“Will the real Slim Shady please stand up?”

Rhythm in speech and music

May I have your attention please?”

1

Do you remember back in 2000, when Marshall Mathers, better known as Eminem, tried to find out who “The Real Slim Shady” was? You might have known immediately that he was referring to his alter ego, but would you have considered yourself a Slim Shady? If so, you were right.

In their latest series of experiments, published in the journals Proceedings of the Royal Society B and Hearing Research, Manon Grube of the University of Newcastle (UK) and her team have found out it is actually not only rappers who need an understanding of rhythm in their language, we all do.

While talking, people put together sequences of rhythmic and melodic patterns to convey their intentions. If the rhythm was “wrong” in some way, the message can easily be misunderstood (Imagine Marshall Mathers asking for your attention in this way: “Ma-y-I-ha-ve-you-r-at-ten-tion-plea-se?”). This may be why many rappers tend to carry a strong sense of time, not only when spitting bars with a good flow, but also when plainly speaking.

One of the studies (Grube et al., 2012) showed how closely related the phonological skill you need to speak is to the ability to process short sequences of rhythmic patterns. 238 eleven-year-olds from a school in Newcastle were given standard language & intelligence tests and had their pitch and rhythm perception tested. Specifically, the ability to perceive isochrony violations in short sequences reveals a link between rhythm perception and speech processing, where anisochrony detection is the ability to notice when something is ‘just’ out of time (‘off-beat’). In short, if you are better at detecting whether something is just off-beat, then you will likely be better at processing language and even at producing speech. In a follow-up study (Grube et al. 2014), to test whether this was true for people with atypical development, 28 students with dyslexic traits from the same school underwent the same procedure and the results were not replicated, meaning it was only the case for typically developing children.

In a further study of 24 undergraduates (2013), Grube et al. found that the rhythm perception for longer, more complex ‘roughly regular’ sequences played a role in language processing, specifically in reading. This differed from the 11 year-olds, for whom the perception for shorter rhythmic sequences was more important. In their present work at TU Berlin, Grube and colleagues are tracing the neural time signature of the processing of more complex sequences with a ‘pseudo-rhythmic’ beat similar to that of speech.

And every single person is a Slim Shady lurking”

If so, where is this rhythm processing taking place?

2In preceding studies on these aspects of rhythm perception, Grube and colleagues showed evidence, using techniques varying from transcranial magnetic stimulation (TMS) to functional magnetic resonance imaging (fMRI) (Grube et al., 2010; Teki et al., 2011), that specific brain areas play a differential role in processing different kinds of timing mechanisms. Teki et al. (2011) measured the perception of rhythmic timing in the human brain using fMRI and found what is shown in the picture (in grey yellow and green). When participants focused on the absolute duration of a series of time intervals, the cerebellum and inferior olive (marked yellow in the picture), was activated. However, when participants perceived time intervals compared to a regular beat, the putamen and the neocortex (green), were activated. In most recent work, Grube et al. (in prep.) investigated which brain structures supports rhythm processing and its relationship with speech and language skill during adolescent development. Using structural MRI on 42 participants, their initial results suggest that parts of the cerebellum are specific for rhythm, whilst an area around the left intra-parietal sulcus supports the relationship with language.

So won’t the real Slim Shady please stand up […]?”

What can impairments tell us about these regions?

jpgThe cerebellum is one part of the brain that is involved largely in motor control. In 2010, Grube et al. found that patients with cerebellar degeneration showed a significant deficit in duration-, but not beat-based timing, supporting the existence of functionally distinct aspects of rhythm processing. The basal ganglia, a structure consisting of many nuclei including the putamen, controls our voluntary motor movements and is involved in learning and emotion processes. In 2014, Cope et al. found that patients with basal ganglia disease showed deficiencies in both duration- and beat-based tasks. This finding provides evidence for some functional link, i.e. a differential involvement of both types of perceptual timing (Teki et al., 2012) as opposed to the clear function divide suggested by Teki et al. (2011). Consistent with this, Launay et al. (2014) found that participants with dysrhythmia showed an opposite dissociation; an impairment in beat-, but not duration-based timing. In conclusion, these findings provide evidence for a more complex model of rhythm processing in humans than has been previously proposed.

