuust, P. & Witek, M. A. Rhythmic complexity and predictive coding: a novel approach to modeling rhythm and meter perception in music. Front. Psychol. 5 , 1111 (2014).

Friston, K. The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. 11 , 127–138 (2010). This review posits that several global brain theories may be unified by the free-energy principle .

Koelsch, S., Vuust, P. & Friston, K. Predictive processes and the peculiar case of music. Trends Cogn. Sci. 23 , 63–77 (2019). This review focuses specifically on predictive coding in music .

Article   PubMed   Google Scholar  

Meyer, L. Emotion and Meaning in Music (Univ. of Chicago Press, 1956).

Lerdahl, F. & Jackendoff, R. A Generative Theory of Music (MIT Press, 1999).

Huron, D. Sweet Anticipation (MIT Press, 2006). In this book, Huron draws on evolutionary theory and statistical learning to propose a general theory of musical expectation .

Hansen, N. C. & Pearce, M. T. Predictive uncertainty in auditory sequence processing. Front. Psychol. https://doi.org/10.3389/fpsyg.2013.01008 (2014).

Vuust, P., Brattico, E., Seppanen, M., Naatanen, R. & Tervaniemi, M. The sound of music: differentiating musicians using a fast, musical multi-feature mismatch negativity paradigm. Neuropsychologia 50 , 1432–1443 (2012).

Altenmüller, E. O. How many music centers are in the brain? Ann. N. Y. Acad. Sci. 930 , 273–280 (2001).

Monelle, R. Linguistics and Semiotics in Music (Harwood Academic Publishers, 1992).

Rohrmeier, M. A. & Koelsch, S. Predictive information processing in music cognition. A critical review. Int. J. Psychophysiol. 83 , 164–175 (2012).

Vuust, P., Dietz, M. J., Witek, M. & Kringelbach, M. L. Now you hear it: a predictive coding model for understanding rhythmic incongruity. Ann. N. Y. Acad. Sci. https://doi.org/10.1111/nyas.13622 (2018).

Vuust, P., Ostergaard, L., Pallesen, K. J., Bailey, C. & Roepstorff, A. Predictive coding of music–brain responses to rhythmic incongruity. Cortex 45 , 80–92 (2009).

Vuust, P. & Frith, C. Anticipation is the key to understanding music and the effects of music on emotion. Behav. Brain Res. 31 , 599–600 (2008). This is the foundation for the PCM model used in this Review .

Google Scholar  

Garrido, M. I., Sahani, M. & Dolan, R. J. Outlier responses reflect sensitivity to statistical structure in the human brain. PLoS Comput. Biol. 9 , e1002999 (2013).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Lumaca, M., Baggio, G., Brattico, E., Haumann, N. T. & Vuust, P. From random to regular: neural constraints on the emergence of isochronous rhythm during cultural transmission. Soc. Cogn. Affect. Neurosci. 13 , 877–888 (2018).

Quiroga-Martinez, D. R. et al. Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians. Eur. J. Neurosci. https://doi.org/10.1111/ejn.14667 (2019).

Article   Google Scholar  

Koelsch, S., Schröger, E. & Gunter, T. C. Music matters: preattentive musicality of the human brain. Psychophysiology 39 , 38–48 (2002).

Koelsch, S., Schmidt, B.-h & Kansok, J. Effects of musical expertise on the early right anterior negativity: an event-related brain potential study. Psychophysiology 39 , 657–663 (2002).

Lumaca, M., Dietz, M. J., Hansen, N. C., Quiroga-Martinez, D. R. & Vuust, P. Perceptual learning of tone patterns changes the effective connectivity between Heschl’s gyrus and planum temporale. Hum. Brain Mapp. 42 , 941–952 (2020).

Lieder, F., Daunizeau, J., Garrido, M. I., Friston, K. J. & Stephan, K. E. Modelling trial-by-trial changes in the mismatch negativity. PLoS Comput. Biol. 9 , e1002911 (2013).

Wacongne, C., Changeux, J. P. & Dehaene, S. A neuronal model of predictive coding accounting for the mismatch negativity. J. Neurosci. 32 , 3665–3678 (2012).

Kiebel, S. J., Garrido, M. I. & Friston, K. J. Dynamic causal modelling of evoked responses: the role of intrinsic connections. Neuroimage 36 , 332–345 (2007).

Feldman, H. & Friston, K. J. Attention, uncertainty, and free-energy. Front. Hum. Neurosci. 4 , 215 (2010).

Cheung, V. K. M. et al. Uncertainty and surprise jointly predict musical pleasure and amygdala, hippocampus, and auditory cortex activity. Curr. Biol. 29 , 4084–4092 e4084 (2019). This fMRI study ties uncertainty and surprise to musical pleasure .

McDermott, J. H. & Oxenham, A. J. Music perception, pitch, and the auditory system. Curr. Opin. Neurobiol. 18 , 452–463 (2008).

Thoret, E., Caramiaux, B., Depalle, P. & McAdams, S. Learning metrics on spectrotemporal modulations reveals the perception of musical instrument timbre. Nat. Hum. Behav. 5 , 369–377 (2020).

Siedenburg, K. & McAdams, S. Four distinctions for the auditory “wastebasket” of timbre. Front. Psychol. 8 , 1747 (2017).

Bendor, D. & Wang, X. The neuronal representation of pitch in primate auditory cortex. Nature 436 , 1161–1165 (2005).

Zatorre, R. J. Pitch perception of complex tones and human temporal-lobe function. J. Acoustical Soc. Am. 84 , 566–572 (1988).

Article   CAS   Google Scholar  

Warren, J. D., Uppenkamp, S., Patterson, R. D. & Griffiths, T. D. Separating pitch chroma and pitch height in the human brain. Proc. Natl Acad. Sci. USA 100 , 10038–10042 (2003). Using fMRI data, this study shows that pitch chroma is represented anterior to the primary auditory cortex, and pitch height is represented posterior to the primary auditory cortex .

Rauschecker, J. P. & Scott, S. K. Maps and streams in the auditory cortex: nonhuman primates illuminate human speech processing. Nat. Neurosci. 12 , 718–724 (2009).

Leaver, A. M., Van Lare, J., Zielinski, B., Halpern, A. R. & Rauschecker, J. P. Brain activation during anticipation of sound sequences. J. Neurosci. 29 , 2477–2485 (2009).

