The evolution of music: how our understanding of music’s origins in group bonding may benefit us in our age of loneliness

We are told we are entering the “age of loneliness” (Monbiot, 2014). This term is utilised here to describe our apparent human social decline, caused by a combination of factors including the breakdown of communities, our ever-increasing population and most recently, the rise of social media. Huge numbers of people are reporting that they feel lonely, both young and old, with the negative effects of loneliness on our health becoming upsettingly clear (Perry, 2015).

Scientists have shown links between an absence of social relationships and deterioration in mental and physical health (Lim & Young, 2006), with recent studies suggesting that social isolation may have an impact comparable to the effects of high blood pressure, obesity and smoking (Cacioppo & Patrick, 2008). Public awareness is increasing too, as reflected in the Christmas 2015 advertising campaign led by John Lewis and Age UK, which highlighted elderly loneliness with the slogan: “show someone that they are loved this Christmas”.

John Lewis

A still from the 2015 John Lewis & Age UK Christmas Advertising Campaign. Watch the advert here.

Given the effect of loneliness on our health and wellbeing, it is important for us to understand the most effective ways to combat it. Increasing our ability for ‘social bonding’ is key, which is our perceived sense of closeness or connectedness to others. It has been well documented that the ability of music can impact positively on our subjective well-being (Denora, 2015; Hodges & Sebald, 2011; Sacks, 2010). It now appears that musical activity and in particular group singing may provide an effective solution to loneliness. To understand why, we look to the work of Dr Jacques Launay, a Postdoctoral Researcher at the University of Oxford, whose work aims to create a model comprising of research into the many aspects of music as an evolutionary tool for facilitating social bonding.

In contrast to other evolutionary theories of music, such as music and sexual selection (Miller, 2000), or music as a by-product of existing evolved traits such as language development (Honing & Ploeger, 2012; Patel, 2008; Pinker, 1997), Dr Jacques Launay suggests that music developed into an evolved ‘technology’ for social bonding. Launay points to experimental evidence that many facets of group music making, including shared attention and synchronisation, combined together are powerful tools for social bonding. In evolutionary terms, our ability to bond with others holds clear benefits in mutual cooperation, and may have been particularly important as we evolved from living in smaller groups to larger complex societies (Richerson & Boyd, 2001).


Social bonding in action with Popchoir

Research has shown that engaging in exertive rhythmic activities, such as musical interaction through synchronised movements releases endorphins: hormones associated with social behaviour, demonstrated in laughter and synchronised sports. Endorphin release encourages social bonding, a feeling of connectivity, and positive affect – all factors that are important for health and happiness in humans. Self-other merging through synchronising dance moves with others also functions as a mechanism that encourages social bonding (Tarr et al., 2014).

Group singing, in particular, has shown to enhance social closeness. In Pearce’s (2015) study with singing, craft and creative writing groups, all activities increased the closeness that individuals felt to ‘strangers’ within their group. Interestingly, the singing group established much quicker social bonds than the non-singing activities, suggesting that singing works as an ‘ice-breaker effect’. Weinstein and colleagues (2015) focused on social bonding within choirs, indicating that larger choirs achieved greater group closeness with one another compared to smaller choirs. These findings suggest that communal singing in larger groups causes greater social closeness, as singing may bypass the need for personal knowledge concerning other individuals, which would be required in more intimate relationships. This research supports evolutionary ideas of music in establishing social bonds, and that evidently the larger the group size the larger the social network was for survival, hence why group bonding scales up (Dunbar, 2003).


The ice-breaker effect

However, achieving social bonding is not as simple as merely singing and dancing together. Although classified as ‘low-level components’, research has shown that the interaction of joint attention, shared goals and success – all involved in music making – are particularly important (Wolf et al., 2015). As shared intentions create common psychological ground, as well as enabling collaborative activities and cooperative communication (Tomasello & Carpenter 2007).

Overall, research has been suggestive in showing music facilitating social bonding. However, the exact mechanisms behind which aspects of singing encourage group bonding, and in particular, faster group bonding in the ‘ice-breaker effect’ are not yet known. In the ice-breaker study, the singing activities shared a common goal of creating a musical piece together, whereas the craft and creative writing activities worked on individual projects. Therefore, shared success, attention and goals need to be explored to understand their effects on how quickly social bonding occurs in different activities. Also, the synchronicity and the somewhat exertive behaviour of the singing group differed greatly from the other activities, thus, activities that also incorporate these behaviours should be compared (Pearce et al., 2015).


Shared goals and shared intentions impact positively on social bonding

Though it is a compelling proposition, given the multi-faceted nature of Dr Jacques Launay’s theory of music’s evolution for social bonding, the experimental evidence to support its many aspects is currently limited. Despite this, much of the supporting research highlights the benefits of music for social bonding and this, in turn, can be used to raise public awareness, fund charity work and guide future implementation into health applications.

We may have entered the age of loneliness, but such research in music psychology may provide an avenue to escape it. Breaking the ice through group singing with shared attention, goals and success with others can provide a means to improve our social bonds.

As with many other activities that can benefit closeness, including sports and dance (Mueller, Agamanolis & Picard, 2003), what is key to Launay’s research is that the origins of group music making may mean singing helps create bonds much quicker than other activities. This is a promising step in the research field and if one were to create a perfect tool for social bonding, music might be it.