This research is still very much in its early stages, and a fantastic insight into the way we understand ourselves, our faculties of action and perception and the role for timing in them. Further examination will need to be conducted in order to reveal just how the basal ganglia and cerebellum and cortex interact in rhythm perception and speech production. The finding that a strong sense of rhythm can affect our propensity for language is bound to lead on to many interesting investigations in the future. With this in mind Eminem seems to be right in saying:

Guess there’s a Slim Shady in all of us […] let’s all stand up.”

Written by: Natalie Kohler, Sarah Charles & Connor Higgins, based on a lecture given by Dr. Manon Grube (Thursday 29th October, 2015)

References:

Eminem (2000). The Real Slim Shady. The Marshall Mathers LP, Aftermath Entertainment.

Cope, T. E., Grube, M., Singh, B., Burn, D. J. & Griffiths, T. D. (2014). The basal ganglia in perceptual timing: Timing performance in Multiple System Atrophy and Huntington’s disease. Neuropsychologia, 52, 73-81.

Grube, M., Cooper, F. E., Chinnery, P. F. & Griffiths, T. D. (2010). Dissociation of duration-based and beat-based auditory timing in cerebellar degeneration. Proceedings of the National Academy of Sciences, 107(25), 11597-11601.

Grube, M., Cooper, F. E. & Griffiths, T. D. (2013). Auditory temporal-regularity processing correlates with language and literacy skill in early adulthood. Cognitive neuroscience, 4(3-4), 225-230.

Grube, M., Kumar, S., Cooper, F. E., Turton, S. & Griffiths, T. D. (2012). Auditory sequence analysis and phonological skill. Proceedings of the Royal Society of London B: Biological Sciences, 279(1746), 4496-4504.

Launay, J., Grube, M., & Stewart, L. (2014). Dysrhythmia: a specific congenital rhythm perception deficit. Frontiers in psychology, 5.

Teki S., Grube M., Griffiths T.D.. (2012) A unified model of time perception accounts for both duration-based and beat-based timing mechanisms. Front Integr Neurosci 5, 90.

Teki, S., Grube, M., Kumar, S. & Griffiths, T. D. (2011). Distinct neural substrates of duration-based and beat-based auditory timing. The Journal of Neuroscience, 31(10), 3805-3812.

Picture 1: http://www.collegedj.net/wp-content/uploads/2011/02/Dr-Dre-Eminem.jpg (viewed: November 16, 2015).

Picture 2: Teki, S., Grube, M., Kumar, S. & Griffiths, T. D. (2011). Distinct neural substrates of duration-based and beat-based auditory timing. The Journal of Neuroscience, 31(10), 3810.

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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).

Popchoir.png

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).

Icebreaker.png

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).

Goal.png

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: http://www.gold.ac.uk/pg/msc-music-mind-brain/.


 

References:

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.
http://www.theguardian.com/commentisfree/2014/oct/14/age-of-loneliness-killing-us

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. http://www.theguardian.com/commentisfree/2015/oct/23/loneliness-health-dangerous-old-age-death

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).  

Picture1Picture2

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

 

References

Behind the Science: New 1 in 45 autism prevalence survey. (2016). Retrieved from https://www.autismspeaks.org/blog/2015/11/16/behind-science-new-1-45-autism-prevalence-survey

Derek Paravicini and Adam Ockelford: In the key of genius. (2013, March). Retrieved from https://www.ted.com/talks/derek_paravicini_and_adam_ockelford_in_the_key_of_genius?language=e

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 (https://www.keele.ac.uk/psychology/people/alexandralamont/) 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?

6

While giving a lecture to our MSc Music, Mind & Brain (http://www.gold.ac.uk/pg/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?

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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).

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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.

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By Manuel Anglada-Tort & Pedro Kirk


References

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’ (www.focusatwill.com) and ‘Earworms Musical Brain Trainer’ (www.earwormslearning.com) 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 (www.rcm.ac.uk/cps), 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?

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This graphic shows the different optimum levels of arousal required for introverts and extraverts (www.fastcompany.com)

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

References

www.focusatwill.com

www.earwormslearning.com

www.rcm.ac.uk/cps

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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