Houde, J. F. & Chang, E. F. The cortical computations underlying feedback control in vocal production. Curr. Opin. Neurobiol. 33 , 174–181 (2015).

Lee, Y. S., Janata, P., Frost, C., Hanke, M. & Granger, R. Investigation of melodic contour processing in the brain using multivariate pattern-based fMRI. Neuroimage 57 , 293–300 (2011).

Janata, P. et al. The cortical topography of tonal structures underlying Western music. Science 298 , 2167–2170 (2002).

Saffran, J. R., Aslin, R. N. & Newport, E. L. Statistical learning by 8-month-old infants. Science 274 , 1926–1928 (1996).

Saffran, J. R., Johnson, E. K., Aslin, R. N. & Newport, E. L. Statistical learning of tone sequences by human infants and adults. Cognition 70 , 27–52 (1999).

Krumhansl, C. L. Perceptual structures for tonal music. Music. Percept. 1 , 28–62 (1983).

Margulis, E. H. A model of melodic expectation. Music. Percept. 22 , 663–714 (2005).

Temperley, D. A probabilistic model of melody perception. Cogn. Sci. 32 , 418–444 (2008).

Pearce, M. T. & Wiggins, G. A. Auditory expectation: the information dynamics of music perception and cognition. Top. Cogn. Sci. 4 , 625–652 (2012).

Sears, D. R. W., Pearce, M. T., Caplin, W. E. & McAdams, S. Simulating melodic and harmonic expectations for tonal cadences using probabilistic models. J. N. Music. Res. 47 , 29–52 (2018).

Näätänen, R., Gaillard, A. W. & Mäntysalo, S. Early selective-attention effect on evoked potential reinterpreted. Acta Psychol. 42 , 313–329 (1978).

Näätänen, R., Paavilainen, P., Rinne, T. & Alho, K. The mismatch negativity (MMN) in basic research of central auditory processing: a review. Clin. Neurophysiol. 118 , 2544–2590 (2007). This classic review covers three decades of MMN research to understand auditory perception .

Wallentin, M., Nielsen, A. H., Friis-Olivarius, M., Vuust, C. & Vuust, P. The Musical Ear Test, a new reliable test for measuring musical competence. Learn. Individ. Differ. 20 , 188–196 (2010).

Tervaniemi, M. et al. Top-down modulation of auditory processing: effects of sound context, musical expertise and attentional focus. Eur. J. Neurosci. 30 , 1636–1642 (2009).

Burunat, I. et al. The reliability of continuous brain responses during naturalistic listening to music. Neuroimage 124 , 224–231 (2016).

Burunat, I. et al. Action in perception: prominent visuo-motor functional symmetry in musicians during music listening. PLoS ONE 10 , e0138238 (2015).

Article   PubMed   PubMed Central   CAS   Google Scholar  

Alluri, V. et al. Large-scale brain networks emerge from dynamic processing of musical timbre, key and rhythm. Neuroimage 59 , 3677–3689 (2012). A free-listening fMRI study showing brain networks involved in perception of distinct acoustical features of music .

Halpern, A. R. & Zatorre, R. J. When that tune runs through your head: a PET investigation of auditory imagery for familiar melodies. Cereb. Cortex 9 , 697–704 (1999).

Herholz, S. C., Halpern, A. R. & Zatorre, R. J. Neuronal correlates of perception, imagery, and memory for familiar tunes. J. Cogn. Neurosci. 24 , 1382–1397 (2012).

Pallesen, K. J. et al. Emotion processing of major, minor, and dissonant chords: a functional magnetic resonance imaging study. Ann. N. Y. Acad. Sci. 1060 , 450–453 (2005).

McPherson, M. J. et al. Perceptual fusion of musical notes by native Amazonians suggests universal representations of musical intervals. Nat. Commun. 11 , 2786 (2020).

Helmholtz H. L. F. On the Sensations of Tone as a Physiological Basis for the Theory of Music (Cambridge Univ. Press, 1954).

Vassilakis, P. N. & Kendall, R. A. in Human Vision and Electronic Imaging XV . 75270O (International Society for Optics and Photonics, 2010).

Plomp, R. & Levelt, W. J. M. Tonal consonance and critical bandwidth. J. Acoustical Soc. Am. 38 , 548–560 (1965).

McDermott, J. H., Schultz, A. F., Undurraga, E. A. & Godoy, R. A. Indifference to dissonance in native Amazonians reveals cultural variation in music perception. Nature 535 , 547–550 (2016). An ethnomusicology study showing that consonance preference may be absent in people with minimal exposure to Western music .

Mehr, S. A. et al. Universality and diversity in human song. Science https://doi.org/10.1126/science.aax0868 (2019).

Patel, A. D., Gibson, E., Ratner, J., Besson, M. & Holcomb, P. J. Processing syntactic relations in language and music: an event-related potential study. J. Cogn. Neurosci. 10 , 717–733 (1998). This classic study compares responses to syntactic incongruities in both language and Western tonal music .

Janata, P. The neural architecture of music-evoked autobiographical memories. Cereb. Cortex 19 , 2579–2594 (2009).

Maess, B., Koelsch, S., Gunter, T. C. & Friederici, A. D. Musical syntax is processed in Broca’s area: an MEG study. Nat. Neurosci. 4 , 540–545 (2001).

Koelsch, S. et al. Differentiating ERAN and MMN: an ERP study. Neuroreport 12 , 1385–1389 (2001). Using EEG, the authors show that ERAN and MMN reflect different cognitive mechanisms .

Loui, P., Grent-‘t-Jong, T., Torpey, D. & Woldorff, M. Effects of attention on the neural processing of harmonic syntax in Western music. Cogn. Brain Res. 25 , 678–687 (2005).

Koelsch, S., Fritz, T., Schulze, K., Alsop, D. & Schlaug, G. Adults and children processing music: an fMRI study. Neuroimage 25 , 1068–1076 (2005).

Tillmann, B., Janata, P. & Bharucha, J. J. Activation of the inferior frontal cortex in musical priming. Ann. N. Y. Acad. Sci. 999 , 209–211 (2003).

Garza-Villarreal, E. A., Brattico, E., Leino, S., Ostergaard, L. & Vuust, P. Distinct neural responses to chord violations: a multiple source analysis study. Brain Res. 1389 , 103–114 (2011).