If you or someone you know is suffering from loneliness, then it may be worth investigating what opportunities exist locally for group singing. There is a growing culture of community choirs and charities – including the Popchoir featured in some of Launay’s research, and the National Association of Choirs.

Blog by Saoirse Finn, Marie Raae, Thomas Baker

This blog was written following Dr Jacques Launay’s presentation to Goldsmiths’ Music, Mind and Brain students on 6th December 2015 as part of the ‘Invited Speaker’ series.

For more details on the Music, Mind and Brain MSc, please visit:



Cacioppo, J. T., & Patrick, W. (2008). Loneliness: Human nature and the need for social connection. WW Norton & Company.

DeNora, T. (2015). Music Asylums: Wellbeing through music in everyday life. Ashgate Publishing, Ltd..

Dunbar, R. I. (2003). The origin and subsequent evolution of language. In: M. H. Christiansen & S. Kirby (Eds.), Language Evolution (pp. 219–234). Oxford, UK: Oxford University Press.

Hodges, D. A., & Sebald, D. C. (2011). Music in the human experience: An introduction to music psychology (pp. 178-190). New York: Routledge.

Honing, H., & Ploeger, A. (2012). Cognition and the evolution of music: Pitfalls and prospects. Topics in cognitive science, 4(4), 513-524.

Lim, M. M., & Young, L. J. (2006). Neuropeptidergic regulation of affiliative behavior and social bonding in animals. Hormones and behavior, 50(4), 506-517.

Miller, G. F. (2000). Evolution of human music through sexual selection. In Wallin, N. L., & Merker, B. (2001). The origins of music. MIT press.

Monbiot, G. (2014). The age of loneliness is killing us. 14 October 2014.

Mueller, F., Agamanolis, S., & Picard, R. (2003). Exertion interfaces: sports over a distance for social bonding and fun. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 561-568). ACM.

Patel, A.D. (2008). Music, Language, and the Brain. NY: Oxford Univ. Press.

Pearce, E., Launay, J., & Dunbar, R. I. (2015). The ice-breaker effect: singing mediates fast social bonding. Royal Society open science2(10), 150221.

Perry, P. (2015). Loneliness is dangerous: ignore it at your peril.

Pinker, S. (1997). How the Mind Works. London: Allen Lane.

Richerson, P. J., & Boyd, R. (2001). Institutional evolution in the Holocene: the rise of complex societies. In Proceedings – British Academy (Vol. 110, pp. 197-234). Oxford University Press Inc.

Sacks, O. (2010). Musicophilia: Tales of music and the brain. Vintage Canada.

Tarr, B., Launay, J., & Dunbar, R. I. (2014). Music and social bonding:“self-other” merging and neurohormonal mechanisms. Frontiers in psychology5.

Tomasello, M., & Carpenter, M. (2007). Shared intentionality. Developmental science10(1), 121-125.

Weinstein, D., Launay, J., Pearce, E., Dunbar, R. I., & Stewart, L. (2015). Singing and social bonding: changes in connectivity and pain threshold as a function of group size. Evolution and Human Behavior.

Wolf, W., Launay, J., & Dunbar, R. I. (2015). Joint attention, shared goals, and social bonding. British Journal of Psychology.

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Ritchie,S. (2015). Intelligence: All that matters. London: John Murray Learning.

IntelligenceSurely, being a full-time academic in a psychology department I shouldn’t be reading a teeny-tiny book on intelligence like this 115-page introduction. Instead you would think that I was  equipped to take on one of the many massive and excellent textbooks that are out there on the topic. But I’ve discovered that reading short books can generate a different kind of satisfaction (you can pat yourself on the back if you finish it within a week!) that thick books can hardly provide, especially if the short one is as well-written and entertaining as this little book by Stuart Ritchie.

What I was hoping to get out of it when I ordered the book for Goldsmiths Library was a quick overview of the current state of the debate on some of the thorny issues that surround the psychological construct of intelligence and questions of how to test for it. For example, how strong is the evidence for the general intelligence factor (‘very strong’), how heritable is intelligence (‘about 50% heritability’), what does the genetic basis of intelligence look like (‘it is polygenic, i.e. at least several hundreds of genes can contribute it’), what are the brain correlates of intelligence (‘strong connections between frontal and parietal parts of the brain’), is there any effective training to increase your intelligence (‘for a while it looked like  working memory training with n-back tasks would make you generally smarter but the initial findings don’t seem to replicate well’) or how many different tests does a comprehensive test battery need to include (not really answered). Of course you could get these answers from individual research or review papers or indeed form the big textbooks but you would have to wade through a lot of pages to find these answers. Naturally, there is a danger that a very short book leaves out a lot of the complexity and controversy of the actual scientific discourse and over-simplifies matters, just to make a neat story fit into 115 pages.

But Stuart Ritchie does not make this mistake. I think this is one of the greatest strengths of this short book: that it provides answers to all those interesting questions around intelligence based on the scientific evidence currently available, but at the same time he also tells the reader how certain or shaky the current evidence is – whether we are talking about results that have been replicated dozens of times (e.g. brain volume correlates with intelligence positively but the correlation is very small) or whether evidence is only building up currently or could be confounded by other factors (e.g. potential positive link between breast-feeding and intelligence).

Obviously, given the size of the book, Ritchie had to compromise somehow and he does so by not even attempting to give exhaustive views on any of the questions. Instead he uses the results of only one or two studies to demonstrate research findings in an exemplary way. Therefore, many of the chapters read like cliff-hangers where you really want to know the full story now. But that is good and probably the best effect that Ritchie could have hoped to achieve.

In this respect the final section of the book ‘100 idea to help you explore intelligence more’ is truly effective. The section doesn’t just contain lists of important papers,  textbooks and living as well as dead intelligence researchers, but also gives links to a list of very active research websites as well as for example fictional characters known for high v. low intelligence (e.g. ‘Marvin the robot from Hitchhiker’s Guide to the Galaxy v. ‘Homer Simpson’). Finally, the list that took me completely, was the ’surprising things that correlate with higher intelligence’ which lists facebook-liking of the 70s gangster drama The Godfather, where I felt very much vindicated for all these long hours in front of the screen. Now, who said intelligence research didn’t matter?

Daniel Müllensiefen
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Book Review: Beaujean, A.A. (2014). Latent Variable Modeling Using R. Hove: Routledge.

LaVaMo_RThis is one of the many stats books I’ve been ordering for the Goldsmiths Library lately (and, boy, I really love ordering new stats books for the library!). Just beware, there are more review of advanced stats books to come over future weeks….

What is R?

This one is an introduction to latent variable modelling and makes use of the R package lavaan which stands for LAtent VAriable ANalysis.  In case you haven’t  heard of it yet, R is a software environment / language / program that is free and open source and offers thousands of packages for all the different types of statistical analysis that anyone could ever think of. The only downside of R over other software programs that psychologists commonly use, is that you can’t get your analysis done by clicking and pointing on a graphical user interface like you would do with SPSS for example. Instead, in R you need to type commands to get anything done, and of course it takes a little while to learn those commands and understand what they are doing. But once you get over this initial hurdle the reward is that the complete world of contemporary statistical analysis procedures is open and free to you and you’ll never have to face that shock again when your software license runs out at the end of July and you haven’t finished your project yet.

Anyway, in R there are several packages for latent variable analysis (or structural equation modelling which is another name for it), but lavaan seems to be the most popular one at the moment. This is probably because it is quite flexible in terms of what kind of data you can analyse with it but much less complicated to use than an alternative package, openMX which is ultra-flexible regarding analysis options and favoured by, for example, the behavioural genetics community but also has a very steep learning curve, even after you think you’ve mastered R.

What is Latent Variable Modelling? 

To be honest, Beaujean’s book isn’t a psychology book per se but latent variable models are of truly high importance to psychologists.  Why is this? Because almost by definition, most questions that psychologists are interested in, involve things we can’t really observe directly with our senses. I’m referring to thinks like intelligence (see below) autism, personality traits, musicality, cognitive deficits, happiness ….. But, even though you can’t observe intelligence or autism directly you might be able to infer from their behaviour whether someone is autistic or not or whether they’re high or low on intelligence. If you are really clever, and dedicated to the question, you might even develop a test or a diagnostic battery which helps you gather observations and data to make inference about the latent construct (intelligence, autism ….) that you are actually interested in. And these are the latent variables that latent variable analysis is all about. So, if we were honest we would have to acknowledge that most models in psychology are actually latent variable models.

Beaujean’s text  
Broadly speaking, Beaujean’s book serves two purposes: First of all, it introduces the main concepts and variants of latent variable analysis (including path analysis, factor analysis, structural equation modelling, latent growth curves, item response models, hierarchical latent models) that you are most likely want to use at some point if you are a working in psychology or educational research. But secondly, after introducing each type of model in very concise terms, Beaujean also shows you how to perform the corresponding statistical analysis using the commands from the lavaan package.

The amazing thing about the book is how clearly it is written both in terms of explaining advanced statistics and in terms of teaching you how to run those analyses yourself. This clarity in writing and its educational mission to really empower the reader to construct their own latent variable models, distinguishes the book from other excellent textbooks on structural equation or latent variable models that either use a lot of maths or don’t cover the breadth of latent variable models that Beaujean is able to present within the 150 pages of this book. Actually, 150 pages is not quite true because the book also contains an extremely useful appendix of about 50 pages that discusses all the corey issues of things like different model fit indices and a glossary that would have cluttered the main text. The appendix also has the answers to the thought-through exercises that Beaujean gives at the end of each chapter. If you’ve got the time to run through at least some of these then you can learn quite a lot about latent variable modelling  – try it out!

Daniel Müllensiefen
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Where Patterns Meet Sounds – The Incredible Power of Music in Autism.

December 3rd, 2015 – Professor Adam Ockelford


Imagine listening to the radio at maximum volume in an unintelligible language and being entirely helpless in turning it off. After less than a minute or two, the sounds become overwhelming and distressing. Unfortunately, this experience is very much a reality for some individuals with autism. Autism is a disorder characterised by difficulties in socialisation, understanding metaphorical language and empathising with others. In 2014, it was estimated that approximately 1 in 68 children were on the spectrum, but autism could be as prevalent as 1 in 45 children (“Behind the Science”, 2016). The perceptual pain felt by some of these children can make everyday life incredibly difficult. Language was even described by one as being like “dynamite in their ears.”  Miraculously, though, music seems to provide an area of engagement for children with autism that can help them relax and focus their minds.

Professor Adam Ockelford, the Director of the Applied Music Research Centre at University of Roehampton in London, described some of his experiences with music and children with autism in a lecture in December 2015 at Goldsmiths University of London, as part of the invited speakers series for the Music, Mind and Brain Master’s programme.