Leino, S., Brattico, E., Tervaniemi, M. & Vuust, P. Representation of harmony rules in the human brain: further evidence from event-related potentials. Brain Res. 1142 , 169–177 (2007).

Sammler, D. et al. Co-localizing linguistic and musical syntax with intracranial EEG. Neuroimage 64 , 134–146 (2013).

Loui, P., Wessel, D. L. & Hudson Kam, C. L. Humans rapidly learn grammatical structure in a new musical scale. Music. Percept. 27 , 377–388 (2010).

Loui, P., Wu, E. H., Wessel, D. L. & Knight, R. T. A generalized mechanism for perception of pitch patterns. J. Neurosci. 29 , 454–459 (2009).

Cheung, V. K. M., Meyer, L., Friederici, A. D. & Koelsch, S. The right inferior frontal gyrus processes nested non-local dependencies in music. Sci. Rep. 8 , 3822 (2018).

Haueisen, J. & Knosche, T. R. Involuntary motor activity in pianists evoked by music perception. J. Cogn. Neurosci. 13 , 786–792 (2001).

Bangert, M. et al. Shared networks for auditory and motor processing in professional pianists: evidence from fMRI conjunction. Neuroimage 30 , 917–926 (2006).

Baumann, S. et al. A network for audio-motor coordination in skilled pianists and non-musicians. Brain Res. 1161 , 65–78 (2007).

Lahav, A., Saltzman, E. & Schlaug, G. Action representation of sound: audiomotor recognition network while listening to newly acquired actions. J. Neurosci. 27 , 308–314 (2007).

Bianco, R. et al. Neural networks for harmonic structure in music perception and action. Neuroimage 142 , 454–464 (2016).

Eerola, T., Vuoskoski, J. K., Peltola, H.-R., Putkinen, V. & Schäfer, K. An integrative review of the enjoyment of sadness associated with music. Phys. Life Rev. 25 , 100–121 (2018).

Huron, D. M. D. The harmonic minor scale provides an optimum way of reducing average melodic interval size, consistent with sad affect cues. Empir. Musicol. Rev. 7 , 15 (2012).

Huron, D. A comparison of average pitch height and interval size in major-and minor-key themes: evidence consistent with affect-related pitch prosody. 3 , 59-63 (2008).

Juslin, P. N. & Laukka, P. Communication of emotions in vocal expression and music performance: different channels, same code? Psychol. Bull. 129 , 770 (2003).

Fritz, T. et al. Universal recognition of three basic emotions in music. Curr. Biol. 19 , 573–576 (2009).

London, J. Hearing in Time: Psychological Aspects of Musical Meter (Oxford Univ. Press, 2012).

Honing, H. Without it no music: beat induction as a fundamental musical trait. Ann. N. Y. Acad. Sci. 1252 , 85–91 (2012).

Hickok, G., Farahbod, H. & Saberi, K. The rhythm of perception: entrainment to acoustic rhythms induces subsequent perceptual oscillation. Psychol. Sci. 26 , 1006–1013 (2015).

Yabe, H., Tervaniemi, M., Reinikainen, K. & Näätänen, R. Temporal window of integration revealed by MMN to sound omission. Neuroreport 8 , 1971–1974 (1997).

Andreou, L.-V., Griffiths, T. D. & Chait, M. Sensitivity to the temporal structure of rapid sound sequences — an MEG study. Neuroimage 110 , 194–204 (2015).

Jongsma, M. L., Meeuwissen, E., Vos, P. G. & Maes, R. Rhythm perception: speeding up or slowing down affects different subcomponents of the ERP P3 complex. Biol. Psychol. 75 , 219–228 (2007).

Graber, E. & Fujioka, T. Endogenous expectations for sequence continuation after auditory beat accelerations and decelerations revealed by P3a and induced beta-band responses. Neuroscience 413 , 11–21 (2019).

Brochard, R., Abecasis, D., Potter, D., Ragot, R. & Drake, C. The “ticktock” of our internal clock: direct brain evidence of subjective accents in isochronous sequences. Psychol. Sci. 14 , 362–366 (2003).

Lerdahl, F. & Jackendoff, R. An overview of hierarchical structure in music. Music. Percept. 1 , 229–252 (1983).

Large, E. W. & Kolen, J. F. Resonance and the perception of musical meter. Connect. Sci. 6 , 177–208 (1994).

Large, E. W. & Jones, M. R. The dynamics of attending: how people track time-varying events. Psychol. Rev. 106 , 119–159 (1999).

Cutietta, R. A. & Booth, G. D. The influence of metre, mode, interval type and contour in repeated melodic free-recall. Psychol. Music 24 , 222–236 (1996).

Smith, K. C. & Cuddy, L. L. Effects of metric and harmonic rhythm on the detection of pitch alterations in melodic sequences. J. Exp. Psychol. 15 , 457–471 (1989).

CAS   Google Scholar  

Palmer, C. & Krumhansl, C. L. Mental representations for musical meter. J. Exp. Psychol. 16 , 728–741 (1990).

Einarson, K. M. & Trainor, L. J. Hearing the beat: young children’s perceptual sensitivity to beat alignment varies according to metric structure. Music. Percept. 34 , 56–70 (2016).

Large, E. W., Herrera, J. A. & Velasco, M. J. Neural networks for beat perception in musical rhythm. Front. Syst. Neurosci. 9 , 159 (2015).

Nozaradan, S., Peretz, I., Missal, M. & Mouraux, A. Tagging the neuronal entrainment to beat and meter. J. Neurosci. 31 , 10234–10240 (2011).

Nozaradan, S., Peretz, I. & Mouraux, A. Selective neuronal entrainment to the beat and meter embedded in a musical rhythm. J. Neurosci. 32 , 17572–17581 (2012).

Nozaradan, S., Schonwiesner, M., Keller, P. E., Lenc, T. & Lehmann, A. Neural bases of rhythmic entrainment in humans: critical transformation between cortical and lower-level representations of auditory rhythm. Eur. J. Neurosci. 47 , 321–332 (2018).

Lenc, T., Keller, P. E., Varlet, M. & Nozaradan, S. Neural and behavioral evidence for frequency-selective context effects in rhythm processing in humans. Cereb. Cortex Commun. https://doi.org/10.1093/texcom/tgaa037 (2020).