To understand why music provides a valuable means of engagement for children with autism, Ockelford first proposes an ecological theory to understanding the developing of hearing. By 12 months of age, the brains of ‘neurotypical’ children have learnt to process sounds in three distinct streams, as shown in the following image (left). However, Ockelford suggests that, in autism, everyday sounds and even speech may be processed as music (see right image; for more information, see Ockelford, 2012).  


It’s well-known that individuals with autism have a love of patterns. Ockelford suggests that this love of pattern may impact on the understanding of speech, in that a child with autism may focus to a greater extent on its perceptual qualities, rather than use it for functional or semantic purposes. Children with autism have have a special affinity for music as Ockelford posits that music is around 80% repetitive. The brains of children with autism search for meaning in the world and are naturally attracted to music. If children with autism process speech as music, and music is highly repetitive, it’s understandable for these children to repeat what they hear. In fact, all children experience this phase in language development known as echolalia (i.e., repetition of heard speech). Typically-developing children quickly grow out of this phase as they learn the semantic meanings behind words. Children with autism can experience this phase for far longer – some remain in it for years, while others never grow out of it. As such, communication becomes an especially difficult task.

Outside of his academic life, Ockelford teaches music to children with autism. Many of these students use music as a means to understand and communicate with their world. Ockelford establishes significant relationships with his students through music. Such a relationship can be seen by following one of Ockelford´s students, Romy (see image below).

The first thing that mattered to Romy was her sound-making toys, and most adored was her small keyboard that helped her to learn how to play various songs. In some ways, the toy was easier for her to understand than peopPicture3le, who are by nature unpredictable, and Romy didn’t like to share her interest in music making with anyone else. But Ockelford was determined to show her that she could use her music to engage with others, and set out to play the piano with her. However, he quickly found that he couldn’t play music she already knew from her small keyboard because it would upset her, nor could he play something new. In the end, she allowed him to play a piece (‘Für Elise’) from her small keyboard slowly, approving one note at a time. But what would happen if he played something she didn’t like? How would she express her dissatisfaction? He taught her to express herself by playing two notes in succession, as if to say “shut up, shut up, shut up.” When Ockelford began to play part of a piece that Romy didn’t like, she first played those two notes in the same key as the piece, thus not having the anticipated effect. She realized this and switched to a different key quickly. This successfully made Ockelford stop playing. So music serves as a proxy-language for Romy. She found that with music, she could be in control of someone else without needing to be aggressive.

Another onPicture4e of Ockelford’s outstanding students is Derek, who has the amazing ability to perform many pieces after only a s
ingle hearing, successfully change keys instantaneously, and has virtuosic improvisational skills. Derek is a well-known savant, who often performs in major public concerts. He has even been featured in a TED Talk presentation and it’s easy to see his fantastic abilities.

From these examples, one can clearly see how strong the connection is between music and autism. As children with autism process everyday sounds and speech as music, it is logical to address the ways to most effectively provide an auditory environment to facilitate learning. Teachers may find it distressing when children with autism seem to disregard their instructions, under the assumption that they had the children’s undivided attention. However, what these teachers may not have understood is that, though the children were listening to their instructions, what they heard was the vocal fluctuations more than the semantic meanings behind the words.

Often, public education systems alienate autistic children by not providing an environment best suited for these children to thrive. Between the loud noises, fluorescent lights, and a jumble of voices, it is understandable that the “dynamite in my ears” phenomenon is a regular occurrence. A learning space more fitting for autistic children would be one that enhances their need for pattern and sound, while being sensitive to the nature of the stimuli presented. Many of these children have amazing capabilities that could flourish under the proper environment.


By Renee Schapiro, Heather Terry, and Fernanda Ureña



Behind the Science: New 1 in 45 autism prevalence survey. (2016). Retrieved from

Derek Paravicini and Adam Ockelford: In the key of genius. (2013, March). Retrieved from

Ockelford, A. (2012) Applied Musicology: Using Music Theory to Inform Music Psychology, Education and Therapy Research, Oxford University Press.

Ockelford, A. (2015). The impact of autism on musical development. Personal Collection of A. Ockelford, University of Roehampton, London, UK.









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The Pursuit of Happiness: Strong Emotional Responses to Music

Dr. Alexandra Lamont, February 26th   2015. 

“Describe in your own words the strongest, most intense experience of music that you have ever had.”

Please take a moment to think on this instruction. Does a strong emotional memory come to mind? If so, you have followed in the footsteps of volunteers who shared well over 1000 responses to this simple directive, used by Gabrielsson and Lindström (1995) to explore and categorise strong experiences to music (SEMs). Dr. Alexandra Lamont ( Senior Lecturer in Music Psychology at Keele University, has spent many years teasing apart questions inspired by the study of SEMs:

  • How does music make us happy?
  • Where, when and with whom do strong emotional responses to music happen?
  • Why does music contribute to our happiness?


While giving a lecture to our MSc Music, Mind & Brain ( class on Thursday 26th February 2015, Lamont suggested that there are two distinct ways of answering the questions above. Firstly, there is the traditional cognitive approach to wellbeing where music is studied by looking in detail at the underlying reward mechanisms in the brain. Conversely, the second more qualitative and phenomenological approach looks in detail at the stories people tell, how they tell them, and what people do or do not say which is important when considering the significance of SEMs. Lamont’s research has concentrated on this second approach by analysing SEMs, with a core focus on balanced happiness and wellbeing.