Jacoby, N. & McDermott, J. H. Integer ratio priors on musical rhythm revealed cross-culturally by iterated reproduction. Curr. Biol. 27 , 359–370 (2017).

Hannon, E. E. & Trehub, S. E. Metrical categories in infancy and adulthood. Psychol. Sci. 16 , 48–55 (2005).

Hannon, E. E. & Trehub, S. E. Tuning in to musical rhythms: infants learn more readily than adults. Proc. Natl Acad. Sci. USA 102 , 12639–12643 (2005).

Vuust, P. et al. To musicians, the message is in the meter pre-attentive neuronal responses to incongruent rhythm are left-lateralized in musicians. Neuroimage 24 , 560–564 (2005).

Grahn, J. A. & Brett, M. Rhythm and beat perception in motor areas of the brain. J. Cogn. Neurosci. 19 , 893–906 (2007). This fMRI study investigates participants listening to rhythms of varied complexity .

Toiviainen, P., Burunat, I., Brattico, E., Vuust, P. & Alluri, V. The chronnectome of musical beat. Neuroimage 216 , 116191 (2019).

Chen, J. L., Penhune, V. B. & Zatorre, R. J. Moving on time: brain network for auditory-motor synchronization is modulated by rhythm complexity and musical training. J. Cogn. Neurosci. 20 , 226–239 (2008).

Levitin, D. J., Grahn, J. A. & London, J. The psychology of music: rhythm and movement. Annu. Rev. Psychol. 69 , 51–75 (2018).

Winkler, I., Haden, G. P., Ladinig, O., Sziller, I. & Honing, H. Newborn infants detect the beat in music. Proc. Natl Acad. Sci. USA 106 , 2468–2471 (2009).

Phillips-Silver, J. & Trainor, L. J. Feeling the beat: movement influences infant rhythm perception. Science 308 , 1430–1430 (2005).

Cirelli, L. K., Trehub, S. E. & Trainor, L. J. Rhythm and melody as social signals for infants. Ann. N. Y. Acad. Sci. https://doi.org/10.1111/nyas.13580 (2018).

Cirelli, L. K., Einarson, K. M. & Trainor, L. J. Interpersonal synchrony increases prosocial behavior in infants. Dev. Sci. 17 , 1003–1011 (2014).

Repp, B. H. Sensorimotor synchronization: a review of the tapping literature. Psychon. Bull. Rev. 12 , 969–992 (2005).

Repp, B. H. & Su, Y. H. Sensorimotor synchronization: a review of recent research (2006-2012). Psychon. Bull. Rev. 20 , 403–452 (2013). This review, and Repp (2005), succinctly covers the field of sensorimotor synchronization .

Zarco, W., Merchant, H., Prado, L. & Mendez, J. C. Subsecond timing in primates: comparison of interval production between human subjects and rhesus monkeys. J. Neurophysiol. 102 , 3191–3202 (2009).

Honing, H., Bouwer, F. L., Prado, L. & Merchant, H. Rhesus monkeys ( Macaca mulatta ) sense isochrony in rhythm, but not the beat: additional support for the gradual audiomotor evolution hypothesis. Front. Neurosci. 12 , 475 (2018).

Hattori, Y. & Tomonaga, M. Rhythmic swaying induced by sound in chimpanzees (Pan troglodytes). Proc. Natl Acad. Sci. USA 117 , 936–942 (2020).

Danielsen, A. Presence and Pleasure. The Funk Grooves of James Brown and Parliament (Wesleyan Univ. Press, 2006).

Madison, G., Gouyon, F., Ullen, F. & Hornstrom, K. Modeling the tendency for music to induce movement in humans: first correlations with low-level audio descriptors across music genres. J. Exp. Psychol. Hum. Percept. Perform. 37 , 1578–1594 (2011).

Stupacher, J., Hove, M. J., Novembre, G., Schutz-Bosbach, S. & Keller, P. E. Musical groove modulates motor cortex excitability: a TMS investigation. Brain Cogn. 82 , 127–136 (2013).

Janata, P., Tomic, S. T. & Haberman, J. M. Sensorimotor coupling in music and the psychology of the groove. J. Exp. Psychol. 141 , 54 (2012). Using a systematic approach, this multiple-studies article shows that the concept of groove can be widely understood as a pleasurable drive towards action .

Witek, M. A. et al. A critical cross-cultural study of sensorimotor and groove responses to syncopation among Ghanaian and American university students and staff. Music. Percept. 37 , 278–297 (2020).

Friston, K., Mattout, J. & Kilner, J. Action understanding and active inference. Biol. Cybern. 104 , 137–160 (2011).

Longuet-Higgins, H. C. & Lee, C. S. The rhythmic interpretation of monophonic music. Music. Percept. 1 , 18 (1984).

Sioros, G., Miron, M., Davies, M., Gouyon, F. & Madison, G. Syncopation creates the sensation of groove in synthesized music examples. Front. Psychol. 5 , 1036 (2014).

Witek, M. A., Clarke, E. F., Wallentin, M., Kringelbach, M. L. & Vuust, P. Syncopation, body-movement and pleasure in groove music. PLoS ONE 9 , e94446 (2014).

Kowalewski, D. A., Kratzer, T. M. & Friedman, R. S. Social music: investigating the link between personal liking and perceived groove. Music. Percept. 37 , 339–346 (2020).

Bowling, D. L., Ancochea, P. G., Hove, M. J. & Tecumseh Fitch, W. Pupillometry of groove: evidence for noradrenergic arousal in the link between music and movement. Front. Neurosci. 13 , 1039 (2019).

Matthews, T. E., Witek, M. A. G., Heggli, O. A., Penhune, V. B. & Vuust, P. The sensation of groove is affected by the interaction of rhythmic and harmonic complexity. PLoS ONE 14 , e0204539 (2019).

Matthews, T. E., Witek, M. A., Lund, T., Vuust, P. & Penhune, V. B. The sensation of groove engages motor and reward networks. Neuroimage 214 , 116768 (2020). This fMRI study shows that the sensation of groove engages both motor and reward networks in the brain .

Vaquero, L., Ramos-Escobar, N., François, C., Penhune, V. & Rodríguez-Fornells, A. White-matter structural connectivity predicts short-term melody and rhythm learning in non-musicians. Neuroimage 181 , 252–262 (2018).

Zatorre, R. J., Halpern, A. R., Perry, D. W., Meyer, E. & Evans, A. C. Hearing in the mind’s ear: a PET investigation of musical imagery and perception. J. Cogn. Neurosci. 8 , 29–46 (1996).

Benadon, F. Meter isn’t everything: the case of a timeline-oriented Cuban polyrhythm. N. Ideas Psychol. 56 , 100735 (2020).

London, J., Polak, R. & Jacoby, N. Rhythm histograms and musical meter: a corpus study of Malian percussion music. Psychon. Bull. Rev. 24 , 474–480 (2017).

Huron, D. Is music an evolutionary adaptation? Ann. N. Y. Acad. Sci. 930 , 43–61 (2001).

Koelsch, S. Towards a neural basis of music-evoked emotions. Trends Cogn. Sci. 14 , 131–137 (2010).

Eerola, T. & Vuoskoski, J. K. A comparison of the discrete and dimensional models of emotion in music. Psychol. Music. 39 , 18–49 (2010).

Lonsdale, A. J. & North, A. C. Why do we listen to music? A uses and gratifications analysis. Br. J. Psychol. 102 , 108–134 (2011).

Juslin, P. N. & Laukka, P. Expression, perception, and induction of musical emotions: a review and a questionnaire study of everyday listening. J. N. Music. Res. 33 , 217–238 (2004).

Huron, D. Why is sad music pleasurable? A possible role for prolactin. Music. Sci. 15 , 146–158 (2011).

Brattico, E. et al. It’s sad but I like it: the neural dissociation between musical emotions and liking in experts and laypersons. Front. Hum. Neurosci. 9 , 676 (2015).

PubMed   Google Scholar  

Sachs, M. E., Damasio, A. & Habibi, A. Unique personality profiles predict when and why sad music is enjoyed. Psychol. Music https://doi.org/10.1177/0305735620932660 (2020).

Sachs, M. E., Habibi, A., Damasio, A. & Kaplan, J. T. Dynamic intersubject neural synchronization reflects affective responses to sad music. Neuroimage 218 , 116512 (2020).

Juslin, P. N. & Vastfjall, D. Emotional responses to music: the need to consider underlying mechanisms. Behav. Brain Sci. 31 , 559–575 (2008). Using a novel theoretical framework, the authors propose that the mechanisms that evoke emotions from music are not unique to music .

Rickard, N. S. Intense emotional responses to music: a test of the physiological arousal hypothesis. Psychol. Music. 32 , 371–388 (2004).

Cowen, A. S., Fang, X., Sauter, D. & Keltner, D. What music makes us feel: at least 13 dimensions organize subjective experiences associated with music across different cultures. Proc. Natl Acad. Sci. USA 117 , 1924–1934 (2020).

Argstatter, H. Perception of basic emotions in music: culture-specific or multicultural? Psychol. Music. 44 , 674–690 (2016).

Stevens, C. J. Music perception and cognition: a review of recent cross-cultural research. Top. Cogn. Sci. 4 , 653–667 (2012).

Pearce, M. Cultural distance: a computational approach to exploring cultural influences on music cognition. in Oxford Handbook of Music and the Brain Vol. 31 (Oxford Univ. Press, 2018).

van der Weij, B., Pearce, M. T. & Honing, H. A probabilistic model of meter perception: simulating enculturation. Front. Psychol. 8 , 824 (2017).

Kringelbach, M. L. & Berridge, K. C. Towards a functional neuroanatomy of pleasure and happiness. Trends Cogn. Sci. 13 , 479–487 (2009).

Blood, A. J. & Zatorre, R. J. Intensely pleasurable responses to music correlate with activity in brain regions implicated in reward and emotion. Proc. Natl Acad. Sci. USA 98 , 11818–11823 (2001). This seminal positron emission tomography study shows that the experience of musical chills correlates with activity in the reward system .

Salimpoor, V. N. & Zatorre, R. J. Complex cognitive functions underlie aesthetic emotions: comment on “From everyday emotions to aesthetic emotions: towards a unified theory of musical emotions” by Patrik N. Juslin. Phys. Life Rev. 10 , 279–280 (2013).

Salimpoor, V. N. et al. Interactions between the nucleus accumbens and auditory cortices predict music reward value. Science 340 , 216–219 (2013).

Salimpoor, V. N., Benovoy, M., Larcher, K., Dagher, A. & Zatorre, R. J. Anatomically distinct dopamine release during anticipation and experience of peak emotion to music. Nat. Neurosci. 14 , 257–262 (2011).

Salimpoor, V. N., Benovoy, M., Longo, G., Cooperstock, J. R. & Zatorre, R. J. The rewarding aspects of music listening are related to degree of emotional arousal. PLoS ONE 4 , e7487 (2009).

Mas-Herrero, E., Zatorre, R. J., Rodriguez-Fornells, A. & Marco-Pallares, J. Dissociation between musical and monetary reward responses in specific musical anhedonia. Curr. Biol. 24 , 699–704 (2014).

Martinez-Molina, N., Mas-Herrero, E., Rodriguez-Fornells, A., Zatorre, R. J. & Marco-Pallares, J. Neural correlates of specific musical anhedonia. Proc. Natl Acad. Sci. USA 113 , E7337–E7345 (2016).

Gebauer, L. K., M., L. & Vuust, P. Musical pleasure cycles: the role of anticipation and dopamine. Psychomusicology 22 , 16 (2012).

Shany, O. et al. Surprise-related activation in the nucleus accumbens interacts with music-induced pleasantness. Soc. Cogn. Affect. Neurosci. 14 , 459–470 (2019).

Gold, B. P., Pearce, M. T., Mas-Herrero, E., Dagher, A. & Zatorre, R. J. Predictability and uncertainty in the pleasure of music: a reward for learning? J. Neurosci. 39 , 9397–9409 (2019).

Swaminathan, S. & Schellenberg, E. G. Current emotion research in music psychology. Emot. Rev. 7 , 189–197 (2015).

Madison, G. & Schiölde, G. Repeated listening increases the liking for music regardless of its complexity: implications for the appreciation and aesthetics of music. Front. Neurosci. 11 , 147 (2017).