One of the main strengths of Lamont’s approach is the rationale behind it. Using the relatively new field of positive psychology, she argues that music has a unique potential to fulfil the three key elements that are essential for happiness and wellbeing: hedonism, engagement and meaning (Figure 1). Seligman’s theory (2002) states that we need a combination that incorporates all three elements in order to reach balanced happiness and wellbeing. Yet, how does music make us happy?

Captura de pantalla 2015-03-13 a la(s) 14.55.31

 Music listening is particularly unique because it can facilitate balanced happiness via a combination of these three routes.

Men play traditional gamelan percussion

Men play traditional Gamelan percussion

Hedonism or pleasure simply refers to the presence of positive affect and absence of negative affect. Music listening has the power to evoke a direct hedonistic route to happiness by boosting positive emotions, as Blood and Zatorre (2001) found in a landmark study. The authors demonstrated that positive responses to music were highly correlated to the same brain regions involved in pleasure and reward. Engagement can be described as gratification generated through absorption in a given activity; in a more colloquial way, it may be called ‘flow’. Listening to music has the potential for feeling fully immersed in a flow of energized focus, involvement and enjoyment. Meaning refers to going beyond oneself. Music is a good candidate to search for a ‘meaningful life’, creating a sense of identity and aesthetic connections with others. Thus, music listening is particularly unique because it can facilitate balanced happiness via a combination of these three routes, as shown in Figure 1.

Lamont sees the exploration of strong emotional responses to music as fundamental in our attempt to understand what the core drivers are for an individual’s happiness. Her grounded approach to music and emotion places great importance on the stories that people report, and she has found characteristics that directly match the three components of Seligman’s model. However, where when and with whom do strong emotional responses to music occur?


In one of her most prestigious works, Lamont (2011) analysed results from 81 undergraduates who responded to the same instruction: “Describe in your own words the strongest, most intense experience of music that you have ever had.” The listening experiences mainly occurred in live situations, such as music festivals and pop concerts (84.5% with other people and 82% while listening to pop music). There was a wide variety of music with examples ranging from Wagner to Cat Stevens, Rage Against The Machine to Keane. Participants reported strong experiences such as tears, thrills, and shivers down the spine. The results also showed a balance between expected and unexpected listening experiences, which overall were found to be overwhelmingly positive. Many of the responses from the study showed obvious links to hedonism:

“A few years ago, I got on stage with a ska band called Lightyear. I was quite drunk and so were my friends who were with me. I was dancing with the singer and everyone was going crazy. I just remem­ber thinking to myself no matter what life throws at you, you will always have music and it will always make you feel good.” (Matt).

This is not only an example of hedonism, but also of engagement and meaning, where Matt describes “thinking to myself” about the long-term effects music has on his life. The social context also came up frequently as a relevant influence:

“Listening to them [Radiohead] on CD is one thing, but when thousands of people surround you, singing to every word like you, the atmosphere’s electric, there’s no other feeling as strong, or intense, as that.” (Tom).


Lamont suggests that music is not simply for listening or playing pleasure, it is an essential quality in our lives and has the ability to improve our relationships and engage with life in a more meaningful and positive way. This supports Seligman and colleagues (2005) who suggested that the development of engagement and meaning are more crucial for life satisfaction than the pursuit of pleasure. Nevertheless, one question remains, why does music contribute to our happiness?

After being introduced to Lamont’s approach, we can say that strong emotional responses to music are mainly positive and occur in social contexts, however, the experiences are highly heterogeneous. Listening experiences also have the potential for generating happiness through association and reminiscence. A song that one day generates a strong emotional experience will probably evoke a similar feeling when heard again. Furthermore, Lamont (2012) showed that when playing music people also experience a large number of SEMs, suggesting that performing music provides the potential to attain hedonism, engagement and meaning.

To conclude, we have seen a new and more ecological approach to researching happiness when compared to the traditional brain centred trend in Psychology. Lamont’s views correspond with the idea of music as a powerful tool in our pursuit of happiness. We have seen strong emotional responses to music listening, namely people becoming absorbed, going beyond themselves and feeling intense positive emotions, thereby fulfilling the three routes to help achieve life satisfaction.


By Manuel Anglada-Tort & Pedro Kirk


Blood, A. J., & Zatorre, R. J. (2001). Intensely pleasurable responses to music correlate with activity in brain regions implicated in reward and emotion.Proceedings of the National Academy of Sciences98(20), 11818-11823.

Gabrielson, A. (2001). Emotions in strong experiences with music. In P. N. Juslin & J. A. Sloboda (Eds.), Music and emotion: Theory and research (pp. 431-449). Oxford: Oxford University Press.

Gabrielsson, A., & Lindström, S. (1995). Can strong experiences of music have therapeutic implications? (pp. 195-202). Springer Berlin Heidelberg.

Lamont, A. (2011). University students’ strong experiences of music Pleasure, engagement, and meaning. Musicae Scientiae15(2), 229-249.

Lamont, A. (2012). Emotion, engagement and meaning in strong experiences of music performance. Psychology of Music40(5), 574-594.

Seligman, M. E. P. (2002). Authentic happiness: Using the new positive psychology to realice your potential for lasting fulfillment. New York: Freww Press.

Seligman, M. E. P. (2005). A balanced psychology and a full life. In F. A. Huppert, N. Baylis, & B. Keverne (Eds.), The science of well-being (pp. 275-304). Oxford: Oxford University Press.