Corrigall, K. A. & Schellenberg, E. G. Liking music: genres, contextual factors, and individual differences. in Art, Aesthetics, and the Brain (Oxford Univ. Press, 2015).

Zentner, A. Measuring the effect of file sharing on music purchases. J. Law Econ. 49 , 63–90 (2006).

Rentfrow, P. J. & Gosling, S. D. The do re mi’s of everyday life: the structure and personality correlates of music preferences. J. Pers. Soc. Psychol. 84 , 1236–1256 (2003).

Vuust, P. et al. Personality influences career choice: sensation seeking in professional musicians. Music. Educ. Res. 12 , 219–230 (2010).

Rohrmeier, M. & Rebuschat, P. Implicit learning and acquisition of music. Top. Cogn. Sci. 4 , 525–553 (2012).

Münthe, T. F., Altenmüller, E. & Jäncke, L. The musician’s brain as a model of neuroplasticity. Nat. Rev. Neurosci. 3 , 1–6 (2002). This review highlights how professional musicians represent an ideal model for investigating neuroplasticity .

Habibi, A. et al. Childhood music training induces change in micro and macroscopic brain structure: results from a longitudinal study. Cereb. Cortex 28 , 4336–4347 (2018).

Schlaug, G., Jancke, L., Huang, Y., Staiger, J. F. & Steinmetz, H. Increased corpus callosum size in musicians. Neuropsychologia 33 , 1047–1055 (1995).

Baer, L. H. et al. Regional cerebellar volumes are related to early musical training and finger tapping performance. Neuroimage 109 , 130–139 (2015).

Kleber, B. et al. Voxel-based morphometry in opera singers: increased gray-matter volume in right somatosensory and auditory cortices. Neuroimage 133 , 477–483 (2016).

Gaser, C. & Schlaug, G. Brain structures differ between musicians and non-musicians. J. Neurosci. 23 , 9240–9245 (2003). Using a morphometric technique, this study shows a grey matter volume difference in multiple brain regions between professional musicians and a matched control group of amateur musicians and non-musicians .

Sluming, V. et al. Voxel-based morphometry reveals increased gray matter density in Broca’s area in male symphony orchestra musicians. Neuroimage 17 , 1613–1622 (2002).

Palomar-García, M.-Á., Zatorre, R. J., Ventura-Campos, N., Bueichekú, E. & Ávila, C. Modulation of functional connectivity in auditory–motor networks in musicians compared with nonmusicians. Cereb. Cortex 27 , 2768–2778 (2017).

Schneider, P. et al. Morphology of Heschl’s gyrus reflects enhanced activation in the auditory cortex of musicians. Nat. Neurosci. 5 , 688–694 (2002).

Bengtsson, S. L. et al. Extensive piano practicing has regionally specific effects on white matter development. Nat. Neurosci. 8 , 1148–1150 (2005).

Zamorano, A. M., Cifre, I., Montoya, P., Riquelme, I. & Kleber, B. Insula-based networks in professional musicians: evidence for increased functional connectivity during resting state fMRI. Hum. Brain Mapp. 38 , 4834–4849 (2017).

Kraus, N. & Chandrasekaran, B. Music training for the development of auditory skills. Nat. Rev. Neurosci. 11 , 599–605 (2010).

Koelsch, S., Schröger, E. & Tervaniemi, M. Superior pre-attentive auditory processing in musicians. Neuroreport 10 , 1309–1313 (1999).

Münte, T. F., Kohlmetz, C., Nager, W. & Altenmüller, E. Superior auditory spatial tuning in conductors. Nature 409 , 580 (2001).

Seppänen, M., Brattico, E. & Tervaniemi, M. Practice strategies of musicians modulate neural processing and the learning of sound-patterns. Neurobiol. Learn. Mem. 87 , 236–247 (2007).

Guillot, A. et al. Functional neuroanatomical networks associated with expertise in motor imagery. Neuroimage 41 , 1471–1483 (2008).

Bianco, R., Novembre, G., Keller, P. E., Villringer, A. & Sammler, D. Musical genre-dependent behavioural and EEG signatures of action planning. a comparison between classical and jazz pianists. Neuroimage 169 , 383–394 (2018).

Vuust, P., Brattico, E., Seppänen, M., Näätänen, R. & Tervaniemi, M. Practiced musical style shapes auditory skills. Ann. N. Y. Acad. Sci. 1252 , 139–146 (2012).

Bangert, M. & Altenmüller, E. O. Mapping perception to action in piano practice: a longitudinal DC-EEG study. BMC Neurosci. 4 , 26 (2003).

Li, Q. et al. Musical training induces functional and structural auditory-motor network plasticity in young adults. Hum. Brain Mapp. 39 , 2098–2110 (2018).

Herholz, S. C., Coffey, E. B. J., Pantev, C. & Zatorre, R. J. Dissociation of neural networks for predisposition and for training-related plasticity in auditory-motor learning. Cereb. Cortex 26 , 3125–3134 (2016).

Putkinen, V., Tervaniemi, M. & Huotilainen, M. Musical playschool activities are linked to faster auditory development during preschool-age: a longitudinal ERP study. Sci. Rep. 9 , 11310–11310 (2019).

Putkinen, V., Tervaniemi, M., Saarikivi, K., Ojala, P. & Huotilainen, M. Enhanced development of auditory change detection in musically trained school-aged children: a longitudinal event-related potential study. Dev. Sci. 17 , 282–297 (2014).

Jentschke, S. & Koelsch, S. Musical training modulates the development of syntax processing in children. Neuroimage 47 , 735–744 (2009).

Chobert, J., François, C., Velay, J. L. & Besson, M. Twelve months of active musical training in 8-to 10-year-old children enhances the preattentive processing of syllabic duration and voice onset time. Cereb. Cortex 24 , 956–967 (2014).

Moreno, S. et al. Musical training influences linguistic abilities in 8-year-old children: more evidence for brain plasticity. Cereb. Cortex 19 , 712–723 (2009).

Putkinen, V., Huotilainen, M. & Tervaniemi, M. Neural encoding of pitch direction is enhanced in musically trained children and is related to reading skills. Front. Psychol. 10 , 1475 (2019).

Wong, P. C., Skoe, E., Russo, N. M., Dees, T. & Kraus, N. Musical experience shapes human brainstem encoding of linguistic pitch patterns. Nat. Neurosci. 10 , 420–422 (2007).

Virtala, P. & Partanen, E. Can very early music interventions promote at-risk infants’ development? Ann. N. Y. Acad. Sci. 1423 , 92–101 (2018).

Flaugnacco, E. et al. Music training increases phonological awareness and reading skills in developmental dyslexia: a randomized control trial. PLoS ONE 10 , e0138715 (2015).

Fiveash, A. et al. A stimulus-brain coupling analysis of regular and irregular rhythms in adults with dyslexia and controls. Brain Cogn. 140 , 105531 (2020).

Schellenberg, E. G. Correlation = causation? music training, psychology, and neuroscience. Psychol. Aesthet. Creat. Arts 14 , 475–480 (2019).

Sala, G. & Gobet, F. Cognitive and academic benefits of music training with children: a multilevel meta-analysis. Mem. Cogn. 48 , 1429–1441 (2020).

Saffran, J. R. Musical learning and language development. Ann. N. Y. Acad. Sci. 999 , 397–401 (2003).

Friston, K. The free-energy principle: a rough guide to the brain? Trends Cogn. Sci. 13 , 293–301 (2009).

Pearce, M. T. Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation. Ann. N. Y. Acad. Sci. 1423 , 378–395 (2018).

Article   PubMed Central   Google Scholar  

Novembre, G., Knoblich, G., Dunne, L. & Keller, P. E. Interpersonal synchrony enhanced through 20 Hz phase-coupled dual brain stimulation. Soc. Cogn. Affect. Neurosci. 12 , 662–670 (2017).

Konvalinka, I. et al. Frontal alpha oscillations distinguish leaders from followers: multivariate decoding of mutually interacting brains. Neuroimage 94C , 79–88 (2014).

Novembre, G., Mitsopoulos, Z. & Keller, P. E. Empathic perspective taking promotes interpersonal coordination through music. Sci. Rep. 9 , 12255 (2019).

Wolpert, D. M., Ghahramani, Z. & Jordan, M. I. An internal model for sensorimotor integration. Science 269 , 1880–1882 (1995).

Patel, A. D. & Iversen, J. R. The evolutionary neuroscience of musical beat perception: the action simulation for auditory prediction (ASAP) hypothesis. Front. Syst. Neurosci. 8 , 57 (2014).

Sebanz, N. & Knoblich, G. Prediction in joint action: what, when, and where. Top. Cogn. Sci. 1 , 353–367 (2009).

Friston, K. J. & Frith, C. D. Active inference, communication and hermeneutics. Cortex 68 , 129–143 (2015). This article proposes a link between active inference, communication and hermeneutics .

Konvalinka, I., Vuust, P., Roepstorff, A. & Frith, C. D. Follow you, follow me: continuous mutual prediction and adaptation in joint tapping. Q. J. Exp. Psychol. 63 , 2220–2230 (2010).

Wing, A. M. & Kristofferson, A. B. Response delays and the timing of discrete motor responses. Percept. Psychophys. 14 , 5–12 (1973).

Repp, B. H. & Keller, P. E. Sensorimotor synchronization with adaptively timed sequences. Hum. Mov. Sci. 27 , 423–456 (2008).

Vorberg, D. & Schulze, H.-H. Linear phase-correction in synchronization: predictions, parameter estimation, and simulations. J. Math. Psychol. 46 , 56–87 (2002).

Novembre, G., Sammler, D. & Keller, P. E. Neural alpha oscillations index the balance between self-other integration and segregation in real-time joint action. Neuropsychologia 89 , 414–425 (2016). Using dual-EEG, the authors propose alpha oscillations as a candidate for regulating the balance between internal and external information in joint action .

Keller, P. E., Knoblich, G. & Repp, B. H. Pianists duet better when they play with themselves: on the possible role of action simulation in synchronization. Conscious. Cogn. 16 , 102–111 (2007).

Fairhurst, M. T., Janata, P. & Keller, P. E. Leading the follower: an fMRI investigation of dynamic cooperativity and leader-follower strategies in synchronization with an adaptive virtual partner. Neuroimage 84 , 688–697 (2014).

Heggli, O. A., Konvalinka, I., Kringelbach, M. L. & Vuust, P. Musical interaction is influenced by underlying predictive models and musical expertise. Sci. Rep. 9 , 1–13 (2019).

Heggli, O. A., Cabral, J., Konvalinka, I., Vuust, P. & Kringelbach, M. L. A Kuramoto model of self-other integration across interpersonal synchronization strategies. PLoS Comput. Biol. 15 , e1007422 (2019).

Heggli, O. A. et al. Transient brain networks underlying interpersonal strategies during synchronized action. Soc. Cogn. Affect. Neurosci. 16 , 19–30 (2020). This EEG study shows that differences in interpersonal synchronization are reflected by activity in a temporoparietal network .

Patel, A. D. Music, Language, and the Brain (Oxford Univ. Press, 2006).

Molnar-Szakacs, I. & Overy, K. Music and mirror neurons: from motion to ‘e’motion. Soc. Cogn. Affect. Neurosci. 1 , 235–241 (2006).

Beaty, R. E., Benedek, M., Silvia, P. J. & Schacter, D. L. Creative cognition and brain network dynamics. Trends Cogn. Sci. 20 , 87–95 (2016).

Limb, C. J. & Braun, A. R. Neural substrates of spontaneous musical performance: an FMRI study of jazz improvisation. PLoS ONE 3 , e1679 (2008).

Liu, S. et al. Neural correlates of lyrical improvisation: an FMRI study of freestyle rap. Sci. Rep. 2 , 834 (2012).

Rosen, D. S. et al. Dual-process contributions to creativity in jazz improvisations: an SPM-EEG study. Neuroimage 213 , 116632 (2020).

Boasen, J., Takeshita, Y., Kuriki, S. & Yokosawa, K. Spectral-spatial differentiation of brain activity during mental imagery of improvisational music performance using MEG. Front. Hum. Neurosci. 12 , 156 (2018).

Berkowitz, A. L. & Ansari, D. Generation of novel motor sequences: the neural correlates of musical improvisation. Neuroimage 41 , 535–543 (2008).

Loui, P. Rapid and flexible creativity in musical improvisation: review and a model. Ann. N. Y. Acad. Sci. 1423 , 138–145 (2018).