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Listen while you Learn? – The Effects of Background Music and Personality on Language Learning

Mats Küssner, February 5th 2015.

Could listening to background music when studying improve learning? Background music has often been claimed to have beneficial effects such as increasing focus, concentration, and productivity, as well as generally improving learning. Websites such as ‘focus@will’ ( and ‘Earworms Musical Brain Trainer’ ( have sung the praises of harnessing music to boost brain function. However, websites such as these often base their claims on spurious evidence, and usually have vested interests commercially. Also, background music has at times been shown to be ineffective or even detrimental in some contexts. Mats Küssner, from the Centre for Performance Science, at the Royal College of Music (, is a music psychologist who has studied the effects of background music on learning. He gave a lecture at Goldsmiths, University of London in February 2015, about these effects generally, and also about the specific role of personality in these effects. Are different cognitive tasks affected in different ways by background music, and why does personality have an impact on this?

Küssner emphasised the difficulty of finding a ‘one size fits all’ effect of background music on learning, as individual differences appear to be a crucial factor in the nature of any effects. Leaving this to one side for the moment however, according to Küssner the beneficial effects of background music have been displayed in the following:

  • Reading Comprehension (e.g. Kiger, 1989)
  • IQ tests (e.g. Cockerton, 1997)
  • Visual search tasks (e.g. Crust et al, 2004)
  • Foreign Vocabulary Learning (e.g. de Groot, 2006; Kang & Williamson, 2014)

Detrimental effects of background music on learning have been found in some of the same, and some different, tasks:

  • Reading Comprehension (e.g. Thompson et al, 2012; Avila et al, 2012)
  • Verbal Memory (e.g. Woo & Kanachi, 2005; Cassidy & MacDonald, 2007)
  • Visual Memory (e.g. Furnham & Bradley, 1997)
  • Recall of Numbers (e.g. Nittino, 1997; Alley & Greene, 2008)

In addition to this, other studies have often found no effect of background music at all (e.g. Pool et al, 2003). The study conducted by de Groot (2006) is especially relevant to the main focus of Küssner’s lecture, in that more learning occurred when background music was playing compared to when it was silent. De Groot presented 64 pairs of words, each comprising one native language and one foreign language word, at six separate times to participants. In a recall test one week later, typical and common words were learned better in general, compared with atypical and uncommon words, and background music appeared to improve learning of foreign words. Crucially however, although the effect of background music generalised across words, the effect did not generalise across participants. This implies that individual differences might account for the lack of a general effect. De Groot mentions that the results may be due to ‘individual learner differences’, but does not elaborate further. Could these differences include personality?

Hans Eysenck, most known for his work on intelligence and personality, proposed a theory of personality that included the key dimension ‘extraversion’ (1967). At one end of this scale, people who are ‘extraverts’ require a larger amount of external stimulation, and require this in order to maintain arousal (sensory alertness). In contrast, at the other end of this scale, ‘introverts’ require inner, mental stimulation in order to maintain their level of arousal, and are prone to losing energy after long social encounters. This relationship is shown in the graph below. Introverts tend to be in a higher state of arousal than extraverts, and overly high levels of arousal can impair performance, when levels of the hormone ‘cortisol’ are too high in the bloodstream. This is important, as it implies that this aspect of personality could be an important factor affecting language learning for example, in addition to any effects of background music. However, again there is mixed evidence both in favour and against these effects of extraversion. Could extraversion have an impact on language learning, in combination with background music?


This graphic shows the different optimum levels of arousal required for introverts and extraverts (

A potential solution to the problem of measuring personality, put forward by Mats Küssner in the lecture, is to measure cortical arousal as an indirect and more objective, biological measure of personality. Eysenck believed that levels of cortical arousal could be used as a biological measure of differences in extraversion. Cortical arousal is thought to be inversely proportional to ‘alpha activity’ in the brain; therefore extraverts should generally have higher levels of alpha activity than introverts. Yet again, there is mixed evidence for this relationship (e.g. Hagemann et al, 2009; Schmidtke & Heller, 2004)! However, it is a more objective measure than any other tests of extraversion. How could this relationship be used experimentally, in order to test whether background music and extraversion interact to affect learning?

Using a variation of de Groot’s (2006) study on foreign vocabulary learning, Küssner and his colleagues introduced the variable of extraversion. 15 highly extraverts and 16 highly introverts were used, split by high and low ‘alpha’ and ‘beta’ activity groups. They predicted that introverts, when learning with background music, would perform more poorly on the word recall task than when learning in silence. Extraverts were predicted to perform as well if not better on the word recall task when learning with background music compared with silence. More generally, people who had high cortical arousal were expected to perform more poorly on the task when background music was playing during learning, and those with low cortical arousal should be unaffected. This hypothesised interaction effect on word recall was not significant. However, there was an unexpected effect of cortical arousal in the beta band on word recall: individuals with high beta activity recalled more words than those with low beta activity. When this study was replicated however, no significant evidence whatsoever was found, apart from a beneficial effect of background music. This may have been due to there genuinely being no effects, or alternatively, it could have been caused by other individual differences such as musical training or neuroticism (another personality dimension).