Beaty, R. E. The neuroscience of musical improvisation. Neurosci. Biobehav. Rev. 51 , 108–117 (2015).

Vuust, P. & Kringelbach, M. L. Music improvisation: a challenge for empirical research. in Routledge Companion to Music Cognition (Routledge, 2017).

Norgaard, M. Descriptions of improvisational thinking by artist-level jazz musicians. J. Res. Music. Educ. 59 , 109–127 (2011).

Kringelbach, M. L. & Deco, G. Brain states and transitions: insights from computational neuroscience. Cell Rep. 32 , 108128 (2020).

Deco, G. & Kringelbach, M. L. Hierarchy of information processing in the brain: a novel ‘intrinsic ignition’ framework. Neuron 94 , 961–968 (2017).

Pinho, A. L., de Manzano, O., Fransson, P., Eriksson, H. & Ullen, F. Connecting to create: expertise in musical improvisation is associated with increased functional connectivity between premotor and prefrontal areas. J. Neurosci. 34 , 6156–6163 (2014).

Pinho, A. L., Ullen, F., Castelo-Branco, M., Fransson, P. & de Manzano, O. Addressing a paradox: dual strategies for creative performance in introspective and extrospective networks. Cereb. Cortex 26 , 3052–3063 (2016).

de Manzano, O. & Ullen, F. Activation and connectivity patterns of the presupplementary and dorsal premotor areas during free improvisation of melodies and rhythms. Neuroimage 63 , 272–280 (2012).

Beaty, R. E. et al. Robust prediction of individual creative ability from brain functional connectivity. Proc. Natl Acad. Sci. USA 115 , 1087–1092 (2018).

Daikoku, T. Entropy, uncertainty, and the depth of implicit knowledge on musical creativity: computational study of improvisation in melody and rhythm. Front. Comput. Neurosci. 12 , 97 (2018).

Belden, A. et al. Improvising at rest: differentiating jazz and classical music training with resting state functional connectivity. Neuroimage 207 , 116384 (2020).

Arkin, C., Przysinda, E., Pfeifer, C. W., Zeng, T. & Loui, P. Gray matter correlates of creativity in musical improvisation. Front. Hum. Neurosci. 13 , 169 (2019).

Bashwiner, D. M., Wertz, C. J., Flores, R. A. & Jung, R. E. Musical creativity “revealed” in brain structure: interplay between motor, default mode, and limbic networks. Sci. Rep. 6 , 20482 (2016).

Przysinda, E., Zeng, T., Maves, K., Arkin, C. & Loui, P. Jazz musicians reveal role of expectancy in human creativity. Brain Cogn. 119 , 45–53 (2017).

Large, E. W., Kim, J. C., Flaig, N. K., Bharucha, J. J. & Krumhansl, C. L. A neurodynamic account of musical tonality. Music. Percept. 33 , 319–331 (2016).

Large, E. W. & Palmer, C. Perceiving temporal regularity in music. Cogn. Sci. 26 , 1–37 (2002). This article proposes an oscillator-based approach for the perception of temporal regularity in music .

Cannon, J. J. & Patel, A. D. How beat perception co-opts motor neurophysiology. Trends Cogn. Sci. 25 , 137–150 (2020). The authors propose that cyclic time-keeping activity in the supplementary motor area, termed ‘proto-actions’, is organized by the dorsal striatum to support hierarchical metrical structures .

Keller, P. E., Novembre, G. & Loehr, J. Musical ensemble performance: representing self, other and joint action outcomes. in Shared Representations: Sensorimotor Foundations of Social Life Cambridge Social Neuroscience (eds Cross, E. S. & Obhi, S. S.) 280-310 (Cambridge Univ. Press, 2016).

Rao, R. P. & Ballard, D. H. Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nat. Neurosci. 2 , 79–87 (1999).

Clark, A. Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behav. Brain Sci. 36 , 181–204 (2013).

Kahl, R. Selected Writings of Hermann Helmholtz (Wesleyan Univ. Press, 1878).

Gregory, R. L. Perceptions as hypotheses. Philos. Trans. R. Soc. Lond. B Biol. Sci. 290 , 181–197 (1980).

Gibson, J. J. The Ecological Approach to Visual Perception (Houghton Mifflin, 1979).

Fuster, J. The Prefrontal Cortex Anatomy, Physiology and Neuropsychology of the Frontal Lobe (Lippincott-Raven, 1997).

Neisser, U. Cognition and Reality: Principles and Implications of Cognitive Psychology (W H Freeman/Times Books/ Henry Holt & Co, 1976).

Arbib, M. A. & Hesse, M. B. The Construction of Reality (Cambridge Univ. Press, 1986).

Cisek, P. & Kalaska, J. F. Neural mechanisms for interacting with a world full of action choices. Annu. Rev. Neurosci. 33 , 269–298 (2010).

Isomura, T., Parr, T. & Friston, K. Bayesian filtering with multiple internal models: toward a theory of social intelligence. Neural Comput. 31 , 2390–2431 (2019).

Friston, K. & Frith, C. A duet for one. Conscious. Cogn. 36 , 390–405 (2015).

Hunt, B. R., Ott, E. & Yorke, J. A. Differentiable generalized synchronization of chaos. Phys. Rev. E 55 , 4029–4034 (1997).

Ghazanfar, A. A. & Takahashi, D. Y. The evolution of speech: vision, rhythm, cooperation. Trends Cogn. Sci. 18 , 543–553 (2014).

Wilson, M. & Wilson, T. P. An oscillator model of the timing of turn-taking. Psychon. Bull. Rev. 12 , 957–968 (2005).

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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

Wellcome Centre for Human Neuroimaging, University College London, London, UK

Karl J. Friston

Department of Psychiatry, University of Oxford, Oxford, UK

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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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8 Experiments

• Published: March 2021
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Chapter 8 of Performing Music Research examines the experiment as a means of assessing new ideas and initiatives, producing evidence that can support crucial developments in the lives and education of musicians. It outlines several key types of experiment, defined by how people are divided into groups, what those groups do, and how those groups are compared; it also considers how experimental strategies can be used to examine changes in an individual over a period of time. The chapter discusses guidelines for the effective design and conduct of experiments. Finally, it describes how to document the method and how to achieve rigor and validity in experimental research.

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