It remains unclear as to whether listening to background music while studying verbal material has any beneficial effects on learning, and this could well depend on context, type of task, and most importantly individual differences. Any applications promoting possible positive effects should be treated carefully, especially as they often have their own commercial interests in mind. Although the importance of individual differences are clear, meaning any effects of background music are not generalizable, whether personality specifically has an impact has still not been shown conclusively. Mats Küssner mentioned the possible importance of other individual differences, such as musical training and neuroticism. This suggests that further research needs to be done using individual differences in the effects of background music on learning. Ultimately, if you enjoy listening to certain music when studying or working, some ambiguous scientific evidence shouldn’t put you off.

By Joe Newton


Alley, T. R., & Greene, M. E. (2008). The Relative and Perceived Impact of Irrelevant Speech, Vocal Music and Non-Vocal Music on Working Memory. Current Psychology, 27(4), 277-289.

Avila, C., Furnham, A., & McClelland, A. (2012). The Influence of Distracting Familiar Vocal Music on Cognitive Performance of Introverts and Extraverts. Psychology of Music, 40(1), 84-93.

Cassidy, G., & MacDonald, R. A. (2007). The Effect of Background Music and Background Noise on the Task Performance of Introverts and Extraverts. Psychology of Music, 35(3), 517-537.

Cockerton, T., Moore, S., & Norman, D. (1997). Cognitive Test Performance and Background Music. Perceptual and Motor Skills, 85(3f), 1435-1438.

Crust, L., Clough, P. J., & Robertson, C. (2004). Influence Of Music and Distraction on Visual Search Performance of Participants with High and Low Affect Intensity 1. Perceptual and motor skills, 98(3), 888-896.

De Groot, A. (2006). Effects of Stimulus Characteristics and Background Music on Foreign Language Vocabulary Learning and Forgetting. Language Learning, 56(3), 463-506.

Eysenck, H. J. (1967). The Biological Basis of Personality (Vol. 689). Transaction publishers.

Furnham, A., & Bradley, A. (1997). Music While you Work: The Differential Distraction of Background Music on the Cognitive Test Performance of Introverts and Extraverts. Applied Cognitive Psychology, 11(5), 445-455.

Hagemann, D., Hewig, J., Walter, C., Schankin, A., Danner, D., & Naumann, E. (2009). Positive Evidence for Eysenck’s Arousal Hypothesis: A Combined EEG and MRI Study with Multiple Measurement Occasions. Personality and Individual Differences, 47(7), 717-721.

Kang, H. J., & Williamson, V. J. (2014). Background Music can aid Second Language Learning. Psychology of Music, 42(5), 728-747.

Kiger, D. M. (1989). Effects of Music Information Load on a Reading Comprehension Task. Perceptual and Motor Skills, 69(2), 531-534.

Nittono, H. (1997). Background Instrumental Music and Serial Recall. Perceptual and Motor Skills, 84(3c), 1307-1313.

Pool, M. M., Koolstra, C. M., & Voort, T. H. (2003). The Impact of Background Radio and Television on High School Students’ Homework Performance. Journal of Communication, 53(1), 74-87.

Schmidtke, J. I., & Heller, W. (2004). Personality, Affect and EEG: Predicting Patterns of Regional Brain Activity Related to Extraversion and Neuroticism. Personality and Individual Differences, 36(3), 717-732.

Thompson, W. F., Schellenberg, E. G., & Letnic, A. K. (2012). Fast and Loud Background Music Disrupts Reading Comprehension. Psychology of Music, 40(6), 700-708.

Woo, E. W., & Kanachi, M. (2005). The Effects of Music Type and Volume on Short-Term Memory. Tohoku Psychologica Folia, 64, 68-76.

Further reading

Eysenck, H. J. (1968). Eysenck Personality Inventory. San Diego: Educational and Industrial Testing Service.

Eysenck, H. J., & Eysenck, M. W. (1987). Personality and Individual Differences. Plenum.

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Life through stained glass: The impact of autism on musical development

Professor Adam Ockelford, 30th October 2014.

Autistic children often show a fascination for music, but why is this the case? In October 2014 Professor Adam Ockelford of Roehampton University spoke to Goldsmiths’ Music, Mind and Brain students as part of the Invited Speaker series. He reflected on his experiences as both a music teacher and researcher working primarily with autistic individuals, and shared his insights regarding the impact of autism on their musical development.

Autism is a pervasive developmental disorder (meaning that it is characterised by delays in the development of many basic skills), the cause of which is still unknown. It is considered a “spectrum” disorder because of its wide ranging severity, and the variety of presentation in individuals. Despite a significant increase in the prevalence of autism in recent years (Elsabbagh et al., 2012), the disorder remains largely misunderstood in today’s society. Prof. Ockelford gave three key insights into what autism might feel like from the inside:

Autistic individuals focus on detail rather than a coherent whole – the world is seen like a jumbled stained glass window

Autistic individuals focus on detail rather than a coherent whole – the world is seen like a jumbled stained glass window

1) Fragmented perception. Prof. Ockelford used an analogy of a stained glass window in which the pieces are jumbled to describe autistic individuals’ focus on detail at the expense of the perception of a coherent whole. This phenomenon is explained by Happé’s (2013) “Weak central coherence theory” and is linked to a fascination with patterns and detail, which is exhibited by artists with autism such as the renowned Stephen Wiltshire (click here to see some of his work).

2) Difficulties with feelings and particularly with understanding the emotions of others. This may be the result of problems with Theory of Mind”, a term initially coined by Simon Baron-Cohen to describe the ability to “impute beliefs to others and to predict their behaviour” (Baron-Cohen, Leslie, & Frith, 1985).

3) Finding language distressing, or as Prof. Ockelford described it “like dynamite in their ears”. He likened their difficulty in understanding language to sitting in a room full of radios in various languages and not being able to turn them off, or focus on a single voice.

Although these three facets might seem like deficits, when thinking about them in terms of music we can see them in a different light. Weak central coherence may explain the extraordinary fact that absolute pitch (the ability to identify a note without any reference tone), is a lot more common in the autistic population (1 in 20) compared to the general population (1 in 10,000, Heaton, 2009). One of Ockelford’s students, Freddie, is an incredible example of an autistic child with absolute pitch: he has no need to press down the keys on the piano because he can hear the notes in his head and sings them aloud -pressing the key down is just unnecessary effort!

Ockelford and student, Freddie, who would usually sing the notes he intended rather than press down the keys

Ockelford and student, Freddie, who would usually sing the notes he intended, rather than press down the keys

Furthermore, despite emotions being a problem for most autistic individuals, there is evidence to suggest that they can understand them in music (Allen, Hill, & Heaton, 2009).

As for language problems, Prof. Ockelford illustrates that music is language to many of his students.

Prof. Ockelford suggests that the effects of autism on musicality are due to a tendency in early development for autistic individuals to process everyday sounds in terms of their perceptual quality rather than function. Moreover, Ockelford proposes that whilst neurotypical individuals develop distinct sound processing streams for music, everyday sounds, and language, in those with autism these streams are blurred, and thus all sounds are processed similarly, lacking input from top-down contextual information.

For example, Ockelford describes individuals who are fascinated with everyday sound, and use everyday objects to proactively create sounds, such as making a ‘plant pot gamelan’. Ockelford proposes that sounds in our environment that we tend to ignore, many autistic individuals perceive and process in the way that we process music.

It is no wonder, then, that autism can often lead to enhanced, and occasionally exceptional, musicality. One such example is Derek Paravicini, one of Ockelford’s autistic and blind students who has developed into an extraordinary and unique pianist. Watch this TED talk and you’ll see what we mean:

Musicality isn’t just a ‘side-effect’ of autism, but can also be an incredibly useful tool to autistic individuals, allowing them to create an expressive language, or even a proxy-language. Another of Prof. Ockelford’s students, Theo, communicated through a series of musical fragments that only his mother understood, for example humming a little phrase of “Singing in the rain” meant that the truck he wanted to make needed a roof. Much of music therapy work with autistic individuals aims to develop communication skills, using musical interaction to learn turn-taking and shared attention.

Ockelford and student, Romy, at the piano - Romy is an "obsessive transposer", changing key so quickly that it is hard for Ockelford to keep up

Ockelford and student, Romy, at the piano – Romy is an “obsessive transposer”, changing key so quickly that it is hard for Ockelford to keep up

Each of the students that Prof. Ockelford introduced to us via various video clips had their own extraordinary quirks. For example, one student would only play in the notoriously tricky key of F# major. Another would switch through keys so quickly it was difficult for Ockelford to keep up. Ockelford proposed that this demonstrates the capacity of music to give these children control over their environment and the people around them, something which is essential in their development and massively improves their self-esteem.

Whilst most of Prof. Ockelford’s theories and ideas are based on case studies, emerging evidence is backing him up. For example, Lim (2010) found that music training was more effective than speech training in improving verbal production in low functioning autistic individuals. Another study found that music sessions were much more likely than play sessions to evoke engagement and ‘joy’ in autistic individuals (Kim, Wigram, & Gold, 2009).

Prof. Ockelford set out to explain how autism affects musical development, however it became evident throughout his talk that there is not only an impact of autism on musical development, but also an impact of music on the development of autistic children. This powerful bond between autism and music should be exploited more often, not only to enhance the lives of autistic individuals, but to further our own understanding of both music and autism.

By Suzie Capps, Chris Blake & Hannah Filer

Further reading:

Ockelford, A. (2007). In the key of genius: The extraordinary life of Derek Paravicini. London: Hutchinson.

Ockelford, A. (2013). Music, language and autism. London: Jessica Kingsley


Allen, R., Hill, E., & Heaton, P. (2009). `Hath charms to soothe … ‘An exploratory study of how high-functioning adults with ASD experience music. Autism, 13(1), 21-41.

Baron-Cohen, S., Leslie, A., & Frith, U. (1985). Does the autistic child have a “theory of mind”? Cognition, 21, 37-46.

Elsabbagh, M., Divan, G., Koh, Y. J., Kim, Y. S., Kauchali, S., Marcín, C., … Fombonne, E. (2012). Global prevalence of autism and other pervasive developmental disorders. Autism Research, 5(3), 160-179.

Happé, F. (2013). Weak Central Coherence. In F. Volkmar (Ed.), Encyclopedia of Autism Spectrum Disorders (pp. 3344-3346): New York: Springer.

Heaton, P. (2009). Assessing musical skills in autistic children who are not savants. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1522), 1443-1447.

Kim, J., Wigram, T., & Gold, C. (2008). The effects of improvisational music therapy on joint attention behaviors in autistic children: a randomized controlled study. Journal of autism and developmental disorders, 38(9), 1758-1766.

Lim, H. (2010). Effect of “Developmental Speech and Language Training Through Music” on Speech Production in Children with Autism Spectrum Disorders. Journal of Music Therapy, 47(1), 2-26.

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